A taxonomy of semantic web data retrieval techniques

Anila Sahar Butt, Armin Haller, Lexing Xie

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

    5 Citations (Scopus)

    Abstract

    The Semantic Web provides access to an increasing amount of structured information in a wide variety of domains. Information overload due to the large amount of structured data is as much a problem as on the traditional Web. To solve this problem, ample research has been proposed on Semantic Web data retrieval techniques and after more than a decade of research in this domain it is now reasonable to consider the questions: is the field of Semantic Web data retrieval making progress? What are the directions that have been taken? and what are some of the promising significant directions to pursue future research? To answer these questions, we review the state-of-the-art Semantic Web data retrieval techniques and define a taxonomy of these techniques to classify the ongoing research and find potential future research directions.

    Original languageEnglish
    Title of host publicationProceedings of the 8th International Conference on Knowledge Capture, K-CAP 2015
    PublisherAssociation for Computing Machinery (ACM)
    ISBN (Electronic)9781450338493
    DOIs
    Publication statusPublished - 7 Oct 2015
    Event8th International Conference on Knowledge Capture, K-CAP 2015 - Palisades, United States
    Duration: 7 Oct 201510 Oct 2015

    Publication series

    NameProceedings of the 8th International Conference on Knowledge Capture, K-CAP 2015

    Conference

    Conference8th International Conference on Knowledge Capture, K-CAP 2015
    Country/TerritoryUnited States
    CityPalisades
    Period7/10/1510/10/15

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