WebSifter: an ontology-based personalizable search agent for the Web

The World Wide Web provides access to a great deal of information on a vast array of subjects. In a typical Web search a vast amount of information is retrieved. The quantity can be overwhelming, and much of the information may be marginally relevant or completely irrelevant to the user´s request. We present a methodology, architecture, and proof-of-concept prototype for query construction and results analysis that provides the user with a ranking of choices based on the user´s determination of importance. The user initially designs the query with assistance from the user´s profile, a thesaurus, and previously constructed queries acting as a taxonomy of the information requirements. After the query has returned its results, decision analytic methods and information source reliability information are used in conjunction with the expanded taxonomy to rank the solution candidates