Li, Jingfei; Song, Dawei; Zhang, Peng; Wen, Ji-Rong and Dou, Zhicheng
(2014).
| DOI (Digital Object Identifier) Link: | https://doi.org/10.1007/978-3-319-12844-3_14 |
|---|---|
| Google Scholar: | Look up in Google Scholar |
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.
| Item Type: | Conference or Workshop Item |
|---|---|
| Copyright Holders: | 2014 Springer International Publishing Switzerland |
| ISBN: | 3-319-12843-4, 978-3-319-12843-6 |
| ISSN: | 0302-9743 |
| Keywords: | personalization; user profile; subspace projection |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Related URLs: | |
| Item ID: | 42215 |
| Depositing User: | Dawei Song |
| Date Deposited: | 06 Mar 2015 09:17 |
| Last Modified: | 07 Dec 2018 10:29 |
| URI: | http://oro.open.ac.uk/id/eprint/42215 |
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