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CALSCALE:Gregorian
X-WR-CALNAME:Beyond Auto-Categorization
BEGIN:VEVENT
DTSTART;VALUE=DATE:20070801
DTEND;VALUE=DATE:20070802
SUMMARY:Beyond Auto-Categorization
LOCATION:Virtual
DESCRIPTION:TaxoCoP Monthly Call
\nDate & Time: August 1st, 1:00pm EDT
\nCo
 st: 50$
\n
\nRegister for the session at http://www.earley.com/_July2007.as
 p
\n
\nRecently, tagging, folkonomies and ontologies are emerging as new wa
 ys to capture social and domain knowledge. Furthermore, using the emerging 
 Semantic Web standards such as RDF and OWL, and technologies for automatic 
 metadata extraction (annotation) and semantic analysis, we have alternative
  or newer ways to organize, integrate and exploit (search, analyze and perf
 orm knowledge discovery) information within enterprise and on the Web.
\n
\
 nWe will provide an overview of current state of the art and share some per
 sonal experiences that may answer the following questions
\n
\n    * what t
 ypes of ontologies have been built, how they are built, is there a typical 
 ontology, low large a typical ontology is, what does it take to build and m
 aintain ontologies
\n    * how well (semantic) metadata annotation/extracti
 on work
\n    * what is the status and adoption of Semantic Web standards a
 nd technologies
\n    * what kind of advanced capabilities (analytical, dec
 ision making and discovery) are made possible using Semantic Web technologi
 es
\n    * which domains have been more amenable to applications of ontolog
 ies and Semantic Web technologies, and what are few use cases?
\n
\nMost of
  the discussion will be through the use of real-world examples/applications
 .
\n
\nPresenter: Dr. Amit Sheth
\nDr. Sheth is the LexisNexis Ohio Eminent
  Scholar and director of the Knowledge Enabled Information and Services Cen
 ter (http://knoesis.wright.edu) at Wright State University. Earlier he foun
 ded and directed the LSDIS lab at University of Georgia, and worked at Bell
 core, Unisys and Honeywell. His research interests include the Semantic Web
 , services science, and information integration and analysis.
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