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Optimal rare query suggestion with implicit user feedback

9 years 7 months ago
Optimal rare query suggestion with implicit user feedback
Query suggestion has been an effective approach to help users narrow down to the information they need. However, most of existing studies focused on only popular/head queries. Since rare queries possess much less information (e.g., clicks) than popular queries in the query logs, it is much more difficult to efficiently suggest relevant queries to a rare query. In this paper, we propose an optimal rare query suggestion framework by leveraging implicit feedbacks from users in the query logs. Our model resembles the principle of pseudo-relevance feedback which assumes that top-returned results by search engines are relevant. However, we argue that the clicked URLs and skipped URLs contain different levels of information and thus should be treated differently. Hence, our framework optimally combines both the click and skip information from users and uses a random walk model to optimize the query correlation. Our model specifically optimizes two parameters: (1) the restarting (jumping)...
Yang Song, Li-wei He
Added 14 May 2010
Updated 14 May 2010
Type Conference
Year 2010
Where WWW
Authors Yang Song, Li-wei He
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