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    A practical image retrieval framework for tourism industry

    20412_downloaded_stream_400.pdf (1.819Mb)
    Access Status
    Open access
    Authors
    Zhao, Shuxin
    Potdar, Vidyasagar
    Chang, Elizabeth
    Date
    2007
    Type
    Conference Paper
    
    Metadata
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    Citation
    Zhao, Shuxin and Potdar, Vidyasagar and Chang, Elizabeth. 2007. : A practical image retrieval framework for tourism industry, Industrial Electronics, 2007. ISIE 2007. IEEE International Symposium on, 4-7 Jun 2007, pp. 2928-2932. Vigo, Spain: IEEE.
    Source Conference
    Industrial Electronics, 2007. ISIE 2007. IEEE International Symposium on
    DOI
    10.1109/ISIE.2007.4375079
    Faculty
    Curtin Business School
    School
    Centre for Extended Enterprises and Business Intelligence
    Remarks

    Copyright 2007 IEEE

    This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

    URI
    http://hdl.handle.net/20.500.11937/14652
    Collection
    • Curtin Research Publications
    Abstract

    Image Retrieval (IR) is one of the most exciting and fastest growing research domains in the field of multimedia technology. And in the industrial ecosystems, images of products, activities, marketing materials etc are needed to be managed and fetched in an efficient way to support and facilitate business processes. Current techniques for IR including keyword based, content based and ontology based image retrieval have several unsolved issues. We promote the ontology based IR approach and focus on two issues: firstly, the difficulty in constructing ontologies of images for those industries without ontology professionals, and, secondly, none of the existing approaches consider image content ranking in search results. In this paper, we propose a practical framework to tackle these issues by introducing an Abstract Image Ontology that serves as a blueprint of image ontologies and by incorporating a Concept Instance Ranking Scheme to allow ranking of each of the contents expressed in images, thus providing extra information for IR process. An application scenario in the tourism industry area is also presented.

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