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Bradford
May 26, 2009 to May 29, 2009
ISBN: 978-1-4244-3999-7
pp: 762-767
ABSTRACT
Web search query logs contain valuable information which can be utilized for personalization and improvement of search engine performance. The aim in this paper is to cluster users based on their interests, and analyze the temporal dynamics of these clusters. In the proposed approach, we first apply clustering techniques to group similar users with respect to their web searches. Anticipating that the small number of query terms used in search queries would not be sufficient to obtain a proper clustering scheme, we extracted the summary content of the clicked web page from the query log. In this way, we enriched the feature set more efficiently than the content crawling. We also provide preliminary survey results to evaluate clusters. Clusters may change with the user flow from one cluster to the other as time passes. This is due to the fact that users' interests may shift over time. We used statistical methods for the analysis of temporal changes in users' interests. As a case study, we experimented on the query logs of a search engine.
INDEX TERMS
Web Mining, Clustering, Search Engine, Query Log
CITATION
Aysegul Cayci, Selcuk Sumengen, Cagatay Turkay, Selim Balcisoy, Yucel Saygin, "Temporal Dynamics of User Interests in Web Search Queries", WAINA, 2009, 2009 IEEE 23rd International Conference on Advanced Information Networking and Applications Workshops (WAINA), 2009 IEEE 23rd International Conference on Advanced Information Networking and Applications Workshops (WAINA) 2009, pp. 762-767, doi:10.1109/WAINA.2009.71
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