Assessing the effectiveness of the DAML ontologies for the semantic web

Abstract

The continued growth of the World Wide Web makes the retrieval of relevant information for a user's query increasingly difficult. Current search engines provide the user with many web pages, but varying levels of relevancy. In response, the Semantic Web has been proposed to retrieve and use more semantic information from the web. Our prior research has developed an intelligent agent to automate the processing of a user's query while taking into account the query's context. The intelligent agent uses WordNet and the DARPA Agent Markup Language (DAML) ontologies to act as surrogates for understanding the context of terms in a user's query. This research develops a set of syntactic, semantic, and pragmatic constructs to assess the effectiveness of the DAML ontologies so that the intelligent agent can select the most useful ontologies. These constructs have been implemented in a tool called the "Ontology Auditor" for use by the intelligent agent.