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SBSGRID

INTELLIGENT APPLICATIONS WITH LINKED-DATA

Contextual Reasoning in a “SearchQuery”

SBS Semantic Business Solutions, Inc

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PREVIEW

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Humans operate…

PREVIEW

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Humans operate / think contextually & associatively…

PREVIEW

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PREVIEW

This is about contextual questions

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PREVIEW

Galleries in NYCrepresenting conceptual artists from Korea who already had shows in at

least 5 capitals ?

This is about contextual questionslike this one about art…

… | Art | Pharma | Finance | …

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PREVIEW

What proteins are involved in signal

transduction and are related to pyramidal

neurons ?

This is about contextual questionslike this one from Pharma…

… | Art | Pharma | Finance | …

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PREVIEW

Accounts from the London branch with a balance > 1 mill and

transactions directly or indirectly related to IBM ?

This is about contextual questionslike this one from Finance…

… | Art | Pharma | Finance | …

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PREVIEW

…and how SBSGRID reasonsacross Linked-Data and finds precise answers

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INTRODUCTION

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Linked-Data is a world wide standard…

INTRODUCTION

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Linked-Data is a world wide standard that allows for contextual & intelligent software

INTRODUCTION

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Linked-Data is a world wide standard that allows for contextual & intelligent software across any data source

INTRODUCTION

… | Databases | Websites | Documents | Wikis | Tweets | …

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SBSGRID’s CONTRIBUTION

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SBSGRID’S CONTRIBUTION

SBSGRID takes Linked-Data…

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SBSGRID’S CONTRIBUTION

SBSGRID takes Linked-Data and turns them into

Dynamic Associative Networks

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SBSGRID’S CONTRIBUTION

This means:

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SBSGRID’S CONTRIBUTION

This means:

the context + all associationswithin information becomes visible & accessible

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SBSGRID’S CONTRIBUTION

This means:

integration of different information sources is dynamic & based on meaning

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SBSGRID’S CONTRIBUTION

This means:

intelligent information-cloudsbecome an active part in the system

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EXAMPLE

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A database contains informationabout…

Performers

EXAMPLE

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A database contains informationabout…

Performers Institutions&

EXAMPLE

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A database contains informationabout…

and a lot more…

Performers Institutions&

EXAMPLE

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Performers

InstitutionsEvents

Fairs

Magazines

Auctions

Styles CitiesNationality

TimeTime

Cities

Time

Topic

EXAMPLE

Price

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This information is not ”linked”….

EXAMPLE

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This information is not ”linked”…. relationships are implicit and not accessible

?

EXAMPLE

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Associative & contextual questions can not be asked…

??

EXAMPLE

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The user has to know the specific keywords…

???

EXAMPLE

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SBSGRID links information...

EXAMPLE

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SBSGRID links information and creates a network….

EXAMPLE

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Performers

InstitutionsEvents

Fairs

Magazines

Auctions

Styles CitiesNationality

TimeTime

Cities

Topic

Time

EXAMPLE

Price

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Now I can ask contextualquestions like…

EXAMPLE

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Now I can ask contextualquestions like…

Where are Events on Pop Art below $8000

in NYC next Week ?

EXAMPLE

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The questions can have any number of keywords…

Where are Events on Pop Art below $8000

in NYC next Week ?

EXAMPLE

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The questions can have any number of keywords & conditions…

Where are Events on Pop Art below $8000

in NYC next Week ?

EXAMPLE

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… the results will always be precise and contextual

Where are Events on Pop Art below $8000

in NYC next Week ?

EXAMPLE

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HOW IT WORKS

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Even| Go

HOW IT WORKS

During typing…

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Even| Go

Suggestions:

Person Inst. Perf. Article

Person Inst. Perf. Article

Person Inst. Perf. Article

Person Inst. Perf. Article

Person Inst. Perf. Article

Person Inst. Perf. Article

…suggestions will be made

PerformersInstitutions Events

Fairs

Magazines

Auctions

StylesCitiesNationality

TimeTime

Cities

Topic

Time

HOW IT WORKS

Price

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Events | Go

…results will be displayed

Events

Main Results:

Event Event Event

Event Event Event

Event Event Event

Related Results:

Event Event Event

Event

Event

Event

Event

Person Inst. Perf. Article

HOW IT WORKS

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Events NYC | Go

contextually joined…

InstitutionsEvents

NYCMain Results:

Event Event Event

Event Event Event

Event Event Event

Related Results:

Event

Event

Event

Event

Person Inst. Perf. Article

HOW IT WORKS

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Institutions

Events NYC Pop Art | Go

Events

Performers

NYC

Pop Art

Main Results:

Event Event Event

Event Event Event

Event

Related Results:

Event

Event

Person Inst. Perf. Article

contextually joined…

HOW IT WORKS

Event

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Events NYC Pop Art Next Week | Go

contextually joined & filtered…

Institutions

Main Results:

Events

Performers

NYC

Pop Art

Next Week

Related Results:

Person Inst. Perf. Article

HOW IT WORKS

Event Event Event

Event Event Event

Event

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Events NYC Pop Art Next Week below 8k Go

contextually joined & filtered…

Institutions

Main Results:

Events

Performers

Event Event Event NYC

Pop Art

Related Results:

Person Inst. Perf. Article

HOW IT WORKS

Price

Next Week

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…these joins are associative & contextual

HOW IT WORKS

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…because institutions

Events next Week

Institutions

Institutions in New York City

HOW IT WORKS

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…because institutions & performers

Events next Week

Performers

Performers on Pop Art

Institutions in New York City

Institutions

HOW IT WORKS

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…only appear implicitly in the user query

HOW IT WORKS

Where are Events on Pop Art below $8000

in NYC next Week ?

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=

Synonyms…

“New York City"

HOW IT WORKS

Events NYC Pop Art Next Week below 8k Go

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Synonyms, geo-information…

HOW IT WORKS

ManhattanBrooklynQueens…

NY StateUS East Coast…

=

“New York City"

Events NYC Pop Art Next Week below 8k Go

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Related categories…

HOW IT WORKS

=

xxx

xxx xxx

xxx xxx

Events NYC Pop Art Next Week below 8k Go

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=

the meaning of terms …

HOW IT WORKS

Timeframe is matched against the start-/end-date of an exhibition

Events NYC Pop Art Next Week below 8k Go

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=

the price of artworks …

HOW IT WORKS

Price range is matched with

exhibited artwork

Events NYC Pop Art Next Week below 8k Go

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HOW IT WORKS

as well as attributes…

in about within

Events NYC Pop Art Next Week below 8k Go

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HOW IT WORKS

…are handled automatically

as well as attributes…

in about within

Events NYC Pop Art Next Week below 8k Go

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RESULTS

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RESULTS

The user (or software agent) can ask intuitive, contextual & associative questions…

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RESULTS

… he can start from any direction

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RESULTS

… he can start from any direction

Pop Art Events NYC … Go

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RESULTS

… he can start from any direction

Next Week Pop Art Events … Go

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RESULTS

…and gets distinctive, unambiguous and associativeresults

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RESULTS

…which are derived from the contextual network

PerformersInstitutions Events

Fairs

Magazines

Auctions

StylesCitiesNationality

TimeTime

Cities

Topic

Time

Price

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RESULTS

He is guided and can approximate the question…

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RESULTS

PerformersInstitutions Events

Fairs

Magazines

Auctions

StylesNationality

TimeTime

Cities

Exhibitions ?

CitiesTime

Topic

Price

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RESULTS

PerformersInstitutions Events

Fairs

Magazines

Auctions

StylesNationality

TimeTime

Cities

Exhibitions in NYC ?

CitiesTime

Topic

Price

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RESULTS

PerformersInstitutions Events

Fairs

Magazines

Auctions

StylesNationality

TimeTime

Cities

Exhibitions on Pop Art

in NYC ?

CitiesTime

Topic

Price

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RESULTS

PerformersInstitutions Events

Fairs

Magazines

Auctions

StylesNationality

TimeTime

Cities

Exhibitions on Pop Art

in NYC Next Week ?

CitiesTime

Topic

Price

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RESULTS

PerformersInstitutions Events

Fairs

Magazines

Auctions

StylesNationality

TimeTime

Cities

Austrian ?

CitiesTime

Topic

Price

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RESULTS

PerformersInstitutions Events

Fairs

Magazines

Auctions

StylesNationality

TimeTime

Cities

Austrian Performers ?

CitiesTime

Topic

Price

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RESULTS

PerformersInstitutions Events

Fairs

Magazines

Auctions

StylesNationality

TimeTime

Cities

Austrian Performers represented

in NYC ?

CitiesTime

Topic

Price

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RESULTS

PerformersInstitutions Events

Fairs

Magazines

Auctions

StylesNationality

TimeTime

Cities

Previews ?

CitiesTime

Topic

Price

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RESULTS

PerformersInstitutions Events

Fairs

Magazines

Auctions

StylesNationality

TimeTime

Cities

Previews onupcoming Auctions ?

CitiesTime

Topic

Price

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IT'S ALL SEMANTICS

Thank You

www.sbsgrid.net

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APPENDIX

TECHNICAL INFORMATION

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APPENDIX

• HPC Engine

• Based on Java, TCP/IP, XML & HTML5

• Designed for Pure In-Memory (Compressed Index / Data)

• Hybrid of GraphQuery/FullTextSearch/Cache Engine

• Reasoner is aware about structural graph characteristics

• Optimized structures for syntactic & semantic decomposition

• WEB API

• XML-REST API

• JavaScript Classes for Continuous Query

• Java & C# API

• SPARQL++ Functionality

• Non Transactional (Compensate Action)

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APPENDIX

• Import API

• Triple Strings TCP/IP Interface

• Java / C# Client Interface

• Hot Updates (incremental index creation)

• Bulk Load

• Small Code

• No usage of libraries (no context switch; high security)

• 100% ownership (high end optimization)

• Specific Reasoner requests can be implemented

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APPENDIX

• Queries

• N-dimensional Reasoner- covers all query cases wanted- covers combinations of concepts, terms, data & operators

• Any Number of Keywords (still precise results)

• Support for Ranks, Synonyms, Operators

• Context Aware Full-Text-Server

• User Escort (Semantic Suggest Lists, Context Maps)

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APPENDIX

• Deployment

• JAR Deployment (with our without servlet container)

• No Middleware Development- Semantic Queries are created automatically- Data Deployment on fact level (config vs. coding)

• Data publishing and import through visual tool

• Data transport via TCP/IP

• Embedded Web-Server (optional)

• Admin GUI (runtime statistics)

• Security

• Access entitlement on field, object or namespace level

• No usage of external libraries (high security, 100% ownership)