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lawTechCamp - Knowledge Management Panel


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Ron Carriere's presentation from lawTechCamp. Ron was a panelist on the Knowledge Management panel.

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lawTechCamp - Knowledge Management Panel

  1. 1. Leveraging Knowledge to Increase Responsiveness Ron Carriere, CEO 2011 Cognitive-Intelligence-App Presented at LawTech Camp 2011
  2. 2. C ognitive I nformatics' R esearch I nstitute Cirilab Inc. <ul><ul><li>2000 – 2011 Cirilab Incorporated in 2000. </li></ul></ul><ul><ul><ul><ul><ul><li>R&D on Advanced Multi-Dimensional Indexing Technology for Text Clustering and Profiling. </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Privately Owned Research Center to Develop </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Advanced Knowledge Management (KM) Technology Products. </li></ul></ul></ul></ul></ul>
  3. 3. The Problem <ul><li>“ information overload” was identified as the business problem of 2008 and estimated to be a $650 billion drain on the US economy. Companies like Microsoft, Google, Cisco, and Oracle are all working to try to solve the problem that they’ve helped create. Something’s got to give. </li></ul><ul><li>According to a study by research firm Basex and reported by The New York Times, </li></ul>
  4. 4. The Source <ul><li>   a folder of documents </li></ul><ul><li>· the contents of a web site </li></ul><ul><li>· all the posts in a Blog </li></ul><ul><li>· all the posts in a Discussion Group </li></ul><ul><li>· unstructured text records within a Customer Relations Management system </li></ul><ul><li>·  and many other unstructured text collections. </li></ul><ul><li>The “Captions” from a video file </li></ul>
  5. 5. The ROI <ul><li>“ Did you know the average information worker spends up to 10 hours a week searching and gathering information from the enterprise? Do you know how much that costs your organization? According to IDC, over $15,000 per employee with an average salary of $75,000. </li></ul>
  6. 6. META-Knowledge     <ul><li>Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. In effect, the role model for soft computing is the human mind. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost. </li></ul>
  7. 7. The Solution Let The Documents Express Themselves <ul><li>And give me a way to access them based on what I am interested in, not what some search engine wants me to see! Cirilab takes a very different approach. As with Cirilab Speed Read, we allow each document to express its own thematic content through a Knowledge Signature™. With a Cirilab Knowledge Map™ we simply combine all of the Knowledge Signatures™ of individual documents into one thematic hierarchical representation of the entire collection. A Cirilab Knowledge Map™ can be created from almost any repository of unstructured text </li></ul>
  8. 8. Review Information Faster <ul><li>Cirilab’s software not only finds content across multiple documents but also helps you review content when you find it. </li></ul>
  9. 9. Autonomous Knowledge Objects <ul><li>Self-Organizing </li></ul><ul><li>Self-Simplifying </li></ul><ul><li>Self-Describing </li></ul>KOS KOS KOS
  10. 10. Technology Components KGE Speed Read Enterprise Server K-store Knowledge Map Yahoo Discovery Research Workbench *Web Ready Publishing Knowledge Generation Engine TM Your Interface Here via API!
  11. 11. List of functions <ul><li>Read a document to identify and summarize relevant information </li></ul><ul><li>Profile and organize a document collection or website </li></ul><ul><li>Index and build a knowledge base of all your documents </li></ul><ul><li>Discover on the index to build a research knowledge base </li></ul><ul><li>Cleanup by finding duplicates </li></ul><ul><li>and similar documents </li></ul>Fast decision making using Cirlab’s Intelligence systems
  12. 12. Databases Minutes Press Releases Policies Official Records Workshop/Meetings Correspondence Active Organizational Intelligence (index) Index
  13. 13. <ul><li>Knowledge Query By: </li></ul><ul><ul><li>Document </li></ul></ul><ul><ul><li>Expert profile </li></ul></ul><ul><ul><li>Natural language </li></ul></ul>Technical manuals Regulations Legal Documents Policies Project Reports Correspondence Official Records Internet Intranet Query Organizational Intelligence Databases Discover
  14. 17. Semantic Wave
  15. 19. Knowledge Value Chain s Strategic Operational “ Tactical MC SI BI <ul><li>- Text Analytics </li></ul><ul><li>- Semantic Intelligence </li></ul><ul><li>Business Intelligence </li></ul><ul><li>Meta- Cognition </li></ul>- Knowledge Monitoring - “What do they know” - Functional Reporting - Text Monitoring and “ What are they talking about” Information Vectors Information Systems
  16. 20. What are they talking about?
  17. 21. Situation <ul><li>The Leukemia & Lymphoma Society is the world's largest voluntary health organization dedicated to funding blood cancer research, education, and patient services. </li></ul><ul><li>The web site’s Discussion Boards have 32 categories and over 108,000 Posts. </li></ul><ul><li>There is a desire to understand conversation patterns within common discussion themes to better understand how web site users are communicating </li></ul>
  18. 22. Approach <ul><li>LLS will extract all 108,000 Discussion Board posts </li></ul><ul><ul><li>Each Discussion Board category will be stored in one Folder </li></ul></ul><ul><ul><li>Each Topic Thread within a Discussion Board will be saved as one HTML file that will contain the initial post as well as all of the following post replies. </li></ul></ul><ul><ul><li>The Topic Thread title will be used as the file name within the Category folder </li></ul></ul><ul><li>Cirilab’s Thematic Extraction and Knowledge Mapping software to create a Thematic Knowledge Map Profiles of each of the 32 Discussion Board categories </li></ul><ul><li>MauroNewMedia will use the Knowledge Maps to analyze the thematic similarities within and among Topic posts and across DB categories </li></ul>
  19. 23. Summary <ul><li>Cirilab’s Thematic Extraction technology looks for common “thematic veins” across multiple documents within a collection and allows the researcher to quickly locate them. </li></ul><ul><li>Cirilab’s Discover technology allows the analyst to search available information for additional insight to “thematic veins” that have been discovered . </li></ul>
  20. 24. <ul><li>Contact info: Ron Carriere </li></ul><ul><li>[email_address] or [email_address] </li></ul><ul><li> </li></ul><ul><li>Note Webinars available </li></ul>