Amit Sheth's Keynote talk given at: “Semantic Web in Action: Ontology-driven information search, integration and analysis,” Net Object Days 2003 and MATES03, Erfurt, Germany, September 23, 2003. http://knoesis.org
Note: slides 51-55 have audio.
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Semantic Web in Action: Ontology-driven information search, integration and analysis
1. Talk Abstract Semantic Web in Action Ontology-driven information search, integration and analysis Net Object Days and MATES, Erfurt, September 23, 2003 Amit Sheth Semagix , Inc. and LSDIS Lab , University of Georgia
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4. Broad Scope of Semantic (Web) Technology Other dimensions: how agreements are reached, … Lots of Useful Semantic Technology (interoperability, Integration) Cf: Guarino, Gruber Gen. Purpose, Broad Based Scope of Agreement Task/ App Domain Industry Common Sense Degree of Agreement Informal Semi-Formal Formal Agreement About Data/ Info. Function Execution Qos Current Semantic Web Focus Semantic Web Processes
42. Scalable Architecture SQS SQS SQS SES SES SES Metabase Ontology cluster scale-up Semantic Application LOAD BALANCER LOAD BALANCER
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44. BLENDED BROWSING & QUERYING INTERFACE VideoAnywhere and Taalee Semantic Search Engine ATTRIBUTE & KEYWORD QUERYING uniform view of worldwide distributed assets of similar type SEMANTIC BROWSING Targeted e-shopping/e-commerce assets access
45. Semantic Enhancement used in Semantic Search Click on first result for Jamal Anderson View metadata. Note that Team name and League name are also included in the metadata Search for ‘Jamal Anderson’ in ‘Football’ View the original source HTML page. Verify that the source page contains no mention of Team name and League name . They are value-additions to the metadata to facilitate easier search.
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47. Bill Gates relationships within text in the document relationships across documents in the same corpus Ontology Corpus of documents Databases relationships across documents outside of the same corpus Single document belonging to a corpus Semantic Information Integration spanning three layers of semantic relationships
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49. Semantic Application Example: Equity Research Dashboard with Blended Semantic Querying and Browsing Focused relevant content organized by topic ( semantic categorization ) Automatic Content Aggregation from multiple content providers and feeds Related relevant content not explicitly asked for (semantic associations) Competitive research inferred automatically Automatic 3 rd party content integration
50. Semantic Information Integration in Portals Sample content item that is explicitly or implicitly associated semantically to facets in user profile User profile as a context for semantic integration of diverse yet relevant content Semantic integration and presentation of various types of personalized content items in one place
51. Anti Money Laundering – Know Your Customer Risk Profiles are developed for individuals or companies. If the risk profile changes based on new information the individuals Risk Profile and Branch Aggregate Risk Profile is automatically updated R
Semantics (of information, communication) is a very old area, and extensive work on Semantic Technology has been going on for well over a decade (many projects on semantic interoperability, semantic information brokering) Semantic Web and related visions are being achieved in various depth and scope – mostly starting with targeted applications where requirements are much better understood and scope is manageable