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AIC Seminar Series

Swoogle: Search and Metadata for the Semantic Web

Li DingUniversity of Maryland Baltimore County[Home Page]

Date:  2005-03-17 at 16:00

Location:  EJ228  (Directions)

   Abstract

Information retrieval technology has been central to the success of the World Wide Web. Web based indexing and search systems such as Google and Yahoo have profoundly changed the way we access information. For the Semantic Web, which aims to be the web for machine agents, to have an impact, effective information retrieval technologies are needed. As an initial foray into this territory, we have constructed Swoogle (http://swoogle.umbc.edu/) as a crawler-based indexing and retrieval system for the Semantic Web - a web of semantic web documents that serialize RDF graphs. Swoogle extracts metadata for each discovered document, computes relations among them, and provides a search interface. Swoogle also tracks provenance of defined classes and properties in the Semantic Web with its Ontology Dictionary, and helps users in creating ontologies and instance data. One of the interesting properties Swoogle computes is ontology rank, a measure of the importance of a semantic web document.

   Bio for Li Ding

Li Ding is a Ph.D candidate in the Department of Computer Science and Electrical Engineering at University of Maryland Baltimore County. His major research focus is web scale semantic web data access, which facilitate users accessing semantic web data available on the Web and evaluating quality of semantic web data in the web context. He received his M.S in Computer Science (2001) and B.S. in Computer Science (1998) from Peking University, China. His personal home page with links to publications and an informal biography is available at http://www.csee.umbc.edu/~dingli1/.

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