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Extracting user interests from search query logs: A clustering approach

Lyes Limam 1 David Coquil Harald Kosch 2 Lionel Brunie 1
1 DRIM - Distribution, Recherche d'Information et Mobilité
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : This paper proposes to enhance search query log analysis by taking into account the semantic properties of query terms. We first describe a method for extracting a global semantic representation of a search query log and then show how we can use it to semantically extract the user interests. The global representation is composed of a taxonomy that organizes query terms based on generalization/specialization (“is a”) semantic relations and of a function to measure the semantic distance between terms. We then define a query terms clustering algorithm that is applied to the log representation to extract user interests. The evaluation has been done on large real-life logs of a popular search engine.
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Lyes Limam, David Coquil, Harald Kosch, Lionel Brunie. Extracting user interests from search query logs: A clustering approach. the 7th International Workshop on Text-based Information Retrieval (TIR '10) in conjunction with the 21st International Conference on Database and Expert Systems Applications (DEXA '10), Aug 2010, Bilbao, Spain. pp.5-9, ⟨10.1109/DEXA.2010.23⟩. ⟨hal-01381483⟩



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