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- Publisher Website: 10.5591/978-1-57735-516-8/IJCAI11-394
- Scopus: eid_2-s2.0-84881064951
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Conference Paper: Mining User Dwell Time for Personalized Web Search Re-Ranking
Title | Mining User Dwell Time for Personalized Web Search Re-Ranking |
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Authors | |
Issue Date | 2011 |
Publisher | AAAI Press/International Joint Conferences on Artificial Intelligence. |
Citation | Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI), Barcelona, Catalonia, Spain, 16–22 July 2011, p. 2367-2372 How to Cite? |
Abstract | We propose a personalized re-ranking algorithm through mining user dwell times derived from a user's previously online reading or browsing activities. We acquire document level user dwell times via a customized web browser, from which we then infer concept word level user dwell times in order to understand a user's personal interest. According to the estimated concept word level user dwell times, our algorithm can estimate a user's potential dwell time over a new document, based on which personalized webpage re-ranking can be carried out. We compare the rankings produced by our algorithm with rankings generated by popular commercial search engines and a recently proposed personalized ranking algorithm. The results clearly show the superiority of our method. |
Description | Session: Web and Knowledge-Based Information Systems |
Persistent Identifier | http://hdl.handle.net/10722/169318 |
ISBN |
DC Field | Value | Language |
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dc.contributor.author | Xu, S | en_US |
dc.contributor.author | Jiang, H | en_US |
dc.contributor.author | Lau, FCM | en_US |
dc.date.accessioned | 2012-10-18T08:49:54Z | - |
dc.date.available | 2012-10-18T08:49:54Z | - |
dc.date.issued | 2011 | en_US |
dc.identifier.citation | Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI), Barcelona, Catalonia, Spain, 16–22 July 2011, p. 2367-2372 | en_US |
dc.identifier.isbn | 9781577355168 | - |
dc.identifier.uri | http://hdl.handle.net/10722/169318 | - |
dc.description | Session: Web and Knowledge-Based Information Systems | - |
dc.description.abstract | We propose a personalized re-ranking algorithm through mining user dwell times derived from a user's previously online reading or browsing activities. We acquire document level user dwell times via a customized web browser, from which we then infer concept word level user dwell times in order to understand a user's personal interest. According to the estimated concept word level user dwell times, our algorithm can estimate a user's potential dwell time over a new document, based on which personalized webpage re-ranking can be carried out. We compare the rankings produced by our algorithm with rankings generated by popular commercial search engines and a recently proposed personalized ranking algorithm. The results clearly show the superiority of our method. | - |
dc.language | eng | en_US |
dc.publisher | AAAI Press/International Joint Conferences on Artificial Intelligence. | - |
dc.relation.ispartof | International Joint Conference on Artificial Intelligence (IJCAI 2011) | en_US |
dc.title | Mining User Dwell Time for Personalized Web Search Re-Ranking | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Lau, FCM: fcmlau@cs.hku.hk | en_US |
dc.identifier.authority | Lau, FCM=rp00221 | en_US |
dc.description.nature | link_to_OA_fulltext | - |
dc.identifier.doi | 10.5591/978-1-57735-516-8/IJCAI11-394 | - |
dc.identifier.scopus | eid_2-s2.0-84881064951 | - |
dc.identifier.hkuros | 211553 | en_US |
dc.identifier.spage | 2367 | en_US |
dc.identifier.epage | 2372 | en_US |
dc.publisher.place | United States | - |