Learning knowledge bases for text and multimedia

Lexing Xie, Haixun Wang

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

    1 Citation (Scopus)

    Abstract

    Knowledge acquisition, representation, and reasoning has been one of the long-standing challenges in artificial intelligence 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 became widely available, turning the knowledge representation problems into a computational grand challenge with feasible solutions in sight. The research and development on knowledge bases is becoming a lively fusion area among web information extraction, machine learning, databases and information retrieval, with knowledge over images and multimedia 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 representation, acquisition, and inference. The content of this tutorial are intended for surveying the field, as well as for educating practitioners and aspiring researchers.

    Original languageEnglish
    Title of host publicationMM 2014 - Proceedings of the 2014 ACM Conference on Multimedia
    PublisherAssociation for Computing Machinery
    Pages1235-1236
    Number of pages2
    ISBN (Electronic)9781450330633
    DOIs
    Publication statusPublished - 3 Nov 2014
    Event2014 ACM Conference on Multimedia, MM 2014 - Orlando, United States
    Duration: 3 Nov 20147 Nov 2014

    Publication series

    NameMM 2014 - Proceedings of the 2014 ACM Conference on Multimedia

    Conference

    Conference2014 ACM Conference on Multimedia, MM 2014
    Country/TerritoryUnited States
    CityOrlando
    Period3/11/147/11/14

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