Number of the records: 1  

Evaluating Natural User Preferences for Selective Retrieval

  1. 1.
    SYSNO ASEP0331862
    Document TypeC - Proceedings Paper (int. conf.)
    R&D Document TypeConference Paper
    TitleEvaluating Natural User Preferences for Selective Retrieval
    TitleVyužití přirozených uživatelských preferencí při dotazování
    Author(s) Eckhardt, Alan (UIVT-O)
    Vojtáš, Peter (UIVT-O)
    Source TitleProceedings of 2009 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 3. - Los Alamitos : IEEE Computer Society, 2009 / Boldi P. ; Vizzari G. ; Pasi G. ; Baeza-Yates R. - ISBN 978-0-7695-3801-3
    Pagess. 104-107
    Number of pages4 s.
    ActionWI-IAT 2009 Workshops. IEEE/WIC/ACM 2009 International Conference on Web Intelligence and Intelligent Agent Technology
    Event date15.09.2009-18.09.2009
    VEvent locationMilan
    CountryIT - Italy
    Event typeWRD
    Languageeng - English
    CountryUS - United States
    Keywordsdata-mining ; user preferences ; decision support
    Subject RIVIN - Informatics, Computer Science
    R&D Projects1ET100300517 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR)
    GD201/09/H057 GA ČR - Czech Science Foundation (CSF)
    CEZAV0Z10300504 - UIVT-O (2005-2011)
    UT WOS000279801400026
    DOI10.1109/WI-IAT.2009.241
    AnnotationLearning user preferences is a complex area, especially difficult for performing experiments - every person is different and has different preferences, which often change in time. In this paper, we propose a method for testing a preference learning method that is in a sense more general than our previous attempts of testing an inductive method. We address the issue of limited rating set that results on larger datasets into more objects with the highest rating.
    WorkplaceInstitute of Computer Science
    ContactTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Year of Publishing2010
Number of the records: 1  

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