SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Reasoning about naming systems
ACM Transactions on Programming Languages and Systems (TOPLAS)
Characterizing browsing strategies in the World-Wide Web
Proceedings of the Third International World-Wide Web conference on Technology, tools and applications
WordNet: a lexical database for English
Communications of the ACM
Analysis of a very large web search engine query log
ACM SIGIR Forum
Placing search in context: the concept revisited
Proceedings of the 10th international conference on World Wide Web
Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
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The rapid increase of the information on the World Wide Web (WWW) makes it challenging to extract the relevant information utilizing the reasonable amount of resources. Most of the time, it become necessary for users to modify their search queries several times before they obtain the necessary information. Certainly there are various ways to circumvent this problem up to a certain extent. However, most of those approaches do not consider the searching behavior of the end users. A wide spectrum of research is on its way to personalize the web search results to meet the user needs. Therefore, we are proposing an algorithm to generate a hierarchical structure to extract the general user search patterns identified based on the randomly selected seed word and queries. In other words, we propose grouping user queries semantically to form what we refer to as "super concepts" composed of related queries. Our results indicate significant improvement in retrieval effectiveness by utilizing the generic behavioral patterns.