Learning to extract symbolic knowledge from the World Wide Web
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Grouper: a dynamic clustering interface to Web search results
WWW '99 Proceedings of the eighth international conference on World Wide Web
Bringing order to the Web: automatically categorizing search results
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Enabling Concept-Based Relevance Feedback for Information Retrieval on the WWW
IEEE Transactions on Knowledge and Data Engineering
OntoSeek: Content-Based Access to the Web
IEEE Intelligent Systems
The YPA - An Assistant for Classified Directory Enquiries
Intelligent Systems and Soft Computing: Prospects, Tools and Applications
Exploiting Structure for Intelligent Web Search
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 4 - Volume 4
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Web search has become an everyday activity for millions of people. Unfortunately, there is a number of well known problems associated with it. Two of those problems are to express an information need as a set of search terms and to actually present only the most relevant matches for this query once the search has been performed. This paper tackles those problems for limited domains where the amount of data might be large, but the application of some fairly simple intelligent techniques to extract conceptual information is feasible. We describe how a dialogue system utilizes the extracted knowledge to guide the search. This paper builds on earlier work which focussed on the extraction of knowledge-rich indices.