Applications of Semantic Technology in the Real World Today

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Amit Sheth, "Applications of Semantic Technology in the Real World Today," talk given at Semantic Technology Conference, San Jose, CA, March 2005.

This talk reviews real-world applications mainly deployed in financial services industry developed over Semagix Freedom platform described in http://knoesis.org/library/resource.php?id=810 . Technology is based on this patent: "Semantic web and its applications in browsing, searching, profiling, personalization and advertising", http://knoesis.org/library/resource.php?id=843 .

Amit Sheth founded Taalee in 1999, which merged with Voquette in 2002, and then with Semagix in 2004.

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  • Taalee, a Semantic Web company was started in 1999 with initial application for A/V Semantic search/browsing/personalization/advertisement/targeting, but after merger with Voquette and then Semagix, we adopted the technology for Enterprise applications because it was too early for Web/consumer centric apps in early 2000s (see http://knoesis.org/library/resource.php?id=735 for early Web centric Semantic applications enabled by 2000. Voquette SCORE/Semagix Freedom (first released 2001, significant deployed semantic applications stating 2002 — core technology/ applications in Financial services space still ongoing, now owned by Actimize; Know Your Customer app to support Patriot law regulations was deployed at a majority of top 30 banks by 2006). Technical details in this 2001 patent: http://knoesis.org/library/resource.php?id=843 and this 2002 article: http://knoesis.org/library/resource.php?id=810
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  • Semantic Web in a Nutshell: - Ontology as the centerpiece - Metadata that associate meaning to content - Computing (complex querying, inferencing, other reasoning) that support semantic applications
  • CENTRAL ROLE OF ONTOLOGIES Ontology represents agreement, represents common terminology/nomenclature Ontology is populated with extensive domain knowledge or known facts/assertions Key enabler of semantic metadata extraction from all forms of content: unstructured text (and 150 file formats) semi-structured (HTML, XML) and structured data Ontology is in turn the center price that enables resolution of semantic heterogeneity semantic integration semantically correlating/associating objects and documents
  • Large scale metadata extraction and semantic annotation is possible. IBM WebFountain [Dill et al 2003] demonstrates the ability to annotate on a Web scale (i.e., over 2.5 billion pages), while Semagix Freedom related technology [Hammond et al 2002] demonstrates capabilities that work for a few million documents per day per server. However, the general trade-off of depth versus scale applies. Storage and manipulation of metadata for millions to hundreds of millions of content items requires database techniques with the challenge of improving performance and scale in presence of more complex structures
  • (a) Serve global population of 500 users (B) Complete all source checks in 20 seconds or less © Integrate with enterprise single sign-on systems (d) Meet complex name matching and disambiguation criteria (e) Adhere to complex security requirements Results: Rapid, accurate KYC checks; Automatic audit trails; Reduction in in false positives; Streamlines and enhances due diligence of potential high risk accounts
  • Requirements: (a) Merge and link case data from multiple sources to a taxonomy using effective identification, disambiguation, and analysis; (b) Ability to use pre-defined/investigation-specific case studies for search and match © Positive and negative searching of cases (d) Ability to explore case data starting from any entity via link analysis Results: Superior, faster identification of prolific offenders; Better prioritization of cases; Greater investigator productivity and effectiveness
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