Aggregative query generation

Reede Ren, Martin Halvey, Joemon M. Jose

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

    Abstract

    This paper proposes an aggregative query generation which exploits a media document representation called feature term to create a query from multiple media examples, e.g. images. A feature term denotes an interval of one media feature dimension, such as a bin in colour histogram. This approach (1) can easily accumulate features from multiple query examples to generate an efficient query; (2) enables the exploration of text-based retrieval models for multimedia retrieval. Two criteria, minimised chi2 and maximised entropy, are proposed to optimise feature term selection.
    Original languageEnglish
    Title of host publicationProceedings of the IEEE International Conference on Multimedia and Expo
    PublisherIEEE
    Pages850-853
    Number of pages4
    ISBN (Print)9781424442904
    DOIs
    Publication statusPublished - 2009

    Keywords

    • query generation
    • image retrieval
    • multimedia

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  • Cite this

    Ren, R., Halvey, M., & Jose, J. M. (2009). Aggregative query generation. In Proceedings of the IEEE International Conference on Multimedia and Expo (pp. 850-853). IEEE. https://doi.org/10.1109/ICME.2009.5202628