Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Data mining and knowledge discovery in databases
Communications of the ACM
Cyberspace 2000: dealing with information overload
Communications of the ACM
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
30% accessible—a survey of the UK Wide Web
Selected papers from the sixth international conference on World Wide Web
Journal of the American Society for Information Science
Results and challenges in Web search evaluation
WWW '99 Proceedings of the eighth international conference on World Wide Web
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Knowledge-Based Approaches to Query Expansion in Information Retrieval
AI '96 Proceedings of the 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Discovering Association Rules Based on Image Content
ADL '99 Proceedings of the IEEE Forum on Research and Technology Advances in Digital Libraries
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
Template-based information mining from HTML documents
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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The World-Wide Web is an enormous, distributed, and heterogeneous information space. Currently, with the growth of available data, finding interesting information is difficult. Search engines like Altavista are useful, but their results are not always satisfactory. In this paper, we present a method called Knowledge Discovery on the Web for extracting connections between terms. The knowledge in these connections is used for query expansion. We present experiments performed with our system, which is based on the SMART retrieval system. We used the comparative precision method for evaluating our system against three well-known Web search engines on a collection of 60,000 Web pages. These pages are a snapshot of the IMAG domain and were captured using the CLIPS-Index spider. We show how the knowledge discovered can be useful for search engines.