Using Association Rules to Discover Search Engines Related Queries
LA-WEB '03 Proceedings of the First Conference on Latin American Web Congress
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SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
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Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
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Toolbar navigation logs provide rich data for enhancing information discovery on the Web. The value of this data resides in its scope, which goes beyond that of traditional query-mining data sources, such as search-engine logs. In this paper we present a methodology for extracting relevant association rules for queries, based on historic user navigational data. In addition, we propose a graph-based approach for extracting related queries and URLs for a given query.