Relevance feedback and other query modification techniques
Information retrieval
Machine Learning
Neural network design
Visual information retrieval from large distributed online repositories
Communications of the ACM
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
W3QS: A Query System for the World-Wide Web
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
A Declarative Language for Querying and Restructuring the Web
RIDE '96 Proceedings of the 6th International Workshop on Research Issues in Data Engineering (RIDE '96) Interoperability of Nontraditional Database Systems
Improving Category Specific Web Search by Learning Query Modifications
SAINT '01 Proceedings of the 2001 Symposium on Applications and the Internet (SAINT 2001)
Query-by-structure approach for the web
Data mining
Syskill & webert: Identifying interesting web sites
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Extracting semantics from audio-visual content: the final frontier in multimedia retrieval
IEEE Transactions on Neural Networks
Artificial neural networks for feature extraction and multivariate data projection
IEEE Transactions on Neural Networks
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This paper describes our research into a query-by-semantics approach to searching the World Wide Web. This research extends existing work, which had focused on a query-by-structure approach for the Web. We present a system that allows users to request documents containing not only specific content information, but also to specify that documents be of a certain type. The system captures and utilizes structure information as well as content during a distributed query of the Web. The system also allows the user the option of creating their own document types by providing the system with example documents. In addition, although the system still gives users the option of dynamically querying the web, the incorporation of a document database has improved the response time involved in the search process. Based on extensive testing and validation presented herein, it is clear that a system that incorporates structure and document semantic information into the query process can significantly improve search results over the standard keyword search.