Improving news ranking by community tweets
Proceedings of the 21st international conference companion on World Wide Web
Incorporating variability in user behavior into systems based evaluation
Proceedings of the 21st ACM international conference on Information and knowledge management
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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.