When Metadata is the ContentFrom Articles to KnowledgeSSP 2009 Annual MeetingChris Beguel – Director of Sales – TEMISBalti...
Where are we? Semantic Age!      Copyright © 2009 TEMIS –All rights reserved   2
From Words to Meaning…         Trimilax 500 mg makes me feel dizzy after ingestionTerm        Prop.     Num. Abrev. Verb /...
Metadata? Understand!                                                              Metadata                               ...
Metadata? Understand!                                                                 Metadata                            ...
Metadata? Understand!                                                                           Who: Gilbarco             ...
From Metadata to Knowledge!      Copyright © 2009 TEMIS –All rights reserved   7
What is Text Mining? v Text Mining is an information access technology… v Text Mining generates Knowledge v Text Mining se...
1. Enhanced Search ExperienceFrom standard keyword search….                       Simple recognition of words…       Copyr...
1. Enhanced Search Experience     … to Entity & Fact search!            •Make comprehensive and precise search End-User   ...
2. Faceted NavigationFrom “     narrow your search”                       ….       Copyright © 2009 TEMIS –All rights rese...
2. Faceted Navigation… to multi-dimensional faceted navigation         Point & Click              filtering    Ability to ...
3. Data Analysis and ReportingFrom bug view ….       Copyright © 2009 TEMIS –All rights reserved   13
3. Data Analysis and Reporting                                                            … to bird-                      ...
4. Information DiscoveryFrom flat list of documents ….        Copyright © 2009 TEMIS –All rights reserved   15
4. Information Discovery    … toinformation  network                                                           Discovery  ...
Semantic Enrichment at the Core     Automatic         Entity & Facts       Taxonomy         Content   Categorization      ...
Benefits to Information Producers    Increase stickiness of website to maximize       ad revenue or subscription utilizati...
Re-Packaging Content – Elsevier v Objective    • Develop a revolutionary database indexing the last 28 years      in chemi...
Exposing the Long Tail – Springer v Objective    • Mapping of meaningful words and phrases      in journal articles to enc...
Answering Burning Questions – EFL v Objectives    • Extract numerical data      from case law to enhance      information ...
Questions?Thank you!SSP 2009 Annual MeetingChris Beguel – Director of Sales – TEMISBaltimore, MD – May 09
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  1. 1. When Metadata is the ContentFrom Articles to KnowledgeSSP 2009 Annual MeetingChris Beguel – Director of Sales – TEMISBaltimore, MD – May 09
  2. 2. Where are we? Semantic Age! Copyright © 2009 TEMIS –All rights reserved 2
  3. 3. From Words to Meaning… Trimilax 500 mg makes me feel dizzy after ingestionTerm Prop. Num. Abrev. Verb /3rd Pron. Verb Adj. Prep. NounEntity Product Dosing Action Target State Event ActionFact Drug Symptom Condition Potential Adverse Effect Drug = TrimilaxKnowledge Dosing = 500mg Symptom = Tireness When = After administration Copyright © 2009 TEMIS –All rights reserved 3
  4. 4. Metadata? Understand! Metadata Title: Google gives drivers a hand at the gas pumps Source: InformationWeek Author: Antone Gonsalves Date: November 7, 2007 Entities Facts Copyright © 2009 TEMIS –All rights reserved 4
  5. 5. Metadata? Understand! Metadata Entities Companies Gilbarco Veeder-Root Gilbarco Google InformationWeek T-Mobile HTC Qualcomm Motorola Persons Lucy Sackett Sackett Locations Atlanta United States Organizations National Association of Conveni… Technologies Internet Linux Open-source … Product New Service Google Service Copyright © 2009 TEMIS –All rights reserved Facts 5
  6. 6. Metadata? Understand! Who: Gilbarco Whom: unknown What: New Service Metadata When: unknown Announcement Entities Who: Gilbarco Facts What: Google Service When: early next week Announcement Gilbarco New service Who: Sackett Launch Whom: InformationWeek When: unknown Sackett InformationWeek What: unknown Launch Gilbarco Google Service Function Function Announcement Who: Gilbarco Sackett Gilbarco With whom: Google Who: Sackett When; unknown State: Negative Partnership Company: Gilbarco Who: Google Function: spoke woman Gilbarco Google With whom: T- Mobile, HTC, Partnership Qualcom, Motorola Alliance When: unknown T-Mobile Google HTC Alliance Qualcomm Motorola Copyright © 2009 TEMIS –All rights reserved 6
  7. 7. From Metadata to Knowledge! Copyright © 2009 TEMIS –All rights reserved 7
  8. 8. What is Text Mining? v Text Mining is an information access technology… v Text Mining generates Knowledge v Text Mining serves information consumers & producers Text Mining Back-End Data Repository Text Mining Front-End (Text Analytics) Copyright © 2009 TEMIS –All rights reserved 8
  9. 9. 1. Enhanced Search ExperienceFrom standard keyword search…. Simple recognition of words… Copyright © 2009 TEMIS –All rights reserved 9
  10. 10. 1. Enhanced Search Experience … to Entity & Fact search! •Make comprehensive and precise search End-User •Get more relevant documents Benefits •Find what you don’know! t Copyright © 2009 TEMIS –All rights reserved 10
  11. 11. 2. Faceted NavigationFrom “ narrow your search” …. Copyright © 2009 TEMIS –All rights reserved 11
  12. 12. 2. Faceted Navigation… to multi-dimensional faceted navigation Point & Click filtering Ability to combine several filters at once (and/or) Self-adjusting filters to refine the search •Get a quick vision of document content End-User •Navigate within context-relevant information Benefits •Rapidly focus on targeted documents Copyright © 2009 TEMIS –All rights reserved 12
  13. 13. 3. Data Analysis and ReportingFrom bug view …. Copyright © 2009 TEMIS –All rights reserved 13
  14. 14. 3. Data Analysis and Reporting … to bird- eye view! •Visualize key Entities & Facts (pie/bar charts) End-User •Detect Entities & Facts dependencies (matrix charts) Benefits •Zoom in & out by drilling anywhere Copyright © 2009 TEMIS –All rights reserved 14
  15. 15. 4. Information DiscoveryFrom flat list of documents …. Copyright © 2009 TEMIS –All rights reserved 15
  16. 16. 4. Information Discovery … toinformation network Discovery Search Tools Panel Entities Proofs Facts •Search in knowledge, not in documents End-User •Get a graphical representation of knowledge Benefits •Discover information by navigating within Facts Copyright © 2009 TEMIS –All rights reserved 16
  17. 17. Semantic Enrichment at the Core Automatic Entity & Facts Taxonomy Content Categorization Extraction Management Editors Related Topics Editorial Web Content Extraction & Content Management Similarity Management Detection Smart Text Mining Linking Content Enrichment Trends Analysis Product & Charting Visitors & customers Management Sentiment Analysis Content Metadata Annotation Extraction Original Content Journal Scans Expert Interviews Event Reports Copyright © 2009 TEMIS –All rights reserved 17
  18. 18. Benefits to Information Producers Increase stickiness of website to maximize ad revenue or subscription utilization! v Create more engaging, longer lasting user visits • Richer user experience with context sensitive information • Enhanced page views per visits • Exposing the “long tail” through suggestions and linking • Integrate more content at a fraction of the cost v Establish your web properties as a community gateway • “70% of all searches do NOT start on Google/MSN/Yahoo” says Sue Feldman at IDC Research • Smart search and navigation are critical to user’ experience s Copyright © 2009 TEMIS –All rights reserved 18
  19. 19. Re-Packaging Content – Elsevier v Objective • Develop a revolutionary database indexing the last 28 years in chemistry patent • Provide an exceptional users’experience by using “smart content” v Results • ~20 Million Chemistry Patent documents • Searchable by chemical reactions, solvents, reactants directly extracted from the documents • Released by Elsevier-MDL in Nov. 2004 v Currently • TEMIS distributes the Chemical Entities Relationships Annotator in partnership with Elsevier Copyright © 2009 TEMIS –All rights reserved 19
  20. 20. Exposing the Long Tail – Springer v Objective • Mapping of meaningful words and phrases in journal articles to encyclopedia entries • Identification of related documents in a pool of over three million journal articles v Solution • Indexing of incoming journal articles to link journal articles with the related encyclopedia entry • Creation of semantic fingerprint for each journal article to allow search engine calculate degree of relationship • Integration with Springer’ search engine s v Benefits • Increased product sales by improving content linking Copyright © 2009 TEMIS –All rights reserved 20
  21. 21. Answering Burning Questions – EFL v Objectives • Extract numerical data from case law to enhance information access for lawyers. v Solution • Luxid® with custom annotators (address, activity, compensation, age, turnover… ) • Export numerical data as metadata to a search engine. v Benefits • Productivity gain to extract and validate metadata • Allowing to treat huge amount of case law Copyright © 2009 TEMIS –All rights reserved 21
  22. 22. Questions?Thank you!SSP 2009 Annual MeetingChris Beguel – Director of Sales – TEMISBaltimore, MD – May 09

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