Neural network design
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
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
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
Syskill & webert: Identifying interesting web sites
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Discovering Document Semantics QBYS: A System for Querying the WWW by Semantics
Multimedia Tools and Applications
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This chapter presents three systems that incorporate document structure information into a search of the Web. These systems extend existing Web searches by allowing the user to request documents containing not only specific search words, but also to specify that documents be of a certain type. In addition to being able to search a local database (DB), all three systems are capable of dynamically querying the Web. Each system applies a query-by-structure approach that captures and utilizes structure information as well as content during a query of the Web. Two of the systems also employ neural networks (NNs) to organize the information based on relevancy of both the content and structure. These systems utilize a supervised Hamming NN and an unsupervised competitive NN, respectively. Initial testing of these systems has shown promising results when compared to straight keyword searches.