introduction to ibm spss modeler text analytics...

0A104G www.globalknowledge.be [email protected] 0800/84.009

Introduction to IBM SPSS Modeler Text Analytics (v15)

Duration: 2 Days Course Code: 0A104G

Overview:

Introduction to IBM SPSS Modeler Text Analytics is a two-day instructor led classroom course that teaches you how to analyze text data usingIBM SPSS Modeler Text Analytics. You will see the complete set of steps involved in working with text data, from reading the text data tocreating the final categories for additional analysis. After the final model has been created, there is an example of how to apply the model toperform Churn analysis. Topics include how to automatically and manually create and modify categories, how to edit synonym, type, andexclude dictionaries, and how to perform Text Link Analysis and Cluster Analysis with text data. Also included are examples of how to createresource templates and Text Analysis packages to share work with other projects and other users.

Target Audience:

This course is for:anyone who needs to analyze text data for the purpose of creating predictive models or reports based in part on textdatausers of IBM SPSS Modeler Text Analytics

Objectives:

Please refer to course overview.

Prerequisites:

You should have completed:

"Introduction to IBM SPSS Modeler and Data Mining" course orhave experience with IBM SPSS Modeler

You should have:

General computer literacyPractical experience with coding text data is not a prerequisite butwould be helpful.


Content:

line line lineDescribe text mining and its relationship to Explain CRISP-DM methodology as it Describe text mining and its relationship todata mining applies to text mining data miningExplain the text mining nodes available in Describe the steps in a text mining Explain the text mining nodes available inModeler project ModelerRead text from documents A Text Mining Example Read text from documentsDescribe linguistic analysis Complete a typical text mining modeling Describe linguistic analysisDevelop a text mining concept model session Develop a text mining concept modelUse the Interactive Workbench Reading Text Data Use the Interactive WorkbenchDescribe the resource template View text from documents within Modeler Describe the resource templateLinguistic Editing Preparation Read text from Web Feeds Linguistic Editing PreparationReview Advanced Resources Linguistic Analysis and Text Mining Review Advanced ResourcesUse Text Link Analysis interactively Describe the process of text extraction Use Text Link Analysis interactivelyCreate clusters Describe categorization of terms and Create clustersDescribe approaches to categorization concepts Describe approaches to categorizationDevelop categorization strategy Describe Templates and Libraries Develop categorization strategyUse the Template Editor Describe Text Analysis Packages Use the Template EditorExplore text mining models Creating a Text Mining Concept Model Explore text mining models

Compare models based on usingdifferent Resource Templates

line Score model data lineExplain CRISP-DM methodology as it Analyze model results Explain CRISP-DM methodology as itapplies to text mining Extracted Results in the Interactive applies to text miningDescribe the steps in a text mining project Workbench Describe the steps in a text mining projectA Text Mining Example Review extracted concepts A Text Mining ExampleComplete a typical text mining modeling Review extracted types Complete a typical text mining modelingsession Update the modeling node sessionReading Text Data Linguistic Resources Reading Text DataView text from documents within Modeler Review libraries View text from documents within ModelerRead text from Web Feeds Review Dictionaries Read text from Web FeedsLinguistic Analysis and Text Mining Manage libraries Linguistic Analysis and Text MiningDescribe the process of text extraction Editing Dictionaries Describe the process of text extractionDescribe categorization of terms and Develop editing strategy Describe categorization of terms andconcepts Add Type definitions conceptsDescribe Templates and Libraries Add Synonym definitions Describe Templates and LibrariesDescribe Text Analysis Packages Add Exclusion definitions Describe Text Analysis PackagesCreating a Text Mining Concept Model Text re-extraction to review modifications Creating a Text Mining Concept ModelCompare models based on using different Editing Advanced Resources Compare models based on using differentResource Templates Add fuzzy grouping exceptions Resource TemplatesScore model data Review Text Link Rules Score model dataAnalyze model results Text Link Analysis Analyze model resultsExtracted Results in the Interactive Use visualization pane Extracted Results in the InteractiveWorkbench Use Text Link Analysis node WorkbenchReview extracted concepts Create categories from a pattern Review extracted conceptsReview extracted types Clustering Concepts Review extracted typesUpdate the modeling node Use visualization pane Update the modeling nodeLinguistic Resources Create categories from a cluster Linguistic ResourcesReview libraries Categorization Techniques Review librariesReview Dictionaries Describe linguistic based categorization Review DictionariesManage libraries Describe frequency based categorization Manage librariesEditing Dictionaries Describe results of different Editing DictionariesDevelop editing strategy categorization methods Develop editing strategyAdd Type definitions Creating Categories Add Type definitionsAdd Synonym definitions Create categories automatically Add Synonym definitionsAdd Exclusion definitions Create categories manually Add Exclusion definitionsText re-extraction to review modifications Use conditional rules to create categories Text re-extraction to review modificationsEditing Advanced Resources Assess category overlap Editing Advanced ResourcesAdd fuzzy grouping exceptions Extend categories Add fuzzy grouping exceptionsReview Text Link Rules Import coding frames Review Text Link RulesText Link Analysis Managing Linguistic Resources Text Link AnalysisUse visualization pane Save resource templates Use visualization paneUse Text Link Analysis node Describe local and public libraries Use Text Link Analysis nodeCreate categories from a pattern Publishing libraries Create categories from a pattern


Clustering Concepts Share libraries Clustering ConceptsUse visualization pane Share templates Use visualization paneCreate categories from a cluster Create Text Analysis Packages Create categories from a clusterCategorization Techniques Backup resources Categorization TechniquesDescribe linguistic based categorization Using Text Mining Models Describe linguistic based categorizationDescribe frequency based categorization Develop a model with quantitative and Describe frequency based categorizationDescribe results of different categorization qualitative data Describe results of different categorizationmethods Score new data methodsCreating Categories Creating CategoriesCreate categories automatically Create categories automaticallyCreate categories manually line Create categories manuallyUse conditional rules to create categories Describe text mining and its relationship Use conditional rules to create categoriesAssess category overlap to data mining Assess category overlapExtend categories Explain the text mining nodes available in Extend categoriesImport coding frames Modeler Import coding framesManaging Linguistic Resources Read text from documents Managing Linguistic ResourcesSave resource templates Describe linguistic analysis Save resource templatesDescribe local and public libraries Develop a text mining concept model Describe local and public librariesPublishing libraries Use the Interactive Workbench Publishing librariesShare libraries Describe the resource template Share librariesShare templates Linguistic Editing Preparation Share templatesCreate Text Analysis Packages Review Advanced Resources Create Text Analysis PackagesBackup resources Use Text Link Analysis interactively Backup resourcesUsing Text Mining Models Create clusters Using Text Mining ModelsDevelop a model with quantitative and Describe approaches to categorization Develop a model with quantitative andqualitative data Develop categorization strategy qualitative dataScore new data Use the Template Editor Score new data

Explore text mining models

line lineExplain CRISP-DM methodology as it line Explain CRISP-DM methodology as itapplies to text mining Explain CRISP-DM methodology as it applies to text miningDescribe the steps in a text mining project applies to text mining Describe the steps in a text mining projectA Text Mining Example Describe the steps in a text mining A Text Mining ExampleComplete a typical text mining modeling project Complete a typical text mining modelingsession A Text Mining Example sessionReading Text Data Complete a typical text mining modeling Reading Text DataView text from documents within Modeler session View text from documents within ModelerRead text from Web Feeds Reading Text Data Read text from Web FeedsLinguistic Analysis and Text Mining View text from documents within Modeler Linguistic Analysis and Text MiningDescribe the process of text extraction Read text from Web Feeds Describe the process of text extractionDescribe categorization of terms and Linguistic Analysis and Text Mining Describe categorization of terms andconcepts Describe the process of text extraction conceptsDescribe Templates and Libraries Describe categorization of terms and Describe Templates and LibrariesDescribe Text Analysis Packages concepts Describe Text Analysis PackagesCreating a Text Mining Concept Model Describe Templates and Libraries Creating a Text Mining Concept ModelCompare models based on using different Describe Text Analysis Packages Compare models based on using differentResource Templates Creating a Text Mining Concept Model Resource TemplatesScore model data Compare models based on using Score model dataAnalyze model results different Resource Templates Analyze model resultsExtracted Results in the Interactive Score model data Extracted Results in the InteractiveWorkbench Analyze model results WorkbenchReview extracted concepts Extracted Results in the Interactive Review extracted conceptsReview extracted types Workbench Review extracted typesUpdate the modeling node Review extracted concepts Update the modeling nodeLinguistic Resources Review extracted types Linguistic ResourcesReview libraries Update the modeling node Review librariesReview Dictionaries Linguistic Resources Review DictionariesManage libraries Review libraries Manage librariesEditing Dictionaries Review Dictionaries Editing DictionariesDevelop editing strategy Manage libraries Develop editing strategyAdd Type definitions Editing Dictionaries Add Type definitionsAdd Synonym definitions Develop editing strategy Add Synonym definitionsAdd Exclusion definitions Add Type definitions Add Exclusion definitionsText re-extraction to review modifications Add Synonym definitions Text re-extraction to review modificationsEditing Advanced Resources Add Exclusion definitions Editing Advanced Resources


Add fuzzy grouping exceptions Text re-extraction to review modifications Add fuzzy grouping exceptionsReview Text Link Rules Editing Advanced Resources Review Text Link RulesText Link Analysis Add fuzzy grouping exceptions Text Link AnalysisUse visualization pane Review Text Link Rules Use visualization paneUse Text Link Analysis node Text Link Analysis Use Text Link Analysis nodeCreate categories from a pattern Use visualization pane Create categories from a patternClustering Concepts Use Text Link Analysis node Clustering ConceptsUse visualization pane Create categories from a pattern Use visualization paneCreate categories from a cluster Clustering Concepts Create categories from a clusterCategorization Techniques Use visualization pane Categorization TechniquesDescribe linguistic based categorization Create categories from a cluster Describe linguistic based categorizationDescribe frequency based categorization Categorization Techniques Describe frequency based categorizationDescribe results of different categorization Describe linguistic based categorization Describe results of different categorizationmethods Describe frequency based categorization methodsCreating Categories Describe results of different Creating CategoriesCreate categories automatically categorization methods Create categories automaticallyCreate categories manually Creating Categories Create categories manuallyUse conditional rules to create categories Create categories automatically Use conditional rules to create categoriesAssess category overlap Create categories manually Assess category overlapExtend categories Use conditional rules to create categories Extend categoriesImport coding frames Assess category overlap Import coding framesManaging Linguistic Resources Extend categories Managing Linguistic ResourcesSave resource templates Import coding frames Save resource templatesDescribe local and public libraries Managing Linguistic Resources Describe local and public librariesPublishing libraries Save resource templates Publishing librariesShare libraries Describe local and public libraries Share librariesShare templates Publishing libraries Share templatesCreate Text Analysis Packages Share libraries Create Text Analysis PackagesBackup resources Share templates Backup resourcesUsing Text Mining Models Create Text Analysis Packages Using Text Mining ModelsDevelop a model with quantitative and Backup resources Develop a model with quantitative andqualitative data Using Text Mining Models qualitative dataScore new data Develop a model with quantitative and Score new data

qualitative dataScore new data

line lineExplain CRISP-DM methodology as it Explain CRISP-DM methodology as itapplies to text mining line applies to text miningDescribe the steps in a text mining project Explain CRISP-DM methodology as it Describe the steps in a text mining projectA Text Mining Example applies to text mining A Text Mining ExampleComplete a typical text mining modeling Describe the steps in a text mining Complete a typical text mining modelingsession project sessionReading Text Data A Text Mining Example Reading Text DataView text from documents within Modeler Complete a typical text mining modeling View text from documents within ModelerRead text from Web Feeds session Read text from Web FeedsLinguistic Analysis and Text Mining Reading Text Data Linguistic Analysis and Text MiningDescribe the process of text extraction View text from documents within Modeler Describe the process of text extractionDescribe categorization of terms and Read text from Web Feeds Describe categorization of terms andconcepts Linguistic Analysis and Text Mining conceptsDescribe Templates and Libraries Describe the process of text extraction Describe Templates and LibrariesDescribe Text Analysis Packages Describe categorization of terms and Describe Text Analysis PackagesCreating a Text Mining Concept Model concepts Creating a Text Mining Concept ModelCompare models based on using different Describe Templates and Libraries Compare models based on using differentResource Templates Describe Text Analysis Packages Resource TemplatesScore model data Creating a Text Mining Concept Model Score model dataAnalyze model results Compare models based on using Analyze model resultsExtracted Results in the Interactive different Resource Templates Extracted Results in the InteractiveWorkbench Score model data WorkbenchReview extracted concepts Analyze model results Review extracted conceptsReview extracted types Extracted Results in the Interactive Review extracted typesUpdate the modeling node Workbench Update the modeling nodeLinguistic Resources Review extracted concepts Linguistic ResourcesReview libraries Review extracted types Review librariesReview Dictionaries Update the modeling node Review DictionariesManage libraries Linguistic Resources Manage librariesEditing Dictionaries Review libraries Editing Dictionaries


Develop editing strategy Review Dictionaries Develop editing strategyAdd Type definitions Manage libraries Add Type definitionsAdd Synonym definitions Editing Dictionaries Add Synonym definitionsAdd Exclusion definitions Develop editing strategy Add Exclusion definitionsText re-extraction to review modifications Add Type definitions Text re-extraction to review modificationsEditing Advanced Resources Add Synonym definitions Editing Advanced ResourcesAdd fuzzy grouping exceptions Add Exclusion definitions Add fuzzy grouping exceptionsReview Text Link Rules Text re-extraction to review modifications Review Text Link RulesText Link Analysis Editing Advanced Resources Text Link AnalysisUse visualization pane Add fuzzy grouping exceptions Use visualization paneUse Text Link Analysis node Review Text Link Rules Use Text Link Analysis nodeCreate categories from a pattern Text Link Analysis Create categories from a patternClustering Concepts Use visualization pane Clustering ConceptsUse visualization pane Use Text Link Analysis node Use visualization paneCreate categories from a cluster Create categories from a pattern Create categories from a clusterCategorization Techniques Clustering Concepts Categorization TechniquesDescribe linguistic based categorization Use visualization pane Describe linguistic based categorizationDescribe frequency based categorization Create categories from a cluster Describe frequency based categorizationDescribe results of different categorization Categorization Techniques Describe results of different categorizationmethods Describe linguistic based categorization methodsCreating Categories Describe frequency based categorization Creating CategoriesCreate categories automatically Describe results of different Create categories automaticallyCreate categories manually categorization methods Create categories manuallyUse conditional rules to create categories Creating Categories Use conditional rules to create categoriesAssess category overlap Create categories automatically Assess category overlapExtend categories Create categories manually Extend categoriesImport coding frames Use conditional rules to create categories Import coding framesManaging Linguistic Resources Assess category overlap Managing Linguistic ResourcesSave resource templates Extend categories Save resource templatesDescribe local and public libraries Import coding frames Describe local and public librariesPublishing libraries Managing Linguistic Resources Publishing librariesShare libraries Save resource templates Share librariesShare templates Describe local and public libraries Share templatesCreate Text Analysis Packages Publishing libraries Create Text Analysis PackagesBackup resources Share libraries Backup resourcesUsing Text Mining Models Share templates Using Text Mining ModelsDevelop a model with quantitative and Create Text Analysis Packages Develop a model with quantitative andqualitative data Backup resources qualitative dataScore new data Using Text Mining Models Score new data

Develop a model with quantitative andqualitative data

line Score new data lineDescribe text mining and its relationship to Explain CRISP-DM methodology as itdata mining applies to text miningExplain the text mining nodes available in line Describe the steps in a text mining projectModeler Explain CRISP-DM methodology as it A Text Mining ExampleRead text from documents applies to text mining Complete a typical text mining modelingDescribe linguistic analysis Describe the steps in a text mining sessionDevelop a text mining concept model project Reading Text DataUse the Interactive Workbench A Text Mining Example View text from documents within ModelerDescribe the resource template Complete a typical text mining modeling Read text from Web FeedsLinguistic Editing Preparation session Linguistic Analysis and Text MiningReview Advanced Resources Reading Text Data Describe the process of text extractionUse Text Link Analysis interactively View text from documents within Modeler Describe categorization of terms andCreate clusters Read text from Web Feeds conceptsDescribe approaches to categorization Linguistic Analysis and Text Mining Describe Templates and LibrariesDevelop categorization strategy Describe the process of text extraction Describe Text Analysis PackagesUse the Template Editor Describe categorization of terms and Creating a Text Mining Concept ModelExplore text mining models concepts Compare models based on using different

Describe Templates and Libraries Resource TemplatesDescribe Text Analysis Packages Score model data

line Creating a Text Mining Concept Model Analyze model resultsExplain CRISP-DM methodology as it Compare models based on using Extracted Results in the Interactiveapplies to text mining different Resource Templates WorkbenchDescribe the steps in a text mining project Score model data Review extracted conceptsA Text Mining Example Analyze model results Review extracted types


Complete a typical text mining modeling Extracted Results in the Interactive Update the modeling nodesession Workbench Linguistic ResourcesReading Text Data Review extracted concepts Review librariesView text from documents within Modeler Review extracted types Review DictionariesRead text from Web Feeds Update the modeling node Manage librariesLinguistic Analysis and Text Mining Linguistic Resources Editing DictionariesDescribe the process of text extraction Review libraries Develop editing strategyDescribe categorization of terms and Review Dictionaries Add Type definitionsconcepts Manage libraries Add Synonym definitionsDescribe Templates and Libraries Editing Dictionaries Add Exclusion definitionsDescribe Text Analysis Packages Develop editing strategy Text re-extraction to review modificationsCreating a Text Mining Concept Model Add Type definitions Editing Advanced ResourcesCompare models based on using different Add Synonym definitions Add fuzzy grouping exceptionsResource Templates Add Exclusion definitions Review Text Link RulesScore model data Text re-extraction to review modifications Text Link AnalysisAnalyze model results Editing Advanced Resources Use visualization paneExtracted Results in the Interactive Add fuzzy grouping exceptions Use Text Link Analysis nodeWorkbench Review Text Link Rules Create categories from a patternReview extracted concepts Text Link Analysis Clustering ConceptsReview extracted types Use visualization pane Use visualization paneUpdate the modeling node Use Text Link Analysis node Create categories from a clusterLinguistic Resources Create categories from a pattern Categorization TechniquesReview libraries Clustering Concepts Describe linguistic based categorizationReview Dictionaries Use visualization pane Describe frequency based categorizationManage libraries Create categories from a cluster Describe results of different categorizationEditing Dictionaries Categorization Techniques methodsDevelop editing strategy Describe linguistic based categorization Creating CategoriesAdd Type definitions Describe frequency based categorization Create categories automaticallyAdd Synonym definitions Describe results of different Create categories manuallyAdd Exclusion definitions categorization methods Use conditional rules to create categoriesText re-extraction to review modifications Creating Categories Assess category overlapEditing Advanced Resources Create categories automatically Extend categoriesAdd fuzzy grouping exceptions Create categories manually Import coding framesReview Text Link Rules Use conditional rules to create categories Managing Linguistic ResourcesText Link Analysis Assess category overlap Save resource templatesUse visualization pane Extend categories Describe local and public librariesUse Text Link Analysis node Import coding frames Publishing librariesCreate categories from a pattern Managing Linguistic Resources Share librariesClustering Concepts Save resource templates Share templatesUse visualization pane Describe local and public libraries Create Text Analysis PackagesCreate categories from a cluster Publishing libraries Backup resourcesCategorization Techniques Share libraries Using Text Mining ModelsDescribe linguistic based categorization Share templates Develop a model with quantitative andDescribe frequency based categorization Create Text Analysis Packages qualitative dataDescribe results of different categorization Backup resources Score new datamethods Using Text Mining ModelsCreating Categories Develop a model with quantitative andCreate categories automatically qualitative data lineCreate categories manually Score new data Describe text mining and its relationship toUse conditional rules to create categories data miningAssess category overlap Explain the text mining nodes available inExtend categories line ModelerImport coding frames Explain CRISP-DM methodology as it Read text from documentsManaging Linguistic Resources applies to text mining Describe linguistic analysisSave resource templates Describe the steps in a text mining Develop a text mining concept modelDescribe local and public libraries project Use the Interactive WorkbenchPublishing libraries A Text Mining Example Describe the resource templateShare libraries Complete a typical text mining modeling Linguistic Editing PreparationShare templates session Review Advanced ResourcesCreate Text Analysis Packages Reading Text Data Use Text Link Analysis interactivelyBackup resources View text from documents within Modeler Create clustersUsing Text Mining Models Read text from Web Feeds Describe approaches to categorizationDevelop a model with quantitative and Linguistic Analysis and Text Mining Develop categorization strategyqualitative data Describe the process of text extraction Use the Template EditorScore new data Describe categorization of terms and Explore text mining models

concepts


Describe Templates and Librariesline Describe Text Analysis Packages line

Explain CRISP-DM methodology as it Creating a Text Mining Concept Model Explain CRISP-DM methodology as itapplies to text mining Compare models based on using applies to text miningDescribe the steps in a text mining project different Resource Templates Describe the steps in a text mining projectA Text Mining Example Score model data A Text Mining ExampleComplete a typical text mining modeling Analyze model results Complete a typical text mining modelingsession Extracted Results in the Interactive sessionReading Text Data Workbench Reading Text DataView text from documents within Modeler Review extracted concepts View text from documents within ModelerRead text from Web Feeds Review extracted types Read text from Web FeedsLinguistic Analysis and Text Mining Update the modeling node Linguistic Analysis and Text MiningDescribe the process of text extraction Linguistic Resources Describe the process of text extractionDescribe categorization of terms and Review libraries Describe categorization of terms andconcepts Review Dictionaries conceptsDescribe Templates and Libraries Manage libraries Describe Templates and LibrariesDescribe Text Analysis Packages Editing Dictionaries Describe Text Analysis PackagesCreating a Text Mining Concept Model Develop editing strategy Creating a Text Mining Concept ModelCompare models based on using different Add Type definitions Compare models based on using differentResource Templates Add Synonym definitions Resource TemplatesScore model data Add Exclusion definitions Score model dataAnalyze model results Text re-extraction to review modifications Analyze model resultsExtracted Results in the Interactive Editing Advanced Resources Extracted Results in the InteractiveWorkbench Add fuzzy grouping exceptions WorkbenchReview extracted concepts Review Text Link Rules Review extracted conceptsReview extracted types Text Link Analysis Review extracted typesUpdate the modeling node Use visualization pane Update the modeling nodeLinguistic Resources Use Text Link Analysis node Linguistic ResourcesReview libraries Create categories from a pattern Review librariesReview Dictionaries Clustering Concepts Review DictionariesManage libraries Use visualization pane Manage librariesEditing Dictionaries Create categories from a cluster Editing DictionariesDevelop editing strategy Categorization Techniques Develop editing strategyAdd Type definitions Describe linguistic based categorization Add Type definitionsAdd Synonym definitions Describe frequency based categorization Add Synonym definitionsAdd Exclusion definitions Describe results of different Add Exclusion definitionsText re-extraction to review modifications categorization methods Text re-extraction to review modificationsEditing Advanced Resources Creating Categories Editing Advanced ResourcesAdd fuzzy grouping exceptions Create categories automatically Add fuzzy grouping exceptionsReview Text Link Rules Create categories manually Review Text Link RulesText Link Analysis Use conditional rules to create categories Text Link AnalysisUse visualization pane Assess category overlap Use visualization paneUse Text Link Analysis node Extend categories Use Text Link Analysis nodeCreate categories from a pattern Import coding frames Create categories from a patternClustering Concepts Managing Linguistic Resources Clustering ConceptsUse visualization pane Save resource templates Use visualization paneCreate categories from a cluster Describe local and public libraries Create categories from a clusterCategorization Techniques Publishing libraries Categorization TechniquesDescribe linguistic based categorization Share libraries Describe linguistic based categorizationDescribe frequency based categorization Share templates Describe frequency based categorizationDescribe results of different categorization Create Text Analysis Packages Describe results of different categorizationmethods Backup resources methodsCreating Categories Using Text Mining Models Creating CategoriesCreate categories automatically Develop a model with quantitative and Create categories automaticallyCreate categories manually qualitative data Create categories manuallyUse conditional rules to create categories Score new data Use conditional rules to create categoriesAssess category overlap Assess category overlapExtend categories Extend categoriesImport coding frames line Import coding framesManaging Linguistic Resources Describe text mining and its relationship Managing Linguistic ResourcesSave resource templates to data mining Save resource templatesDescribe local and public libraries Explain the text mining nodes available in Describe local and public librariesPublishing libraries Modeler Publishing librariesShare libraries Read text from documents Share librariesShare templates Describe linguistic analysis Share templatesCreate Text Analysis Packages Develop a text mining concept model Create Text Analysis Packages


Backup resources Use the Interactive Workbench Backup resourcesUsing Text Mining Models Describe the resource template Using Text Mining ModelsDevelop a model with quantitative and Linguistic Editing Preparation Develop a model with quantitative andqualitative data Review Advanced Resources qualitative dataScore new data Use Text Link Analysis interactively Score new data

Create clustersDescribe approaches to categorization

line Develop categorization strategy lineDescribe text mining and its relationship to Use the Template Editor Explain CRISP-DM methodology as itdata mining Explore text mining models applies to text miningExplain the text mining nodes available in Describe the steps in a text mining projectModeler A Text Mining ExampleRead text from documents line Complete a typical text mining modelingDescribe linguistic analysis Explain CRISP-DM methodology as it sessionDevelop a text mining concept model applies to text mining Reading Text DataUse the Interactive Workbench Describe the steps in a text mining View text from documents within ModelerDescribe the resource template project Read text from Web FeedsLinguistic Editing Preparation A Text Mining Example Linguistic Analysis and Text MiningReview Advanced Resources Complete a typical text mining modeling Describe the process of text extractionUse Text Link Analysis interactively session Describe categorization of terms andCreate clusters Reading Text Data conceptsDescribe approaches to categorization View text from documents within Modeler Describe Templates and LibrariesDevelop categorization strategy Read text from Web Feeds Describe Text Analysis PackagesUse the Template Editor Linguistic Analysis and Text Mining Creating a Text Mining Concept ModelExplore text mining models Describe the process of text extraction Compare models based on using different

Describe categorization of terms and Resource Templatesconcepts Score model data

line Describe Templates and Libraries Analyze model resultsExplain CRISP-DM methodology as it Describe Text Analysis Packages Extracted Results in the Interactiveapplies to text mining Creating a Text Mining Concept Model WorkbenchDescribe the steps in a text mining project Compare models based on using Review extracted conceptsA Text Mining Example different Resource Templates Review extracted typesComplete a typical text mining modeling Score model data Update the modeling nodesession Analyze model results Linguistic ResourcesReading Text Data Extracted Results in the Interactive Review librariesView text from documents within Modeler Workbench Review DictionariesRead text from Web Feeds Review extracted concepts Manage librariesLinguistic Analysis and Text Mining Review extracted types Editing DictionariesDescribe the process of text extraction Update the modeling node Develop editing strategyDescribe categorization of terms and Linguistic Resources Add Type definitionsconcepts Review libraries Add Synonym definitionsDescribe Templates and Libraries Review Dictionaries Add Exclusion definitionsDescribe Text Analysis Packages Manage libraries Text re-extraction to review modificationsCreating a Text Mining Concept Model Editing Dictionaries Editing Advanced ResourcesCompare models based on using different Develop editing strategy Add fuzzy grouping exceptionsResource Templates Add Type definitions Review Text Link RulesScore model data Add Synonym definitions Text Link AnalysisAnalyze model results Add Exclusion definitions Use visualization paneExtracted Results in the Interactive Text re-extraction to review modifications Use Text Link Analysis nodeWorkbench Editing Advanced Resources Create categories from a patternReview extracted concepts Add fuzzy grouping exceptions Clustering ConceptsReview extracted types Review Text Link Rules Use visualization paneUpdate the modeling node Text Link Analysis Create categories from a clusterLinguistic Resources Use visualization pane Categorization TechniquesReview libraries Use Text Link Analysis node Describe linguistic based categorizationReview Dictionaries Create categories from a pattern Describe frequency based categorizationManage libraries Clustering Concepts Describe results of different categorizationEditing Dictionaries Use visualization pane methodsDevelop editing strategy Create categories from a cluster Creating CategoriesAdd Type definitions Categorization Techniques Create categories automaticallyAdd Synonym definitions Describe linguistic based categorization Create categories manuallyAdd Exclusion definitions Describe frequency based categorization Use conditional rules to create categoriesText re-extraction to review modifications Describe results of different Assess category overlapEditing Advanced Resources categorization methods Extend categoriesAdd fuzzy grouping exceptions Creating Categories Import coding framesReview Text Link Rules Create categories automatically Managing Linguistic Resources


Text Link Analysis Create categories manually Save resource templatesUse visualization pane Use conditional rules to create categories Describe local and public librariesUse Text Link Analysis node Assess category overlap Publishing librariesCreate categories from a pattern Extend categories Share librariesClustering Concepts Import coding frames Share templatesUse visualization pane Managing Linguistic Resources Create Text Analysis PackagesCreate categories from a cluster Save resource templates Backup resourcesCategorization Techniques Describe local and public libraries Using Text Mining ModelsDescribe linguistic based categorization Publishing libraries Develop a model with quantitative andDescribe frequency based categorization Share libraries qualitative dataDescribe results of different categorization Share templates Score new datamethods Create Text Analysis PackagesCreating Categories Backup resourcesCreate categories automatically Using Text Mining Models lineCreate categories manually Develop a model with quantitative and Explain CRISP-DM methodology as itUse conditional rules to create categories qualitative data applies to text miningAssess category overlap Score new data Describe the steps in a text mining projectExtend categories A Text Mining ExampleImport coding frames Complete a typical text mining modelingManaging Linguistic Resources line sessionSave resource templates Explain CRISP-DM methodology as it Reading Text DataDescribe local and public libraries applies to text mining View text from documents within ModelerPublishing libraries Describe the steps in a text mining Read text from Web FeedsShare libraries project Linguistic Analysis and Text MiningShare templates A Text Mining Example Describe the process of text extractionCreate Text Analysis Packages Complete a typical text mining modeling Describe categorization of terms andBackup resources session conceptsUsing Text Mining Models Reading Text Data Describe Templates and LibrariesDevelop a model with quantitative and View text from documents within Modeler Describe Text Analysis Packagesqualitative data Read text from Web Feeds Creating a Text Mining Concept ModelScore new data Linguistic Analysis and Text Mining Compare models based on using different

Describe the process of text extraction Resource TemplatesDescribe categorization of terms and Score model data

line concepts Analyze model resultsExplain CRISP-DM methodology as it Describe Templates and Libraries Extracted Results in the Interactiveapplies to text mining Describe Text Analysis Packages WorkbenchDescribe the steps in a text mining project Creating a Text Mining Concept Model Review extracted conceptsA Text Mining Example Compare models based on using Review extracted typesComplete a typical text mining modeling different Resource Templates Update the modeling nodesession Score model data Linguistic ResourcesReading Text Data Analyze model results Review librariesView text from documents within Modeler Extracted Results in the Interactive Review DictionariesRead text from Web Feeds Workbench Manage librariesLinguistic Analysis and Text Mining Review extracted concepts Editing DictionariesDescribe the process of text extraction Review extracted types Develop editing strategyDescribe categorization of terms and Update the modeling node Add Type definitionsconcepts Linguistic Resources Add Synonym definitionsDescribe Templates and Libraries Review libraries Add Exclusion definitionsDescribe Text Analysis Packages Review Dictionaries Text re-extraction to review modificationsCreating a Text Mining Concept Model Manage libraries Editing Advanced ResourcesCompare models based on using different Editing Dictionaries Add fuzzy grouping exceptionsResource Templates Develop editing strategy Review Text Link RulesScore model data Add Type definitions Text Link AnalysisAnalyze model results Add Synonym definitions Use visualization paneExtracted Results in the Interactive Add Exclusion definitions Use Text Link Analysis nodeWorkbench Text re-extraction to review modifications Create categories from a patternReview extracted concepts Editing Advanced Resources Clustering ConceptsReview extracted types Add fuzzy grouping exceptions Use visualization paneUpdate the modeling node Review Text Link Rules Create categories from a clusterLinguistic Resources Text Link Analysis Categorization TechniquesReview libraries Use visualization pane Describe linguistic based categorizationReview Dictionaries Use Text Link Analysis node Describe frequency based categorizationManage libraries Create categories from a pattern Describe results of different categorizationEditing Dictionaries Clustering Concepts methodsDevelop editing strategy Use visualization pane Creating CategoriesAdd Type definitions Create categories from a cluster Create categories automatically


Add Synonym definitions Categorization Techniques Create categories manuallyAdd Exclusion definitions Describe linguistic based categorization Use conditional rules to create categoriesText re-extraction to review modifications Describe frequency based categorization Assess category overlapEditing Advanced Resources Describe results of different Extend categoriesAdd fuzzy grouping exceptions categorization methods Import coding framesReview Text Link Rules Creating Categories Managing Linguistic ResourcesText Link Analysis Create categories automatically Save resource templatesUse visualization pane Create categories manually Describe local and public librariesUse Text Link Analysis node Use conditional rules to create categories Publishing librariesCreate categories from a pattern Assess category overlap Share librariesClustering Concepts Extend categories Share templatesUse visualization pane Import coding frames Create Text Analysis PackagesCreate categories from a cluster Managing Linguistic Resources Backup resourcesCategorization Techniques Save resource templates Using Text Mining ModelsDescribe linguistic based categorization Describe local and public libraries Develop a model with quantitative andDescribe frequency based categorization Publishing libraries qualitative dataDescribe results of different categorization Share libraries Score new datamethods Share templatesCreating Categories Create Text Analysis PackagesCreate categories automatically Backup resources lineCreate categories manually Using Text Mining Models Explain CRISP-DM methodology as itUse conditional rules to create categories Develop a model with quantitative and applies to text miningAssess category overlap qualitative data Describe the steps in a text mining projectExtend categories Score new data A Text Mining ExampleImport coding frames Complete a typical text mining modelingManaging Linguistic Resources sessionSave resource templates line Reading Text DataDescribe local and public libraries Explain CRISP-DM methodology as it View text from documents within ModelerPublishing libraries applies to text mining Read text from Web FeedsShare libraries Describe the steps in a text mining Linguistic Analysis and Text MiningShare templates project Describe the process of text extractionCreate Text Analysis Packages A Text Mining Example Describe categorization of terms andBackup resources Complete a typical text mining modeling conceptsUsing Text Mining Models session Describe Templates and LibrariesDevelop a model with quantitative and Reading Text Data Describe Text Analysis Packagesqualitative data View text from documents within Modeler Creating a Text Mining Concept ModelScore new data Read text from Web Feeds Compare models based on using different

Linguistic Analysis and Text Mining Resource TemplatesDescribe the process of text extraction Score model data

line Describe categorization of terms and Analyze model resultsExplain CRISP-DM methodology as it concepts Extracted Results in the Interactiveapplies to text mining Describe Templates and Libraries WorkbenchDescribe the steps in a text mining project Describe Text Analysis Packages Review extracted conceptsA Text Mining Example Creating a Text Mining Concept Model Review extracted typesComplete a typical text mining modeling Compare models based on using Update the modeling nodesession different Resource Templates Linguistic ResourcesReading Text Data Score model data Review librariesView text from documents within Modeler Analyze model results Review DictionariesRead text from Web Feeds Extracted Results in the Interactive Manage librariesLinguistic Analysis and Text Mining Workbench Editing DictionariesDescribe the process of text extraction Review extracted concepts Develop editing strategyDescribe categorization of terms and Review extracted types Add Type definitionsconcepts Update the modeling node Add Synonym definitionsDescribe Templates and Libraries Linguistic Resources Add Exclusion definitionsDescribe Text Analysis Packages Review libraries Text re-extraction to review modificationsCreating a Text Mining Concept Model Review Dictionaries Editing Advanced ResourcesCompare models based on using different Manage libraries Add fuzzy grouping exceptionsResource Templates Editing Dictionaries Review Text Link RulesScore model data Develop editing strategy Text Link AnalysisAnalyze model results Add Type definitions Use visualization paneExtracted Results in the Interactive Add Synonym definitions Use Text Link Analysis nodeWorkbench Add Exclusion definitions Create categories from a patternReview extracted concepts Text re-extraction to review modifications Clustering ConceptsReview extracted types Editing Advanced Resources Use visualization paneUpdate the modeling node Add fuzzy grouping exceptions Create categories from a clusterLinguistic Resources Review Text Link Rules Categorization Techniques


Review libraries Text Link Analysis Describe linguistic based categorizationReview Dictionaries Use visualization pane Describe frequency based categorizationManage libraries Use Text Link Analysis node Describe results of different categorizationEditing Dictionaries Create categories from a pattern methodsDevelop editing strategy Clustering Concepts Creating CategoriesAdd Type definitions Use visualization pane Create categories automaticallyAdd Synonym definitions Create categories from a cluster Create categories manuallyAdd Exclusion definitions Categorization Techniques Use conditional rules to create categoriesText re-extraction to review modifications Describe linguistic based categorization Assess category overlapEditing Advanced Resources Describe frequency based categorization Extend categoriesAdd fuzzy grouping exceptions Describe results of different Import coding framesReview Text Link Rules categorization methods Managing Linguistic ResourcesText Link Analysis Creating Categories Save resource templatesUse visualization pane Create categories automatically Describe local and public librariesUse Text Link Analysis node Create categories manually Publishing librariesCreate categories from a pattern Use conditional rules to create categories Share librariesClustering Concepts Assess category overlap Share templatesUse visualization pane Extend categories Create Text Analysis PackagesCreate categories from a cluster Import coding frames Backup resourcesCategorization Techniques Managing Linguistic Resources Using Text Mining ModelsDescribe linguistic based categorization Save resource templates Develop a model with quantitative andDescribe frequency based categorization Describe local and public libraries qualitative dataDescribe results of different categorization Publishing libraries Score new datamethods Share librariesCreating Categories Share templatesCreate categories automatically Create Text Analysis Packages lineCreate categories manually Backup resources Explain CRISP-DM methodology as itUse conditional rules to create categories Using Text Mining Models applies to text miningAssess category overlap Develop a model with quantitative and Describe the steps in a text mining projectExtend categories qualitative data A Text Mining ExampleImport coding frames Score new data Complete a typical text mining modelingManaging Linguistic Resources sessionSave resource templates Reading Text DataDescribe local and public libraries line View text from documents within ModelerPublishing libraries Explain CRISP-DM methodology as it Read text from Web FeedsShare libraries applies to text mining Linguistic Analysis and Text MiningShare templates Describe the steps in a text mining Describe the process of text extractionCreate Text Analysis Packages project Describe categorization of terms andBackup resources A Text Mining Example conceptsUsing Text Mining Models Complete a typical text mining modeling Describe Templates and LibrariesDevelop a model with quantitative and session Describe Text Analysis Packagesqualitative data Reading Text Data Creating a Text Mining Concept ModelScore new data View text from documents within Modeler Compare models based on using different

Read text from Web Feeds Resource TemplatesLinguistic Analysis and Text Mining Score model data

line Describe the process of text extraction Analyze model resultsDescribe text mining and its relationship to Describe categorization of terms and Extracted Results in the Interactivedata mining concepts WorkbenchExplain the text mining nodes available in Describe Templates and Libraries Review extracted conceptsModeler Describe Text Analysis Packages Review extracted typesRead text from documents Creating a Text Mining Concept Model Update the modeling nodeDescribe linguistic analysis Compare models based on using Linguistic ResourcesDevelop a text mining concept model different Resource Templates Review librariesUse the Interactive Workbench Score model data Review DictionariesDescribe the resource template Analyze model results Manage librariesLinguistic Editing Preparation Extracted Results in the Interactive Editing DictionariesReview Advanced Resources Workbench Develop editing strategyUse Text Link Analysis interactively Review extracted concepts Add Type definitionsCreate clusters Review extracted types Add Synonym definitionsDescribe approaches to categorization Update the modeling node Add Exclusion definitionsDevelop categorization strategy Linguistic Resources Text re-extraction to review modificationsUse the Template Editor Review libraries Editing Advanced ResourcesExplore text mining models Review Dictionaries Add fuzzy grouping exceptions

Manage libraries Review Text Link RulesEditing Dictionaries Text Link Analysis

line Develop editing strategy Use visualization pane


Explain CRISP-DM methodology as it Add Type definitions Use Text Link Analysis nodeapplies to text mining Add Synonym definitions Create categories from a patternDescribe the steps in a text mining project Add Exclusion definitions Clustering ConceptsA Text Mining Example Text re-extraction to review modifications Use visualization paneComplete a typical text mining modeling Editing Advanced Resources Create categories from a clustersession Add fuzzy grouping exceptions Categorization TechniquesReading Text Data Review Text Link Rules Describe linguistic based categorizationView text from documents within Modeler Text Link Analysis Describe frequency based categorizationRead text from Web Feeds Use visualization pane Describe results of different categorizationLinguistic Analysis and Text Mining Use Text Link Analysis node methodsDescribe the process of text extraction Create categories from a pattern Creating CategoriesDescribe categorization of terms and Clustering Concepts Create categories automaticallyconcepts Use visualization pane Create categories manuallyDescribe Templates and Libraries Create categories from a cluster Use conditional rules to create categoriesDescribe Text Analysis Packages Categorization Techniques Assess category overlapCreating a Text Mining Concept Model Describe linguistic based categorization Extend categoriesCompare models based on using different Describe frequency based categorization Import coding framesResource Templates Describe results of different Managing Linguistic ResourcesScore model data categorization methods Save resource templatesAnalyze model results Creating Categories Describe local and public librariesExtracted Results in the Interactive Create categories automatically Publishing librariesWorkbench Create categories manually Share librariesReview extracted concepts Use conditional rules to create categories Share templatesReview extracted types Assess category overlap Create Text Analysis PackagesUpdate the modeling node Extend categories Backup resourcesLinguistic Resources Import coding frames Using Text Mining ModelsReview libraries Managing Linguistic Resources Develop a model with quantitative andReview Dictionaries Save resource templates qualitative dataManage libraries Describe local and public libraries Score new dataEditing Dictionaries Publishing librariesDevelop editing strategy Share librariesAdd Type definitions Share templates lineAdd Synonym definitions Create Text Analysis Packages Explain CRISP-DM methodology as itAdd Exclusion definitions Backup resources applies to text miningText re-extraction to review modifications Using Text Mining Models Describe the steps in a text mining projectEditing Advanced Resources Develop a model with quantitative and A Text Mining ExampleAdd fuzzy grouping exceptions qualitative data Complete a typical text mining modelingReview Text Link Rules Score new data sessionText Link Analysis Reading Text DataUse visualization pane View text from documents within ModelerUse Text Link Analysis node line Read text from Web FeedsCreate categories from a pattern Explain CRISP-DM methodology as it Linguistic Analysis and Text MiningClustering Concepts applies to text mining Describe the process of text extractionUse visualization pane Describe the steps in a text mining Describe categorization of terms andCreate categories from a cluster project conceptsCategorization Techniques A Text Mining Example Describe Templates and LibrariesDescribe linguistic based categorization Complete a typical text mining modeling Describe Text Analysis PackagesDescribe frequency based categorization session Creating a Text Mining Concept ModelDescribe results of different categorization Reading Text Data Compare models based on using differentmethods View text from documents within Modeler Resource TemplatesCreating Categories Read text from Web Feeds Score model dataCreate categories automatically Linguistic Analysis and Text Mining Analyze model resultsCreate categories manually Describe the process of text extraction Extracted Results in the InteractiveUse conditional rules to create categories Describe categorization of terms and WorkbenchAssess category overlap concepts Review extracted conceptsExtend categories Describe Templates and Libraries Review extracted typesImport coding frames Describe Text Analysis Packages Update the modeling nodeManaging Linguistic Resources Creating a Text Mining Concept Model Linguistic ResourcesSave resource templates Compare models based on using Review librariesDescribe local and public libraries different Resource Templates Review DictionariesPublishing libraries Score model data Manage librariesShare libraries Analyze model results Editing DictionariesShare templates Extracted Results in the Interactive Develop editing strategyCreate Text Analysis Packages Workbench Add Type definitionsBackup resources Review extracted concepts Add Synonym definitionsUsing Text Mining Models Review extracted types Add Exclusion definitions


Develop a model with quantitative and Update the modeling node Text re-extraction to review modificationsqualitative data Linguistic Resources Editing Advanced ResourcesScore new data Review libraries Add fuzzy grouping exceptions

Review Dictionaries Review Text Link RulesManage libraries Text Link Analysis

line Editing Dictionaries Use visualization paneExplain CRISP-DM methodology as it Develop editing strategy Use Text Link Analysis nodeapplies to text mining Add Type definitions Create categories from a patternDescribe the steps in a text mining project Add Synonym definitions Clustering ConceptsA Text Mining Example Add Exclusion definitions Use visualization paneComplete a typical text mining modeling Text re-extraction to review modifications Create categories from a clustersession Editing Advanced Resources Categorization TechniquesReading Text Data Add fuzzy grouping exceptions Describe linguistic based categorizationView text from documents within Modeler Review Text Link Rules Describe frequency based categorizationRead text from Web Feeds Text Link Analysis Describe results of different categorizationLinguistic Analysis and Text Mining Use visualization pane methodsDescribe the process of text extraction Use Text Link Analysis node Creating CategoriesDescribe categorization of terms and Create categories from a pattern Create categories automaticallyconcepts Clustering Concepts Create categories manuallyDescribe Templates and Libraries Use visualization pane Use conditional rules to create categoriesDescribe Text Analysis Packages Create categories from a cluster Assess category overlapCreating a Text Mining Concept Model Categorization Techniques Extend categoriesCompare models based on using different Describe linguistic based categorization Import coding framesResource Templates Describe frequency based categorization Managing Linguistic ResourcesScore model data Describe results of different Save resource templatesAnalyze model results categorization methods Describe local and public librariesExtracted Results in the Interactive Creating Categories Publishing librariesWorkbench Create categories automatically Share librariesReview extracted concepts Create categories manually Share templatesReview extracted types Use conditional rules to create categories Create Text Analysis PackagesUpdate the modeling node Assess category overlap Backup resourcesLinguistic Resources Extend categories Using Text Mining ModelsReview libraries Import coding frames Develop a model with quantitative andReview Dictionaries Managing Linguistic Resources qualitative dataManage libraries Save resource templates Score new dataEditing Dictionaries Describe local and public librariesDevelop editing strategy Publishing librariesAdd Type definitions Share libraries lineAdd Synonym definitions Share templates Explain CRISP-DM methodology as itAdd Exclusion definitions Create Text Analysis Packages applies to text miningText re-extraction to review modifications Backup resources Describe the steps in a text mining projectEditing Advanced Resources Using Text Mining Models A Text Mining ExampleAdd fuzzy grouping exceptions Develop a model with quantitative and Complete a typical text mining modelingReview Text Link Rules qualitative data sessionText Link Analysis Score new data Reading Text DataUse visualization pane View text from documents within ModelerUse Text Link Analysis node Read text from Web FeedsCreate categories from a pattern line Linguistic Analysis and Text MiningClustering Concepts Explain CRISP-DM methodology as it Describe the process of text extractionUse visualization pane applies to text mining Describe categorization of terms andCreate categories from a cluster Describe the steps in a text mining conceptsCategorization Techniques project Describe Templates and LibrariesDescribe linguistic based categorization A Text Mining Example Describe Text Analysis PackagesDescribe frequency based categorization Complete a typical text mining modeling Creating a Text Mining Concept ModelDescribe results of different categorization session Compare models based on using differentmethods Reading Text Data Resource TemplatesCreating Categories View text from documents within Modeler Score model dataCreate categories automatically Read text from Web Feeds Analyze model resultsCreate categories manually Linguistic Analysis and Text Mining Extracted Results in the InteractiveUse conditional rules to create categories Describe the process of text extraction WorkbenchAssess category overlap Describe categorization of terms and Review extracted conceptsExtend categories concepts Review extracted typesImport coding frames Describe Templates and Libraries Update the modeling nodeManaging Linguistic Resources Describe Text Analysis Packages Linguistic ResourcesSave resource templates Creating a Text Mining Concept Model Review librariesDescribe local and public libraries Compare models based on using Review Dictionaries


Publishing libraries different Resource Templates Manage librariesShare libraries Score model data Editing DictionariesShare templates Analyze model results Develop editing strategyCreate Text Analysis Packages Extracted Results in the Interactive Add Type definitionsBackup resources Workbench Add Synonym definitionsUsing Text Mining Models Review extracted concepts Add Exclusion definitionsDevelop a model with quantitative and Review extracted types Text re-extraction to review modificationsqualitative data Update the modeling node Editing Advanced ResourcesScore new data Linguistic Resources Add fuzzy grouping exceptions

Review libraries Review Text Link RulesReview Dictionaries Text Link Analysis

line Manage libraries Use visualization paneExplain CRISP-DM methodology as it Editing Dictionaries Use Text Link Analysis nodeapplies to text mining Develop editing strategy Create categories from a patternDescribe the steps in a text mining project Add Type definitions Clustering ConceptsA Text Mining Example Add Synonym definitions Use visualization paneComplete a typical text mining modeling Add Exclusion definitions Create categories from a clustersession Text re-extraction to review modifications Categorization TechniquesReading Text Data Editing Advanced Resources Describe linguistic based categorizationView text from documents within Modeler Add fuzzy grouping exceptions Describe frequency based categorizationRead text from Web Feeds Review Text Link Rules Describe results of different categorizationLinguistic Analysis and Text Mining Text Link Analysis methodsDescribe the process of text extraction Use visualization pane Creating CategoriesDescribe categorization of terms and Use Text Link Analysis node Create categories automaticallyconcepts Create categories from a pattern Create categories manuallyDescribe Templates and Libraries Clustering Concepts Use conditional rules to create categoriesDescribe Text Analysis Packages Use visualization pane Assess category overlapCreating a Text Mining Concept Model Create categories from a cluster Extend categoriesCompare models based on using different Categorization Techniques Import coding framesResource Templates Describe linguistic based categorization Managing Linguistic ResourcesScore model data Describe frequency based categorization Save resource templatesAnalyze model results Describe results of different Describe local and public librariesExtracted Results in the Interactive categorization methods Publishing librariesWorkbench Creating Categories Share librariesReview extracted concepts Create categories automatically Share templatesReview extracted types Create categories manually Create Text Analysis PackagesUpdate the modeling node Use conditional rules to create categories Backup resourcesLinguistic Resources Assess category overlap Using Text Mining ModelsReview libraries Extend categories Develop a model with quantitative andReview Dictionaries Import coding frames qualitative dataManage libraries Managing Linguistic Resources Score new dataEditing Dictionaries Save resource templatesDevelop editing strategy Describe local and public librariesAdd Type definitions Publishing libraries lineAdd Synonym definitions Share libraries Describe text mining and its relationship toAdd Exclusion definitions Share templates data miningText re-extraction to review modifications Create Text Analysis Packages Explain the text mining nodes available inEditing Advanced Resources Backup resources ModelerAdd fuzzy grouping exceptions Using Text Mining Models Read text from documentsReview Text Link Rules Develop a model with quantitative and Describe linguistic analysisText Link Analysis qualitative data Develop a text mining concept modelUse visualization pane Score new data Use the Interactive WorkbenchUse Text Link Analysis node Describe the resource templateCreate categories from a pattern Linguistic Editing PreparationClustering Concepts line Review Advanced ResourcesUse visualization pane Describe text mining and its relationship Use Text Link Analysis interactivelyCreate categories from a cluster to data mining Create clustersCategorization Techniques Explain the text mining nodes available in Describe approaches to categorizationDescribe linguistic based categorization Modeler Develop categorization strategyDescribe frequency based categorization Read text from documents Use the Template EditorDescribe results of different categorization Describe linguistic analysis Explore text mining modelsmethods Develop a text mining concept modelCreating Categories Use the Interactive WorkbenchCreate categories automatically Describe the resource template lineCreate categories manually Linguistic Editing Preparation Explain CRISP-DM methodology as itUse conditional rules to create categories Review Advanced Resources applies to text mining


Assess category overlap Use Text Link Analysis interactively Describe the steps in a text mining projectExtend categories Create clusters A Text Mining ExampleImport coding frames Describe approaches to categorization Complete a typical text mining modelingManaging Linguistic Resources Develop categorization strategy sessionSave resource templates Use the Template Editor Reading Text DataDescribe local and public libraries Explore text mining models View text from documents within ModelerPublishing libraries Read text from Web FeedsShare libraries Linguistic Analysis and Text MiningShare templates line Describe the process of text extractionCreate Text Analysis Packages Explain CRISP-DM methodology as it Describe categorization of terms andBackup resources applies to text mining conceptsUsing Text Mining Models Describe the steps in a text mining Describe Templates and LibrariesDevelop a model with quantitative and project Describe Text Analysis Packagesqualitative data A Text Mining Example Creating a Text Mining Concept ModelScore new data Complete a typical text mining modeling Compare models based on using different

session Resource TemplatesReading Text Data Score model data

line View text from documents within Modeler Analyze model resultsExplain CRISP-DM methodology as it Read text from Web Feeds Extracted Results in the Interactiveapplies to text mining Linguistic Analysis and Text Mining WorkbenchDescribe the steps in a text mining project Describe the process of text extraction Review extracted conceptsA Text Mining Example Describe categorization of terms and Review extracted typesComplete a typical text mining modeling concepts Update the modeling nodesession Describe Templates and Libraries Linguistic ResourcesReading Text Data Describe Text Analysis Packages Review librariesView text from documents within Modeler Creating a Text Mining Concept Model Review DictionariesRead text from Web Feeds Compare models based on using Manage librariesLinguistic Analysis and Text Mining different Resource Templates Editing DictionariesDescribe the process of text extraction Score model data Develop editing strategyDescribe categorization of terms and Analyze model results Add Type definitionsconcepts Extracted Results in the Interactive Add Synonym definitionsDescribe Templates and Libraries Workbench Add Exclusion definitionsDescribe Text Analysis Packages Review extracted concepts Text re-extraction to review modificationsCreating a Text Mining Concept Model Review extracted types Editing Advanced ResourcesCompare models based on using different Update the modeling node Add fuzzy grouping exceptionsResource Templates Linguistic Resources Review Text Link RulesScore model data Review libraries Text Link AnalysisAnalyze model results Review Dictionaries Use visualization paneExtracted Results in the Interactive Manage libraries Use Text Link Analysis nodeWorkbench Editing Dictionaries Create categories from a patternReview extracted concepts Develop editing strategy Clustering ConceptsReview extracted types Add Type definitions Use visualization paneUpdate the modeling node Add Synonym definitions Create categories from a clusterLinguistic Resources Add Exclusion definitions Categorization TechniquesReview libraries Text re-extraction to review modifications Describe linguistic based categorizationReview Dictionaries Editing Advanced Resources Describe frequency based categorizationManage libraries Add fuzzy grouping exceptions Describe results of different categorizationEditing Dictionaries Review Text Link Rules methodsDevelop editing strategy Text Link Analysis Creating CategoriesAdd Type definitions Use visualization pane Create categories automaticallyAdd Synonym definitions Use Text Link Analysis node Create categories manuallyAdd Exclusion definitions Create categories from a pattern Use conditional rules to create categoriesText re-extraction to review modifications Clustering Concepts Assess category overlapEditing Advanced Resources Use visualization pane Extend categoriesAdd fuzzy grouping exceptions Create categories from a cluster Import coding framesReview Text Link Rules Categorization Techniques Managing Linguistic ResourcesText Link Analysis Describe linguistic based categorization Save resource templatesUse visualization pane Describe frequency based categorization Describe local and public librariesUse Text Link Analysis node Describe results of different Publishing librariesCreate categories from a pattern categorization methods Share librariesClustering Concepts Creating Categories Share templatesUse visualization pane Create categories automatically Create Text Analysis PackagesCreate categories from a cluster Create categories manually Backup resourcesCategorization Techniques Use conditional rules to create categories Using Text Mining ModelsDescribe linguistic based categorization Assess category overlap Develop a model with quantitative andDescribe frequency based categorization Extend categories qualitative data


Describe results of different categorization Import coding frames Score new datamethods Managing Linguistic ResourcesCreating Categories Save resource templatesCreate categories automatically Describe local and public libraries lineCreate categories manually Publishing libraries Explain CRISP-DM methodology as itUse conditional rules to create categories Share libraries applies to text miningAssess category overlap Share templates Describe the steps in a text mining projectExtend categories Create Text Analysis Packages A Text Mining ExampleImport coding frames Backup resources Complete a typical text mining modelingManaging Linguistic Resources Using Text Mining Models sessionSave resource templates Develop a model with quantitative and Reading Text DataDescribe local and public libraries qualitative data View text from documents within ModelerPublishing libraries Score new data Read text from Web FeedsShare libraries Linguistic Analysis and Text MiningShare templates Describe the process of text extractionCreate Text Analysis Packages line Describe categorization of terms andBackup resources Explain CRISP-DM methodology as it conceptsUsing Text Mining Models applies to text mining Describe Templates and LibrariesDevelop a model with quantitative and Describe the steps in a text mining Describe Text Analysis Packagesqualitative data project Creating a Text Mining Concept ModelScore new data A Text Mining Example Compare models based on using different

Complete a typical text mining modeling Resource Templatessession Score model data

line Reading Text Data Analyze model resultsExplain CRISP-DM methodology as it View text from documents within Modeler Extracted Results in the Interactiveapplies to text mining Read text from Web Feeds WorkbenchDescribe the steps in a text mining project Linguistic Analysis and Text Mining Review extracted conceptsA Text Mining Example Describe the process of text extraction Review extracted typesComplete a typical text mining modeling Describe categorization of terms and Update the modeling nodesession concepts Linguistic ResourcesReading Text Data Describe Templates and Libraries Review librariesView text from documents within Modeler Describe Text Analysis Packages Review DictionariesRead text from Web Feeds Creating a Text Mining Concept Model Manage librariesLinguistic Analysis and Text Mining Compare models based on using Editing DictionariesDescribe the process of text extraction different Resource Templates Develop editing strategyDescribe categorization of terms and Score model data Add Type definitionsconcepts Analyze model results Add Synonym definitionsDescribe Templates and Libraries Extracted Results in the Interactive Add Exclusion definitionsDescribe Text Analysis Packages Workbench Text re-extraction to review modificationsCreating a Text Mining Concept Model Review extracted concepts Editing Advanced ResourcesCompare models based on using different Review extracted types Add fuzzy grouping exceptionsResource Templates Update the modeling node Review Text Link RulesScore model data Linguistic Resources Text Link AnalysisAnalyze model results Review libraries Use visualization paneExtracted Results in the Interactive Review Dictionaries Use Text Link Analysis nodeWorkbench Manage libraries Create categories from a patternReview extracted concepts Editing Dictionaries Clustering ConceptsReview extracted types Develop editing strategy Use visualization paneUpdate the modeling node Add Type definitions Create categories from a clusterLinguistic Resources Add Synonym definitions Categorization TechniquesReview libraries Add Exclusion definitions Describe linguistic based categorizationReview Dictionaries Text re-extraction to review modifications Describe frequency based categorizationManage libraries Editing Advanced Resources Describe results of different categorizationEditing Dictionaries Add fuzzy grouping exceptions methodsDevelop editing strategy Review Text Link Rules Creating CategoriesAdd Type definitions Text Link Analysis Create categories automaticallyAdd Synonym definitions Use visualization pane Create categories manuallyAdd Exclusion definitions Use Text Link Analysis node Use conditional rules to create categoriesText re-extraction to review modifications Create categories from a pattern Assess category overlapEditing Advanced Resources Clustering Concepts Extend categoriesAdd fuzzy grouping exceptions Use visualization pane Import coding framesReview Text Link Rules Create categories from a cluster Managing Linguistic ResourcesText Link Analysis Categorization Techniques Save resource templatesUse visualization pane Describe linguistic based categorization Describe local and public librariesUse Text Link Analysis node Describe frequency based categorization Publishing librariesCreate categories from a pattern Describe results of different Share libraries


Clustering Concepts categorization methods Share templatesUse visualization pane Creating Categories Create Text Analysis PackagesCreate categories from a cluster Create categories automatically Backup resourcesCategorization Techniques Create categories manually Using Text Mining ModelsDescribe linguistic based categorization Use conditional rules to create categories Develop a model with quantitative andDescribe frequency based categorization Assess category overlap qualitative dataDescribe results of different categorization Extend categories Score new datamethods Import coding framesCreating Categories Managing Linguistic ResourcesCreate categories automatically Save resource templates lineCreate categories manually Describe local and public libraries Explain CRISP-DM methodology as itUse conditional rules to create categories Publishing libraries applies to text miningAssess category overlap Share libraries Describe the steps in a text mining projectExtend categories Share templates A Text Mining ExampleImport coding frames Create Text Analysis Packages Complete a typical text mining modelingManaging Linguistic Resources Backup resources sessionSave resource templates Using Text Mining Models Reading Text DataDescribe local and public libraries Develop a model with quantitative and View text from documents within ModelerPublishing libraries qualitative data Read text from Web FeedsShare libraries Score new data Linguistic Analysis and Text MiningShare templates Describe the process of text extractionCreate Text Analysis Packages Describe categorization of terms andBackup resources line conceptsUsing Text Mining Models Explain CRISP-DM methodology as it Describe Templates and LibrariesDevelop a model with quantitative and applies to text mining Describe Text Analysis Packagesqualitative data Describe the steps in a text mining Creating a Text Mining Concept ModelScore new data project Compare models based on using different

A Text Mining Example Resource TemplatesComplete a typical text mining modeling Score model data

line session Analyze model resultsDescribe text mining and its relationship to Reading Text Data Extracted Results in the Interactivedata mining View text from documents within Modeler WorkbenchExplain the text mining nodes available in Read text from Web Feeds Review extracted conceptsModeler Linguistic Analysis and Text Mining Review extracted typesRead text from documents Describe the process of text extraction Update the modeling nodeDescribe linguistic analysis Describe categorization of terms and Linguistic ResourcesDevelop a text mining concept model concepts Review librariesUse the Interactive Workbench Describe Templates and Libraries Review DictionariesDescribe the resource template Describe Text Analysis Packages Manage librariesLinguistic Editing Preparation Creating a Text Mining Concept Model Editing DictionariesReview Advanced Resources Compare models based on using Develop editing strategyUse Text Link Analysis interactively different Resource Templates Add Type definitionsCreate clusters Score model data Add Synonym definitionsDescribe approaches to categorization Analyze model results Add Exclusion definitionsDevelop categorization strategy Extracted Results in the Interactive Text re-extraction to review modificationsUse the Template Editor Workbench Editing Advanced ResourcesExplore text mining models Review extracted concepts Add fuzzy grouping exceptions

Review extracted types Review Text Link RulesUpdate the modeling node Text Link Analysis

line Linguistic Resources Use visualization paneExplain CRISP-DM methodology as it Review libraries Use Text Link Analysis nodeapplies to text mining Review Dictionaries Create categories from a patternDescribe the steps in a text mining project Manage libraries Clustering ConceptsA Text Mining Example Editing Dictionaries Use visualization paneComplete a typical text mining modeling Develop editing strategy Create categories from a clustersession Add Type definitions Categorization TechniquesReading Text Data Add Synonym definitions Describe linguistic based categorizationView text from documents within Modeler Add Exclusion definitions Describe frequency based categorizationRead text from Web Feeds Text re-extraction to review modifications Describe results of different categorizationLinguistic Analysis and Text Mining Editing Advanced Resources methodsDescribe the process of text extraction Add fuzzy grouping exceptions Creating CategoriesDescribe categorization of terms and Review Text Link Rules Create categories automaticallyconcepts Text Link Analysis Create categories manuallyDescribe Templates and Libraries Use visualization pane Use conditional rules to create categoriesDescribe Text Analysis Packages Use Text Link Analysis node Assess category overlapCreating a Text Mining Concept Model Create categories from a pattern Extend categories


Compare models based on using different Clustering Concepts Import coding framesResource Templates Use visualization pane Managing Linguistic ResourcesScore model data Create categories from a cluster Save resource templatesAnalyze model results Categorization Techniques Describe local and public librariesExtracted Results in the Interactive Describe linguistic based categorization Publishing librariesWorkbench Describe frequency based categorization Share librariesReview extracted concepts Describe results of different Share templatesReview extracted types categorization methods Create Text Analysis PackagesUpdate the modeling node Creating Categories Backup resourcesLinguistic Resources Create categories automatically Using Text Mining ModelsReview libraries Create categories manually Develop a model with quantitative andReview Dictionaries Use conditional rules to create categories qualitative dataManage libraries Assess category overlap Score new dataEditing Dictionaries Extend categoriesDevelop editing strategy Import coding framesAdd Type definitions Managing Linguistic Resources lineAdd Synonym definitions Save resource templates Explain CRISP-DM methodology as itAdd Exclusion definitions Describe local and public libraries applies to text miningText re-extraction to review modifications Publishing libraries Describe the steps in a text mining projectEditing Advanced Resources Share libraries A Text Mining ExampleAdd fuzzy grouping exceptions Share templates Complete a typical text mining modelingReview Text Link Rules Create Text Analysis Packages sessionText Link Analysis Backup resources Reading Text DataUse visualization pane Using Text Mining Models View text from documents within ModelerUse Text Link Analysis node Develop a model with quantitative and Read text from Web FeedsCreate categories from a pattern qualitative data Linguistic Analysis and Text MiningClustering Concepts Score new data Describe the process of text extractionUse visualization pane Describe categorization of terms andCreate categories from a cluster conceptsCategorization Techniques line Describe Templates and LibrariesDescribe linguistic based categorization Describe text mining and its relationship Describe Text Analysis PackagesDescribe frequency based categorization to data mining Creating a Text Mining Concept ModelDescribe results of different categorization Explain the text mining nodes available in Compare models based on using differentmethods Modeler Resource TemplatesCreating Categories Read text from documents Score model dataCreate categories automatically Describe linguistic analysis Analyze model resultsCreate categories manually Develop a text mining concept model Extracted Results in the InteractiveUse conditional rules to create categories Use the Interactive Workbench WorkbenchAssess category overlap Describe the resource template Review extracted conceptsExtend categories Linguistic Editing Preparation Review extracted typesImport coding frames Review Advanced Resources Update the modeling nodeManaging Linguistic Resources Use Text Link Analysis interactively Linguistic ResourcesSave resource templates Create clusters Review librariesDescribe local and public libraries Describe approaches to categorization Review DictionariesPublishing libraries Develop categorization strategy Manage librariesShare libraries Use the Template Editor Editing DictionariesShare templates Explore text mining models Develop editing strategyCreate Text Analysis Packages Add Type definitionsBackup resources Add Synonym definitionsUsing Text Mining Models line Add Exclusion definitionsDevelop a model with quantitative and Explain CRISP-DM methodology as it Text re-extraction to review modificationsqualitative data applies to text mining Editing Advanced ResourcesScore new data Describe the steps in a text mining Add fuzzy grouping exceptions

project Review Text Link RulesA Text Mining Example Text Link Analysis

line Complete a typical text mining modeling Use visualization paneExplain CRISP-DM methodology as it session Use Text Link Analysis nodeapplies to text mining Reading Text Data Create categories from a patternDescribe the steps in a text mining project View text from documents within Modeler Clustering ConceptsA Text Mining Example Read text from Web Feeds Use visualization paneComplete a typical text mining modeling Linguistic Analysis and Text Mining Create categories from a clustersession Describe the process of text extraction Categorization TechniquesReading Text Data Describe categorization of terms and Describe linguistic based categorizationView text from documents within Modeler concepts Describe frequency based categorizationRead text from Web Feeds Describe Templates and Libraries Describe results of different categorizationLinguistic Analysis and Text Mining Describe Text Analysis Packages methods


Describe the process of text extraction Creating a Text Mining Concept Model Creating CategoriesDescribe categorization of terms and Compare models based on using Create categories automaticallyconcepts different Resource Templates Create categories manuallyDescribe Templates and Libraries Score model data Use conditional rules to create categoriesDescribe Text Analysis Packages Analyze model results Assess category overlapCreating a Text Mining Concept Model Extracted Results in the Interactive Extend categoriesCompare models based on using different Workbench Import coding framesResource Templates Review extracted concepts Managing Linguistic ResourcesScore model data Review extracted types Save resource templatesAnalyze model results Update the modeling node Describe local and public librariesExtracted Results in the Interactive Linguistic Resources Publishing librariesWorkbench Review libraries Share librariesReview extracted concepts Review Dictionaries Share templatesReview extracted types Manage libraries Create Text Analysis PackagesUpdate the modeling node Editing Dictionaries Backup resourcesLinguistic Resources Develop editing strategy Using Text Mining ModelsReview libraries Add Type definitions Develop a model with quantitative andReview Dictionaries Add Synonym definitions qualitative dataManage libraries Add Exclusion definitions Score new dataEditing Dictionaries Text re-extraction to review modificationsDevelop editing strategy Editing Advanced ResourcesAdd Type definitions Add fuzzy grouping exceptions lineAdd Synonym definitions Review Text Link Rules Explain CRISP-DM methodology as itAdd Exclusion definitions Text Link Analysis applies to text miningText re-extraction to review modifications Use visualization pane Describe the steps in a text mining projectEditing Advanced Resources Use Text Link Analysis node A Text Mining ExampleAdd fuzzy grouping exceptions Create categories from a pattern Complete a typical text mining modelingReview Text Link Rules Clustering Concepts sessionText Link Analysis Use visualization pane Reading Text DataUse visualization pane Create categories from a cluster View text from documents within ModelerUse Text Link Analysis node Categorization Techniques Read text from Web FeedsCreate categories from a pattern Describe linguistic based categorization Linguistic Analysis and Text MiningClustering Concepts Describe frequency based categorization Describe the process of text extractionUse visualization pane Describe results of different Describe categorization of terms andCreate categories from a cluster categorization methods conceptsCategorization Techniques Creating Categories Describe Templates and LibrariesDescribe linguistic based categorization Create categories automatically Describe Text Analysis PackagesDescribe frequency based categorization Create categories manually Creating a Text Mining Concept ModelDescribe results of different categorization Use conditional rules to create categories Compare models based on using differentmethods Assess category overlap Resource TemplatesCreating Categories Extend categories Score model dataCreate categories automatically Import coding frames Analyze model resultsCreate categories manually Managing Linguistic Resources Extracted Results in the InteractiveUse conditional rules to create categories Save resource templates WorkbenchAssess category overlap Describe local and public libraries Review extracted conceptsExtend categories Publishing libraries Review extracted typesImport coding frames Share libraries Update the modeling nodeManaging Linguistic Resources Share templates Linguistic ResourcesSave resource templates Create Text Analysis Packages Review librariesDescribe local and public libraries Backup resources Review DictionariesPublishing libraries Using Text Mining Models Manage librariesShare libraries Develop a model with quantitative and Editing DictionariesShare templates qualitative data Develop editing strategyCreate Text Analysis Packages Score new data Add Type definitionsBackup resources Add Synonym definitionsUsing Text Mining Models Add Exclusion definitionsDevelop a model with quantitative and line Text re-extraction to review modificationsqualitative data Explain CRISP-DM methodology as it Editing Advanced ResourcesScore new data applies to text mining Add fuzzy grouping exceptions

Describe the steps in a text mining Review Text Link Rulesproject Text Link Analysis

line A Text Mining Example Use visualization paneExplain CRISP-DM methodology as it Complete a typical text mining modeling Use Text Link Analysis nodeapplies to text mining session Create categories from a patternDescribe the steps in a text mining project Reading Text Data Clustering ConceptsA Text Mining Example View text from documents within Modeler Use visualization pane


Complete a typical text mining modeling Read text from Web Feeds Create categories from a clustersession Linguistic Analysis and Text Mining Categorization TechniquesReading Text Data Describe the process of text extraction Describe linguistic based categorizationView text from documents within Modeler Describe categorization of terms and Describe frequency based categorizationRead text from Web Feeds concepts Describe results of different categorizationLinguistic Analysis and Text Mining Describe Templates and Libraries methodsDescribe the process of text extraction Describe Text Analysis Packages Creating CategoriesDescribe categorization of terms and Creating a Text Mining Concept Model Create categories automaticallyconcepts Compare models based on using Create categories manuallyDescribe Templates and Libraries different Resource Templates Use conditional rules to create categoriesDescribe Text Analysis Packages Score model data Assess category overlapCreating a Text Mining Concept Model Analyze model results Extend categoriesCompare models based on using different Extracted Results in the Interactive Import coding framesResource Templates Workbench Managing Linguistic ResourcesScore model data Review extracted concepts Save resource templatesAnalyze model results Review extracted types Describe local and public librariesExtracted Results in the Interactive Update the modeling node Publishing librariesWorkbench Linguistic Resources Share librariesReview extracted concepts Review libraries Share templatesReview extracted types Review Dictionaries Create Text Analysis PackagesUpdate the modeling node Manage libraries Backup resourcesLinguistic Resources Editing Dictionaries Using Text Mining ModelsReview libraries Develop editing strategy Develop a model with quantitative andReview Dictionaries Add Type definitions qualitative dataManage libraries Add Synonym definitions Score new dataEditing Dictionaries Add Exclusion definitionsDevelop editing strategy Text re-extraction to review modificationsAdd Type definitions Editing Advanced Resources lineAdd Synonym definitions Add fuzzy grouping exceptions Explain CRISP-DM methodology as itAdd Exclusion definitions Review Text Link Rules applies to text miningText re-extraction to review modifications Text Link Analysis Describe the steps in a text mining projectEditing Advanced Resources Use visualization pane A Text Mining ExampleAdd fuzzy grouping exceptions Use Text Link Analysis node Complete a typical text mining modelingReview Text Link Rules Create categories from a pattern sessionText Link Analysis Clustering Concepts Reading Text DataUse visualization pane Use visualization pane View text from documents within ModelerUse Text Link Analysis node Create categories from a cluster Read text from Web FeedsCreate categories from a pattern Categorization Techniques Linguistic Analysis and Text MiningClustering Concepts Describe linguistic based categorization Describe the process of text extractionUse visualization pane Describe frequency based categorization Describe categorization of terms andCreate categories from a cluster Describe results of different conceptsCategorization Techniques categorization methods Describe Templates and LibrariesDescribe linguistic based categorization Creating Categories Describe Text Analysis PackagesDescribe frequency based categorization Create categories automatically Creating a Text Mining Concept ModelDescribe results of different categorization Create categories manually Compare models based on using differentmethods Use conditional rules to create categories Resource TemplatesCreating Categories Assess category overlap Score model dataCreate categories automatically Extend categories Analyze model resultsCreate categories manually Import coding frames Extracted Results in the InteractiveUse conditional rules to create categories Managing Linguistic Resources WorkbenchAssess category overlap Save resource templates Review extracted conceptsExtend categories Describe local and public libraries Review extracted typesImport coding frames Publishing libraries Update the modeling nodeManaging Linguistic Resources Share libraries Linguistic ResourcesSave resource templates Share templates Review librariesDescribe local and public libraries Create Text Analysis Packages Review DictionariesPublishing libraries Backup resources Manage librariesShare libraries Using Text Mining Models Editing DictionariesShare templates Develop a model with quantitative and Develop editing strategyCreate Text Analysis Packages qualitative data Add Type definitionsBackup resources Score new data Add Synonym definitionsUsing Text Mining Models Add Exclusion definitionsDevelop a model with quantitative and Text re-extraction to review modificationsqualitative data line Editing Advanced ResourcesScore new data Explain CRISP-DM methodology as it Add fuzzy grouping exceptions

applies to text mining Review Text Link Rules


Describe the steps in a text mining Text Link Analysisline project Use visualization pane

Explain CRISP-DM methodology as it A Text Mining Example Use Text Link Analysis nodeapplies to text mining Complete a typical text mining modeling Create categories from a patternDescribe the steps in a text mining project session Clustering ConceptsA Text Mining Example Reading Text Data Use visualization paneComplete a typical text mining modeling View text from documents within Modeler Create categories from a clustersession Read text from Web Feeds Categorization TechniquesReading Text Data Linguistic Analysis and Text Mining Describe linguistic based categorizationView text from documents within Modeler Describe the process of text extraction Describe frequency based categorizationRead text from Web Feeds Describe categorization of terms and Describe results of different categorizationLinguistic Analysis and Text Mining concepts methodsDescribe the process of text extraction Describe Templates and Libraries Creating CategoriesDescribe categorization of terms and Describe Text Analysis Packages Create categories automaticallyconcepts Creating a Text Mining Concept Model Create categories manuallyDescribe Templates and Libraries Compare models based on using Use conditional rules to create categoriesDescribe Text Analysis Packages different Resource Templates Assess category overlapCreating a Text Mining Concept Model Score model data Extend categoriesCompare models based on using different Analyze model results Import coding framesResource Templates Extracted Results in the Interactive Managing Linguistic ResourcesScore model data Workbench Save resource templatesAnalyze model results Review extracted concepts Describe local and public librariesExtracted Results in the Interactive Review extracted types Publishing librariesWorkbench Update the modeling node Share librariesReview extracted concepts Linguistic Resources Share templatesReview extracted types Review libraries Create Text Analysis PackagesUpdate the modeling node Review Dictionaries Backup resourcesLinguistic Resources Manage libraries Using Text Mining ModelsReview libraries Editing Dictionaries Develop a model with quantitative andReview Dictionaries Develop editing strategy qualitative dataManage libraries Add Type definitions Score new dataEditing Dictionaries Add Synonym definitionsDevelop editing strategy Add Exclusion definitionsAdd Type definitions Text re-extraction to review modifications lineAdd Synonym definitions Editing Advanced Resources Explain CRISP-DM methodology as itAdd Exclusion definitions Add fuzzy grouping exceptions applies to text miningText re-extraction to review modifications Review Text Link Rules Describe the steps in a text mining projectEditing Advanced Resources Text Link Analysis A Text Mining ExampleAdd fuzzy grouping exceptions Use visualization pane Complete a typical text mining modelingReview Text Link Rules Use Text Link Analysis node sessionText Link Analysis Create categories from a pattern Reading Text DataUse visualization pane Clustering Concepts View text from documents within ModelerUse Text Link Analysis node Use visualization pane Read text from Web FeedsCreate categories from a pattern Create categories from a cluster Linguistic Analysis and Text MiningClustering Concepts Categorization Techniques Describe the process of text extractionUse visualization pane Describe linguistic based categorization Describe categorization of terms andCreate categories from a cluster Describe frequency based categorization conceptsCategorization Techniques Describe results of different Describe Templates and LibrariesDescribe linguistic based categorization categorization methods Describe Text Analysis PackagesDescribe frequency based categorization Creating Categories Creating a Text Mining Concept ModelDescribe results of different categorization Create categories automatically Compare models based on using differentmethods Create categories manually Resource TemplatesCreating Categories Use conditional rules to create categories Score model dataCreate categories automatically Assess category overlap Analyze model resultsCreate categories manually Extend categories Extracted Results in the InteractiveUse conditional rules to create categories Import coding frames WorkbenchAssess category overlap Managing Linguistic Resources Review extracted conceptsExtend categories Save resource templates Review extracted typesImport coding frames Describe local and public libraries Update the modeling nodeManaging Linguistic Resources Publishing libraries Linguistic ResourcesSave resource templates Share libraries Review librariesDescribe local and public libraries Share templates Review DictionariesPublishing libraries Create Text Analysis Packages Manage librariesShare libraries Backup resources Editing DictionariesShare templates Using Text Mining Models Develop editing strategyCreate Text Analysis Packages Develop a model with quantitative and Add Type definitions


Backup resources qualitative data Add Synonym definitionsUsing Text Mining Models Score new data Add Exclusion definitionsDevelop a model with quantitative and Text re-extraction to review modificationsqualitative data Editing Advanced ResourcesScore new data line Add fuzzy grouping exceptions

Explain CRISP-DM methodology as it Review Text Link Rulesapplies to text mining Text Link Analysis

line Describe the steps in a text mining Use visualization paneDescribe text mining and its relationship to project Use Text Link Analysis nodedata mining A Text Mining Example Create categories from a patternExplain the text mining nodes available in Complete a typical text mining modeling Clustering ConceptsModeler session Use visualization paneRead text from documents Reading Text Data Create categories from a clusterDescribe linguistic analysis View text from documents within Modeler Categorization TechniquesDevelop a text mining concept model Read text from Web Feeds Describe linguistic based categorizationUse the Interactive Workbench Linguistic Analysis and Text Mining Describe frequency based categorizationDescribe the resource template Describe the process of text extraction Describe results of different categorizationLinguistic Editing Preparation Describe categorization of terms and methodsReview Advanced Resources concepts Creating CategoriesUse Text Link Analysis interactively Describe Templates and Libraries Create categories automaticallyCreate clusters Describe Text Analysis Packages Create categories manuallyDescribe approaches to categorization Creating a Text Mining Concept Model Use conditional rules to create categoriesDevelop categorization strategy Compare models based on using Assess category overlapUse the Template Editor different Resource Templates Extend categoriesExplore text mining models Score model data Import coding frames

Analyze model results Managing Linguistic ResourcesExtracted Results in the Interactive Save resource templates

line Workbench Describe local and public librariesExplain CRISP-DM methodology as it Review extracted concepts Publishing librariesapplies to text mining Review extracted types Share librariesDescribe the steps in a text mining project Update the modeling node Share templatesA Text Mining Example Linguistic Resources Create Text Analysis PackagesComplete a typical text mining modeling Review libraries Backup resourcessession Review Dictionaries Using Text Mining ModelsReading Text Data Manage libraries Develop a model with quantitative andView text from documents within Modeler Editing Dictionaries qualitative dataRead text from Web Feeds Develop editing strategy Score new dataLinguistic Analysis and Text Mining Add Type definitionsDescribe the process of text extraction Add Synonym definitionsDescribe categorization of terms and Add Exclusion definitions lineconcepts Text re-extraction to review modifications Explain CRISP-DM methodology as itDescribe Templates and Libraries Editing Advanced Resources applies to text miningDescribe Text Analysis Packages Add fuzzy grouping exceptions Describe the steps in a text mining projectCreating a Text Mining Concept Model Review Text Link Rules A Text Mining ExampleCompare models based on using different Text Link Analysis Complete a typical text mining modelingResource Templates Use visualization pane sessionScore model data Use Text Link Analysis node Reading Text DataAnalyze model results Create categories from a pattern View text from documents within ModelerExtracted Results in the Interactive Clustering Concepts Read text from Web FeedsWorkbench Use visualization pane Linguistic Analysis and Text MiningReview extracted concepts Create categories from a cluster Describe the process of text extractionReview extracted types Categorization Techniques Describe categorization of terms andUpdate the modeling node Describe linguistic based categorization conceptsLinguistic Resources Describe frequency based categorization Describe Templates and LibrariesReview libraries Describe results of different Describe Text Analysis PackagesReview Dictionaries categorization methods Creating a Text Mining Concept ModelManage libraries Creating Categories Compare models based on using differentEditing Dictionaries Create categories automatically Resource TemplatesDevelop editing strategy Create categories manually Score model dataAdd Type definitions Use conditional rules to create categories Analyze model resultsAdd Synonym definitions Assess category overlap Extracted Results in the InteractiveAdd Exclusion definitions Extend categories WorkbenchText re-extraction to review modifications Import coding frames Review extracted conceptsEditing Advanced Resources Managing Linguistic Resources Review extracted typesAdd fuzzy grouping exceptions Save resource templates Update the modeling nodeReview Text Link Rules Describe local and public libraries Linguistic Resources


Text Link Analysis Publishing libraries Review librariesUse visualization pane Share libraries Review DictionariesUse Text Link Analysis node Share templates Manage librariesCreate categories from a pattern Create Text Analysis Packages Editing DictionariesClustering Concepts Backup resources Develop editing strategyUse visualization pane Using Text Mining Models Add Type definitionsCreate categories from a cluster Develop a model with quantitative and Add Synonym definitionsCategorization Techniques qualitative data Add Exclusion definitionsDescribe linguistic based categorization Score new data Text re-extraction to review modificationsDescribe frequency based categorization Editing Advanced ResourcesDescribe results of different categorization Add fuzzy grouping exceptionsmethods line Review Text Link RulesCreating Categories Describe text mining and its relationship Text Link AnalysisCreate categories automatically to data mining Use visualization paneCreate categories manually Explain the text mining nodes available in Use Text Link Analysis nodeUse conditional rules to create categories Modeler Create categories from a patternAssess category overlap Read text from documents Clustering ConceptsExtend categories Describe linguistic analysis Use visualization paneImport coding frames Develop a text mining concept model Create categories from a clusterManaging Linguistic Resources Use the Interactive Workbench Categorization TechniquesSave resource templates Describe the resource template Describe linguistic based categorizationDescribe local and public libraries Linguistic Editing Preparation Describe frequency based categorizationPublishing libraries Review Advanced Resources Describe results of different categorizationShare libraries Use Text Link Analysis interactively methodsShare templates Create clusters Creating CategoriesCreate Text Analysis Packages Describe approaches to categorization Create categories automaticallyBackup resources Develop categorization strategy Create categories manuallyUsing Text Mining Models Use the Template Editor Use conditional rules to create categoriesDevelop a model with quantitative and Explore text mining models Assess category overlapqualitative data Extend categoriesScore new data Import coding frames

line Managing Linguistic ResourcesExplain CRISP-DM methodology as it Save resource templates

line applies to text mining Describe local and public librariesExplain CRISP-DM methodology as it Describe the steps in a text mining Publishing librariesapplies to text mining project Share librariesDescribe the steps in a text mining project A Text Mining Example Share templatesA Text Mining Example Complete a typical text mining modeling Create Text Analysis PackagesComplete a typical text mining modeling session Backup resourcessession Reading Text Data Using Text Mining ModelsReading Text Data View text from documents within Modeler Develop a model with quantitative andView text from documents within Modeler Read text from Web Feeds qualitative dataRead text from Web Feeds Linguistic Analysis and Text Mining Score new dataLinguistic Analysis and Text Mining Describe the process of text extractionDescribe the process of text extraction Describe categorization of terms andDescribe categorization of terms and concepts lineconcepts Describe Templates and Libraries Describe text mining and its relationship toDescribe Templates and Libraries Describe Text Analysis Packages data miningDescribe Text Analysis Packages Creating a Text Mining Concept Model Explain the text mining nodes available inCreating a Text Mining Concept Model Compare models based on using ModelerCompare models based on using different different Resource Templates Read text from documentsResource Templates Score model data Describe linguistic analysisScore model data Analyze model results Develop a text mining concept modelAnalyze model results Extracted Results in the Interactive Use the Interactive WorkbenchExtracted Results in the Interactive Workbench Describe the resource templateWorkbench Review extracted concepts Linguistic Editing PreparationReview extracted concepts Review extracted types Review Advanced ResourcesReview extracted types Update the modeling node Use Text Link Analysis interactivelyUpdate the modeling node Linguistic Resources Create clustersLinguistic Resources Review libraries Describe approaches to categorizationReview libraries Review Dictionaries Develop categorization strategyReview Dictionaries Manage libraries Use the Template EditorManage libraries Editing Dictionaries Explore text mining modelsEditing Dictionaries Develop editing strategyDevelop editing strategy Add Type definitionsAdd Type definitions Add Synonym definitions line


Add Synonym definitions Add Exclusion definitions Explain CRISP-DM methodology as itAdd Exclusion definitions Text re-extraction to review modifications applies to text miningText re-extraction to review modifications Editing Advanced Resources Describe the steps in a text mining projectEditing Advanced Resources Add fuzzy grouping exceptions A Text Mining ExampleAdd fuzzy grouping exceptions Review Text Link Rules Complete a typical text mining modelingReview Text Link Rules Text Link Analysis sessionText Link Analysis Use visualization pane Reading Text DataUse visualization pane Use Text Link Analysis node View text from documents within ModelerUse Text Link Analysis node Create categories from a pattern Read text from Web FeedsCreate categories from a pattern Clustering Concepts Linguistic Analysis and Text MiningClustering Concepts Use visualization pane Describe the process of text extractionUse visualization pane Create categories from a cluster Describe categorization of terms andCreate categories from a cluster Categorization Techniques conceptsCategorization Techniques Describe linguistic based categorization Describe Templates and LibrariesDescribe linguistic based categorization Describe frequency based categorization Describe Text Analysis PackagesDescribe frequency based categorization Describe results of different Creating a Text Mining Concept ModelDescribe results of different categorization categorization methods Compare models based on using differentmethods Creating Categories Resource TemplatesCreating Categories Create categories automatically Score model dataCreate categories automatically Create categories manually Analyze model resultsCreate categories manually Use conditional rules to create categories Extracted Results in the InteractiveUse conditional rules to create categories Assess category overlap WorkbenchAssess category overlap Extend categories Review extracted conceptsExtend categories Import coding frames Review extracted typesImport coding frames Managing Linguistic Resources Update the modeling nodeManaging Linguistic Resources Save resource templates Linguistic ResourcesSave resource templates Describe local and public libraries Review librariesDescribe local and public libraries Publishing libraries Review DictionariesPublishing libraries Share libraries Manage librariesShare libraries Share templates Editing DictionariesShare templates Create Text Analysis Packages Develop editing strategyCreate Text Analysis Packages Backup resources Add Type definitionsBackup resources Using Text Mining Models Add Synonym definitionsUsing Text Mining Models Develop a model with quantitative and Add Exclusion definitionsDevelop a model with quantitative and qualitative data Text re-extraction to review modificationsqualitative data Score new data Editing Advanced ResourcesScore new data Add fuzzy grouping exceptions

Review Text Link Rulesline Text Link Analysis

line Explain CRISP-DM methodology as it Use visualization paneExplain CRISP-DM methodology as it applies to text mining Use Text Link Analysis nodeapplies to text mining Describe the steps in a text mining Create categories from a patternDescribe the steps in a text mining project project Clustering ConceptsA Text Mining Example A Text Mining Example Use visualization paneComplete a typical text mining modeling Complete a typical text mining modeling Create categories from a clustersession session Categorization TechniquesReading Text Data Reading Text Data Describe linguistic based categorizationView text from documents within Modeler View text from documents within Modeler Describe frequency based categorizationRead text from Web Feeds Read text from Web Feeds Describe results of different categorizationLinguistic Analysis and Text Mining Linguistic Analysis and Text Mining methodsDescribe the process of text extraction Describe the process of text extraction Creating CategoriesDescribe categorization of terms and Describe categorization of terms and Create categories automaticallyconcepts concepts Create categories manuallyDescribe Templates and Libraries Describe Templates and Libraries Use conditional rules to create categoriesDescribe Text Analysis Packages Describe Text Analysis Packages Assess category overlapCreating a Text Mining Concept Model Creating a Text Mining Concept Model Extend categoriesCompare models based on using different Compare models based on using Import coding framesResource Templates different Resource Templates Managing Linguistic ResourcesScore model data Score model data Save resource templatesAnalyze model results Analyze model results Describe local and public librariesExtracted Results in the Interactive Extracted Results in the Interactive Publishing librariesWorkbench Workbench Share librariesReview extracted concepts Review extracted concepts Share templatesReview extracted types Review extracted types Create Text Analysis PackagesUpdate the modeling node Update the modeling node Backup resourcesLinguistic Resources Linguistic Resources Using Text Mining Models


Review libraries Review libraries Develop a model with quantitative andReview Dictionaries Review Dictionaries qualitative dataManage libraries Manage libraries Score new dataEditing Dictionaries Editing DictionariesDevelop editing strategy Develop editing strategyAdd Type definitions Add Type definitions lineAdd Synonym definitions Add Synonym definitions Explain CRISP-DM methodology as itAdd Exclusion definitions Add Exclusion definitions applies to text miningText re-extraction to review modifications Text re-extraction to review modifications Describe the steps in a text mining projectEditing Advanced Resources Editing Advanced Resources A Text Mining ExampleAdd fuzzy grouping exceptions Add fuzzy grouping exceptions Complete a typical text mining modelingReview Text Link Rules Review Text Link Rules sessionText Link Analysis Text Link Analysis Reading Text DataUse visualization pane Use visualization pane View text from documents within ModelerUse Text Link Analysis node Use Text Link Analysis node Read text from Web FeedsCreate categories from a pattern Create categories from a pattern Linguistic Analysis and Text MiningClustering Concepts Clustering Concepts Describe the process of text extractionUse visualization pane Use visualization pane Describe categorization of terms andCreate categories from a cluster Create categories from a cluster conceptsCategorization Techniques Categorization Techniques Describe Templates and LibrariesDescribe linguistic based categorization Describe linguistic based categorization Describe Text Analysis PackagesDescribe frequency based categorization Describe frequency based categorization Creating a Text Mining Concept ModelDescribe results of different categorization Describe results of different Compare models based on using differentmethods categorization methods Resource TemplatesCreating Categories Creating Categories Score model dataCreate categories automatically Create categories automatically Analyze model resultsCreate categories manually Create categories manually Extracted Results in the InteractiveUse conditional rules to create categories Use conditional rules to create categories WorkbenchAssess category overlap Assess category overlap Review extracted conceptsExtend categories Extend categories Review extracted typesImport coding frames Import coding frames Update the modeling nodeManaging Linguistic Resources Managing Linguistic Resources Linguistic ResourcesSave resource templates Save resource templates Review librariesDescribe local and public libraries Describe local and public libraries Review DictionariesPublishing libraries Publishing libraries Manage librariesShare libraries Share libraries Editing DictionariesShare templates Share templates Develop editing strategyCreate Text Analysis Packages Create Text Analysis Packages Add Type definitionsBackup resources Backup resources Add Synonym definitionsUsing Text Mining Models Using Text Mining Models Add Exclusion definitionsDevelop a model with quantitative and Develop a model with quantitative and Text re-extraction to review modificationsqualitative data qualitative data Editing Advanced ResourcesScore new data Score new data Add fuzzy grouping exceptions

Review Text Link RulesText Link Analysis

line Use visualization paneExplain CRISP-DM methodology as it Use Text Link Analysis nodeapplies to text mining Create categories from a patternDescribe the steps in a text mining Clustering Conceptsproject Use visualization paneA Text Mining Example Create categories from a clusterComplete a typical text mining modeling Categorization Techniquessession Describe linguistic based categorizationReading Text Data Describe frequency based categorizationView text from documents within Modeler Describe results of different categorizationRead text from Web Feeds methodsLinguistic Analysis and Text Mining Creating CategoriesDescribe the process of text extraction Create categories automaticallyDescribe categorization of terms and Create categories manuallyconcepts Use conditional rules to create categoriesDescribe Templates and Libraries Assess category overlapDescribe Text Analysis Packages Extend categoriesCreating a Text Mining Concept Model Import coding framesCompare models based on using Managing Linguistic Resourcesdifferent Resource Templates Save resource templatesScore model data Describe local and public libraries


Analyze model results Publishing librariesExtracted Results in the Interactive Share librariesWorkbench Share templatesReview extracted concepts Create Text Analysis PackagesReview extracted types Backup resourcesUpdate the modeling node Using Text Mining ModelsLinguistic Resources Develop a model with quantitative andReview libraries qualitative dataReview Dictionaries Score new dataManage librariesEditing DictionariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsEditing Advanced ResourcesAdd fuzzy grouping exceptionsReview Text Link RulesText Link AnalysisUse visualization paneUse Text Link Analysis nodeCreate categories from a patternClustering ConceptsUse visualization paneCreate categories from a clusterCategorization TechniquesDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of differentcategorization methodsCreating CategoriesCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesManaging Linguistic ResourcesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesUsing Text Mining ModelsDevelop a model with quantitative andqualitative dataScore new data

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