TOWARDS THE SEMANTIC WEB: KNOWLEDGE REPRESENTATION IN A DYNAMIC, DISTRIBUTED ENVIRONMENT

The World Wide Web is an information resource with virtually unlimited potential. However, this potential is relatively untapped because it is difficult for machines to process and integrate this information meaningfully. Recently, researchers have begun to explore the potential of associating web content with explicit meaning, in order to create a Semantic Web. Rather than rely on natural language processing to extract this meaning from existing documents, this approach requires authors to describe documents using a knowledge representation language. Although knowledge representation can solve many of the Web’s problems, existing research cannot be directly applied to the Semantic Web. Unlike most traditional knowledge bases, the Web is highly decentralized, changes rapidly, and contains a staggering amount of information. This thesis examines how knowledge representation must change to accommodate these factors. It presents a new method for integrating web data sources based on ontologies, where the sources explicitly commit to one or more autonomously developed ontologies. In addition to specifying the semantics of a set of terms, the ontologies can extend or revise one another. Thi