SBSGRID In_Memory-Reasoner_and_Search_Query_Engine

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SBSGRID

IN-MEMORY REASONING & SEARCHQUERY ENGINE

SBS Semantic Business Solutions, Inc

Overview

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INTRODUCTION LINKED-DATA

Linked-Data is a substantial movement & technology for:

Meaning Based Computing

Next Generation Search & Query

Next Generation Information Discovery

Web based Machine Learning & AI

1 see http://www.linkeddata.org

1

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Linked-Data is also the enabler for the so-called Web 3.0

1 see http://www.linkeddata.org

1

Linked-Data approach works (vs. SemWeb)

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Linked-Data are virtualizing the data-source:

STRUCTURED

LINKED-DATA

RelationalDBs Wikis Documents Websites

SEMISTRUCTURED

UN-STRUCTURED

Wrapper Wrapper Crawler Crawler

Mediated Schema

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INTRODUCTION SEARCHQUERY

SearchQueries leverage the power of Linked-Data:

Contextual & Associative Queries

On Data Level (No Semantic Search)

Information Travel from any Angle

Question in Free Form

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SearchQueries operate on interlinked data (not only linked concepts):

Complex Queries (any # of keywords !!)

Conditions (>, <, =, etc)

Semantic Operators (“today”<->date info)

Analytics (sum, sqrt, div, etc)

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SearchQuery: Quick Tour

Unlinked Data (Relational Database)

Dataset example from the art world


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Linked-Data (Semantic FactBase)



Linked Concepts + Linked Data

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"Galleries in NYC selling Modern Painting below 8k"

Any # of Keywords are Contextually Matched



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“Current Exhibitions on Gerhard Richter in Germany"

The Semantic Operator “Current Exhibitions” is matched against Date Information

Note the potential Polymorphic Role on “Gerhard”



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“Japanese and Korean Art between 10k & 20k"

The Price Range executes > and < Operations



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Applicability

SBSGRID Application Scenarios…

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APPLICABILITY

1 see Slides: SBSGRID SearchQuery Explained

2 see White Pager: Visual Linked-Data Publishing

Data Source A

Wrapper

Scenario: One Database

In-MemorySBSGRID Engine

Browser SearchQuery

High Performance

Automatic Semantics2

1

Self-Governed

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Scenario: Many Databases

Browser SearchQuery• Works Instant & Incremental

• Contains Ontology Alignment

• Meaning based Information Linking

1 see White Paper: Meaning based Information Linking

1

Data Source A

Wrapper

Data Source A

Wrapper

Data Source A

Wrapper


Self-Governed

APPLICABILITY

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Data Source A

Data Source A

Data Source A

ETLData

Warehouse

Classic Relational Approach

Review: ETL Process

APPLICABILITY

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Scenario: Contextual Analytics

Contextual Cubes on the Fly

Browser


1 see White Paper: SBSGRID Contextual Analytics

1

APPLICABILITY

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Scenario: Linked-Data Publishing

1 see White Pager: Visual Linked-Data Publishing

Data Source A

Wrapper


Browser Visual Process1

Self-Governed

• Drag & Drop Interface

• Instant SearchQuery

• JDBC/ODBC Data-sourcesUI Tool

APPLICABILITY

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Scenario: Triple-Store Caching

TripleStore


Browser SearchQuery

High Performance

1

• Transactional Store

• RDF/RDFS/OWL Support

• SPARQL Support

APPLICABILITY

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Scenario: NLP Leverage

APPLICABILITY

Browser SearchQuery• Works Instant & Incremental

• Contains Ontology Alignment

• Meaning based Information Linking

1 see White Paper: Meaning based Information Linking

1

WIKI

NLP

Documents

NLP

Websites

NLP


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SUMMARY

SBSGRID is the first tool for Dynamic Linked-Data:

No Ontology Development

No Middleware Development

Visual Linked-Data Publishing

Instant & Incremental Use

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Appendix

Some more info’s…

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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)

Technology

SBSGRID In_Memory-Reasoner_and_Search_Query_Engine