University of Glasgow at ImageCLEFPhoto 2009: optimising similarity and diversity in image retrieval

Teerapong Leelanupab, Guido Zuccon, Anuj Goyal, Martin Halvey, P Punitha, Joemon M. Jose

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

    Abstract

    In this paper we describe the approaches adopted to generate the runs submitted to ImageCLEFPhoto 2009 with an aim to promote document diversity in the rankings. Four of our runs are text based approaches that employ textual statistics extracted from the captions of images, i.e. MMR [1] as a state of the art method for result diversification, two approaches that combine relevance information and clustering techniques, and an instantiation of Quantum Probability Ranking Principle. The fifth run exploits visual features of the provided images to re-rank the initial results by means of Factor Analysis.
    Original languageEnglish
    Title of host publicationMultilingual Information Access Evaluation II - Multimedia Experiments
    Subtitle of host publicationProceedings of the 10th Workshop of the Cross-Language Evaluation Forum (CLEF 2009)
    PublisherSpringer
    Pages133-141
    Number of pages9
    ISBN (Print)9783642157509
    DOIs
    Publication statusPublished - 2010

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Berlin Heidelberg
    Volume6242
    ISSN (Print)0302-9743

    Keywords

    • image retrieval
    • ImageCLEF
    • diversity

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