Deriving implicit user feedback from partial URLs for effective web page retrieval

Rongmei Li, Theo van der Weide

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

Abstract

User click-throughs provide a search context for understanding the user need of complex information. This paper re-examines the effectiveness of this approach when based on partial clicked data using the language modeling framework. We expand the original query by topical terms derived from clicked Web pages and enhance early precision via a more compact document representation. Since our URLs of Web pages are stripped, we first reconstruct them at different levels based on different collections. Our experimental results on the GOV2 test collection and AOL query log show improvement by 31.7% and 28.3% significantly in statMAP for two sources of reconstruction and 153 ad-hoc queries. Our model also outperforms pseudo relevance feedback.
Original languageEnglish
Title of host publicationRIAO '10
Subtitle of host publicationAdaptivity, Personalization and Fusion of Heterogeneous Information
PublisherACM Press
Pages124-125
Publication statusPublished - 2010
Event9th International Conference on Computer-Assisted Information Retrieval, RIAO 2010: Adaptivity, Personalization and Fusion of Heterogeneous Information (Recherche d'Information et ses Applications) - Bibliotheque Nationale de France, Paris, France
Duration: 28 Apr 201030 Apr 2010
Conference number: 9

Conference

Conference9th International Conference on Computer-Assisted Information Retrieval, RIAO 2010
Abbreviated titleRIAO
CountryFrance
CityParis
Period28/04/1030/04/10

Keywords

  • IR-78541

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