Learning knowledge bases for multimedia in 2015

Lexing Xie, Haixun Wang

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Citation (Scopus)


    Knowledge acquisition, representation, and reasoning has been one of the long-standing challenges in arti-cial intelli-gence and related application areas. Only in the past few years, massive amounts of structured and semi-structured data that directly or indirectly encode human knowledge be-came widely available, turning the knowledge representation problems into a computational grand challenge with feasible solutions in sight. The research and development on knowl-edge bases is becoming a lively fusion area among web in-formation extraction, machine learning, databases and infor-mation retrieval, with knowledge over images and multime-dia emerging as another new frontier of representation and acquisition. This tutorial aims to present a gentle overview of knowledge bases on text and multimedia, including rep-resentation, acquisition, and inference. In particular, the 2015 edition of the tutorial will include recent progress from several active research communities: web, natural language processing, and computer vision and multimedia.

    Original languageEnglish
    Title of host publicationMM 2015 - Proceedings of the 2015 ACM Multimedia Conference
    PublisherAssociation for Computing Machinery, Inc
    Number of pages2
    ISBN (Electronic)9781450334594
    Publication statusPublished - 13 Oct 2015
    Event23rd ACM International Conference on Multimedia, MM 2015 - Brisbane, Australia
    Duration: 26 Oct 201530 Oct 2015

    Publication series

    NameMM 2015 - Proceedings of the 2015 ACM Multimedia Conference


    Conference23rd ACM International Conference on Multimedia, MM 2015


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