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Li, Jingfei; Song, Dawei; Zhang, Peng; Wen, Ji-Rong and Dou, Zhicheng
(2014).
DOI: https://doi.org/10.1007/978-3-319-12844-3_14
Abstract
Personalized search has recently attracted increasing attention. This paper focuses on utilizing click-through data to personalize the web search results, from a novel perspective based on subspace projection. Specifically, we represent a user profile as a vector subspace spanned by a basis generated from a word-correlation matrix, which is able to capture the dependencies between words in the “satisfied click” (SAT Click) documents. A personalized score for each document in the original result list returned by a search engine is computed by projecting the document (represented as a vector or another word-correlation subspace) onto the user profile subspace. The personalized scores are then used to re-rank the documents through the Borda’ ranking fusion method. Empirical evaluation is carried out on a real user log data set collected from a prominent search engine (Bing). Experimental results demonstrate the effectiveness of our methods, especially for the queries with high click entropy.
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About
- Item ORO ID
- 42215
- Item Type
- Conference or Workshop Item
- ISBN
- 3-319-12843-4, 978-3-319-12843-6
- ISSN
- 0302-9743
- Keywords
- personalization; user profile; subspace projection
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Copyright Holders
- © 2014 Springer International Publishing Switzerland
- Related URLs
- Depositing User
- Dawei Song