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© Concept Searching 2017
Groundbreaking and Game-changing
Enterprise Search
Steve Smith
Consultant
C/D/H
www.conceptsearching.com
Twitter @conceptsearch
Steve Mann
Vice President of Sales
Concept Searching
© Concept Searching 2017
Steve Mann – Vice President of Sales at Concept Searching
has proven expertise in consulting, solutions delivery, sales, and
project management in business-to-business environments.
He is experienced in Microsoft technologies, including SharePoint,
and in providing guidance on best practices, technical advice,
and solutions to address a wide range of business challenges,
leveraging a combination of Microsoft and third party technology.
Steve Smith – Consultant at C/D/H is an accomplished and
collaborative technology executive with expertise in ensuring the
business value justification and envisioning of technology solutions
that create real competitive advantage and value. He is an award-
winning consultant, and is internationally recognized as a
technology innovator.
© Concept Searching 2017
Agenda
• Who we are
• What we do
• Solution components
• Business components
• Demo
• Business benefits
© Concept Searching 2017
• Company founded in 2002
• Product launched in 2003
• Focus on management of structured and unstructured information
• Profitable, debt free
• Technology Platform
• Delivered as a web service
• Automatic concept identification, content tagging, auto-classification,
taxonomy management
• Only statistical vendor that can extract conceptual metadata
• 8 years KMWorld ‘100 Companies that Matter in Knowledge Management’
8 years KMWorld ‘Trend Setting Product’
• Authority to Operate enterprise wide US Air Force, NETCON US Army,
and Canadian SLSA
• Client base: Fortune 500/1000 organizations in Healthcare,
Financial Services, Manufacturing, Energy, Professional Services,
Pharmaceutical, Public sector and DoD
• Microsoft Gold Certification in Application Development
• Member of SharePoint PAC and TAP programs
• Deployed as a full trust Add-in for all versions of SharePoint on-premises
and SharePoint Online, including the latest vNext dedicated platform and the
government cloud
The Global Leader in
Managed Metadata Solutions
© Concept Searching 2017
Concept Searching’s technology platforms deliver
semantic metadata generation, auto-classification and
taxonomy/Term Store management, and are fully
integrated with all versions of SharePoint on-premises,
Microsoft Online/Office 365, and OneDrive for Business
What Do We Do?
These infrastructure platforms integrate not only with
SharePoint but also other content repositories, search
engines and file shares, enabling our clients to add
structure and manage their enterprise content,
regardless of environment
The resulting classification metadata is used by clients
to deliver ‘intelligent metadata solutions’ in areas such
as enhanced search, migration, data privacy, records
management, policy enforcement, compliance, text
analytics, and business and social collaboration
© Concept Searching 2017
I Can’t Make My Users Add Accurate Metadata
You are not alone – most users cannot
find what they are looking for either
• 93% of organizations rely solely on
end user tagging
• Search is viewed as essential, but
little is being done by organizations
to improve results
• IT regards developing an enterprise
metadata repository as daunting
• Business process owners don’t know
the problem can be fixed
• Metadata, auto-classification, and
taxonomies are not household terms
• Information governance is outside the
realm of the majority of organizations,
unless their metadata is high quality
and managed
• Office 365 and OneDrive for Business
have raised concerns about security,
compliance, and lifecycle management
• Organizations can no longer keep up
with the influx of unstructured data
© Concept Searching 2017
Why Does Search Make It So Hard To Find Anything?
It’s hard to find anything
• Each Source System of Record may…
• Have different login/security
• Active Directory, LDAP, Kerberos, custom
• Contain both structured and unstructured content
• Documents, pages, images, drawings, data,
metadata
• Have its own terminology or nomenclature
• Customers, products, divisions, functions
And
• Network file shares
• SharePoint, Lotus Notes, and other content management systems
• Applications – finance, HR, sales, marketing, production, custom
• Database – Oracle, Microsoft, IBM
• Web – page, wiki, blog, intranet, extranet, public, chat streams
© Concept Searching 2017
Unique Approach – Compound Term Processing
• Remains unique in the industry
• Ability to identify and correctly weight
multi-word concepts in unstructured text
8
Concept Searching
provides Automatic
Concept Term Extraction
Triple
Baseball
Three
Heart
Organ
Center
Bypass
Highway
Avoid
© Concept Searching 2017
Auto-classification Systems – Statistical
• Taxonomies and thesauri are the foundation of an auto-classifier
• They provide the vocabulary against which rules are built and ‘teach’ the machine
how to ‘understand’ and categorize content
• Accuracy rates with auto-classification systems are approximately 60%-85%
(just statistical)
Statistical
• Often use Bayes theorem: measures ‘degrees of belief’ or ‘degrees of aboutness’
• Use frequency and location to determine important or useful concepts
• Feed the system example text for the specific category
• Statistically identifies and extracts significant keywords and patterns
• Document training sets
• Match word/concept patterns to categories
• Often need sets of 50+ documents, or more, depending on the solution
• Poor document choice can cause pollution/noise
• Drawbacks
• Effort required to create the training set
• Relies on the availability of keyword-rich text
• Hard to determine problems
© Concept Searching 2017
Auto-classification Systems – Rule-based
Rule-based
• Most rely (we don’t) on Boolean (and, or, not) categorization rules to find either
a positive or negative evidence of a match to a category
• LexisNexis: and, not, not w/n, not w/para, or, pre/n, pre/, w/, not w/seg, not
w/sent, w/n, w/p, w/seg, w/s, atleast, allcaps, caps, nocaps, plural, singular
• More control over behavior
• More work
• Success depends on quality of rules
• Example: (Google OR Salesforce) NOT LinkedIn
• Drawbacks
• Dependent on the richness of the taxonomy and collection of
synonyms/keywords
• Creating and/or tweaking the rules for each category – can be onerous
depending on the solution
• Menu-driven, designed for subject-matter experts
• Most popular taxonomy management suites include auto-classification modules
• With few exceptions, taxonomy tools are generally rule-based systems
© Concept Searching 2017
Taxonomies
• Taxonomy (from Greek taxis meaning
arrangement or division and nomos
meaning law)
• Science of classification according to a
pre-determined system
• Separates elements of a group (taxon)
into subgroups (taxa) that are mutually
exclusive, unambiguous, and taken
together, includes all possibilities
• Simple to use and easy to remember
TechTarget
© Concept Searching 2017
Management and Refinement of Taxonomies
Taxonomy Management
• Product was designed for subject-matter experts
• Web-based interface
• Taxonomy component is most sophisticated in the industry,
with unique features to help the taxonomy administrator to
easily refine the taxonomy
• Ability to incorporate your nomenclature and business
terms into the taxonomy
• Automatic clue suggestion
• Eliminates the need for highly trained staff, consultants,
long training periods, or learning a new application language,
eliminates Boolean expressions
• Dynamic screen updating to changes without re-indexing
• Document movement feedback to see cause and effect of changes
© Concept Searching 2017
Features
• The goal of search is to find information – or what you are looking for
• Extreme search provides the ability to discover, analyze, visualize,
and even apply artificial intelligence
• Merging of ALL structured and unstructured contents
• Secure
• Real-time
• Normalized – unique to your corpus of information –
nomenclature map
• I say potato you say potahto
• CV versus résumé
• Structured content – data from legacy applications and
custom databases
• Unstructured content – documents and conversations from file shares
and collaboration and communications platforms
Content Intelligence is the combination of semantic technology and information science
that allows machines to model, interpret, describe, analyze, and visualize the
content of the enterprise, in order to leverage the human intelligence locked in that content
© Concept Searching 2017
Deployment Architecture
Structured Content
Un-Structured Content
On Premise
Business System
(Data)
C/D/H Open Connector Framework for Microsoft Search
(Non-invasive and Non-Proprietary Secure Indexing)
Search Crawler
(Scheduled Full and Incremental)
Network and Authentication
Search Index
(Terms and Metadata)
conceptSearch
Metadata Injection
Based on Rules
(aka Tagging) Metadata
Injection
Search
Business Intelligence
Visualization
Analytics
Artificial Intelligence
Software-as-a-
Service Business
System (Data)
SAP
Systemanalyse und
Programmentwickln
SalesForce
(Salesforce.com)
Dynamics
(Microsoft)
Siebel
(Oracle)
PeopleSoft
(PeopleSoft, Inc.)
Business System
(Sybase)
Business System
(Informix)
Business System
(MySQL)
Business System
(Microsoft SQL) SharePoint
365/16/13/10
Business System
(IBM DB2)
Lotus Notes Intranet
Network File Share
OneDrive
RESTful
Data
Access
Optionally write back Metadata
Extranets
Public Web
Documentum
Box
© Concept Searching 2017
Benefits
• Innovation
• Uniform, global practices and work streams
• Secure
• Faster and improved decision making
• Reduced costs
• Accelerates projects and update processes
• Flexibility to rapidly support changing
business needs and compliance
• Eliminate duplication
• Content optimization
© Concept Searching 2017
Outcomes
• Result is single repository of
organizationally-relevant metadata
• Eliminates end user tagging
• Normalization of content and removal
of ambiguity
• One source for management
• Flexibility to rapidly make changes to
the repository
• Easily used by subject-matter experts,
with minimal training
• Scalable
• High performance
• Multi-language
© Concept Searching 2017
What to Look For in the Demo
• Find everything within your organization within three seconds Fast
• Returns only results each person already has access to Secure
• Based on a corporate, governed nomenclature map Normalized
• Keywords, concepts, compound terms, ranges, and semantics Search
• Both structured and unstructured Content
• From file shares, LOB systems, databases, websites Sources
• Full preview of all types of content for visual detection Visualized
• Refinement based on corporate taxonomy Organized
• Applied artificial intelligence for predictive analytics Analyzed
Delivers unprecedented, unified access to all content
© Concept Searching 2017
© Concept Searching 2017
Flexibility
• Keep it as simple or as complicated as you need
• Access one application or many
• Access specific repositories or all repositories that are in use
• Access databases and/or images
• Eliminate end user tagging
• Designed for subject-matter experts
• Tangible return on investment
© Concept Searching 2017
Next Expert Webinar
Collaboration Can Be Dangerous
Tuesday, April 4th 2017
Register
In Concept Searching’s SharePoint and Office 365 State of the Market
survey results, collaboration was seen as a must-have for organizations of
all sizes.
Information sharing may have unintended consequences, and this webinar
examines secure collaboration and ways to overcome potential security
breaches.
Read more and register in the Upcoming Webinars area of our website.
© Concept Searching 2017
Thank You
Steve Smith
Consultant
C/D/H
www.conceptsearching.com
Twitter @conceptsearch
Steve Mann
Vice President of Sales
Concept Searching