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Enhancing Semantic Web Data Access

Authors: Li Ding

Date: April 06, 2006

Abstract: The Semantic Web was invented by Tim Berners-Lee in 1998 as a web of data for machine consumption. Its applicability in supporting real world applications on the World Wide Web, however, remains unclear to this day because most existing works treat the Semantic Web as one universal RDF graph and ignore the Web aspect. In fact, the Semantic Web is distributed on the Web as a web of belief: each piece of Semantic Web data is independently published on the Web as a certain agent's belief instead of the universal truth. Therefore, we enhance the current conceptual model of the Semantic Web to characterize both the content and the context of Semantic Web data. A significant sample dataset is harvested to demonstrate the non-trivial presence and the global properties of the Semantic Web on the Web. Based on the enhanced conceptual model, we introduce a novel search and navigation model for the unique behaviors in Web-scale Semantic Web data access, and develop an enabling tool -- the Swoogle Semantic Web search engine. To evaluate the data quality of Semantic Web data, we also (i) develop an explainable ranking schema that orders the popularity of Semantic Web documents and terms, and (ii) introduce a new level of granularity of Semantic Web data-- RDF molecule that supports lossless RDF graph decomposition and effective provenance tracking. This dissertation systematically investigates the Web aspect of the Semantic Web. Its primary contributions are the enhanced conceptual model of the Semantic Web, the novel Semantic Web search and navigation model, and the Swoogle Semantic Web search engine.

Type: PhdThesis

Organization: Department of COmputer Science and Electrical Engineering

School: University of Maryland, Baltimore County

Tags: semantic web, swoogle, information retrieval, ontology

Google Scholar: wXq9OSSQ2KwJ

Number of Google Scholar citations: 8 [show citations]

Number of downloads: 4471

 

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Related Projects:

Past Project

 Semantic Discovery: Discovering Complex Relationships in Semantic Web.

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