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  Task-aware Search Personalization

Luxenburger, J., Elbassuoni, S., & Weikum, G. (2008). Task-aware Search Personalization. In S.-H. Myaeng, D. W. Oard, F. Sebastiani, T.-S. Chua, & M.-K. Leong (Eds.), ACM SIGIR 2008: Thirty-First Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 721-722). New York, NY: ACM.

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Urheber

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 Urheber:
Luxenburger, Julia1, Autor           
Elbassuoni, Shady1, 2, Autor           
Weikum, Gerhard1, Autor           
Affiliations:
1Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              
2International Max Planck Research School, MPI for Informatics, Max Planck Society, ou_1116551              

Inhalt

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Schlagwörter: -
 Zusammenfassung: Search personalization has been pursued in many ways, in order to provide better result rankings and better overall search experience to individual users. However, blindly applying personalization to all user queries, for example, by a background model derived from the user's long-term query-and-click history, is not always appropriate for aiding the user in accomplishing her actual task. User interests change over time, a user sometimes works on very different categories of tasks within a short timespan, and history-based personalization may impede a user's desire of discovering new topics. In this paper we propose a personalization framework that is selective in a twofold sense. First, it selectively employs personalization techniques for queries that are expected to benefit from prior history information, while refraining from undue actions otherwise. Second, we introduce the notion of tasks representing different granularity levels of a user profile, ranging from very specific search goals to broad topics, and base our reasoning selectively on query-relevant user tasks. These considerations are cast into a statistical language model for tasks, queries, and documents, supporting both judicious query expansion and result re-ranking. The effectiveness of our method is demonstrated by an empirical user study.

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Sprache(n): eng - English
 Datum: 2009-03-252008
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: New York, NY : ACM
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: eDoc: 428153
URI: http://doi.acm.org/10.1145/1390334.1390469
Anderer: Local-ID: C125756E0038A185-95FBECD09D7B613BC1257424005384EC-LuxSigir2008
 Art des Abschluß: -

Veranstaltung

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Titel: Untitled Event
Veranstaltungsort: Singapore
Start-/Enddatum: 2008-07-20 - 2008-07-24

Entscheidung

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Projektinformation

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Quelle 1

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Titel: ACM SIGIR 2008 : Thirty-First Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Genre der Quelle: Konferenzband
 Urheber:
Myaeng, Sung-Hyon, Herausgeber
Oard, Douglas W., Herausgeber
Sebastiani, Fabrizio, Herausgeber
Chua, Tat-Seng, Herausgeber
Leong, Mun-Kew, Herausgeber
Affiliations:
-
Ort, Verlag, Ausgabe: New York, NY : ACM
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 721 - 722 Identifikator: ISBN: 978-1-60558-164-4

Quelle 2

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Titel: ACM SIGIR Forum
Genre der Quelle: Reihe
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: - Identifikator: -