Silk from a sow's ear: extracting usable structures from the Web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Self-organizing maps
Towards adaptive Web sites: conceptual framework and case study
Artificial Intelligence - Special issue on Intelligent internet systems
Clustering the Users of Large Web Sites into Communities
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Self organization of a massive document collection
IEEE Transactions on Neural Networks
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In this paper we propose a method to improve web search results in search engines. The Self Organizing Map is used for clustering query logs in order to identify prominent groups of user query terms for further analysis. Such groups can provide meaningful information regarding web users' search interests. Identified clusters can further be used for developing an adaptive indexing database for improving conventional search engine efficiency. The proposed hybrid model which combines neural network and indexing for web search applications can provide better data filtering effectiveness and efficiently adapt to the changes based on the web searchers' interests or behaviour patterns.