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    A framework for discovering and classifying ubiquitous services in digital health ecosystems

    185267_185267.pdf (546.8Kb)
    Access Status
    Open access
    Authors
    Dong, Hai
    Hussain, Farookh Khadeer
    Chang, Elizabeth
    Date
    2011
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Dong, Hai and Hussain, Farookh Khadeer and Chang, Elizabeth. 2011. A framework for discovering and classifying ubiquitous services in digital health ecosystems. Journal of Computer and System Sciences. 77 (4): pp. 687-704.
    Source Title
    Journal of Computer and System Sciences
    DOI
    10.1016/j.jcss.2010.02.009
    ISSN
    0022-0000
    School
    Digital Ecosystems and Business Intelligence Institute (DEBII)
    Remarks

    NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Computer and System Sciences. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Computer and System Sciences, Vol. 77, No. 4 (2011). DOI: 10.1016/j.jcss.2010.02.009

    URI
    http://hdl.handle.net/20.500.11937/45725
    Collection
    • Curtin Research Publications
    Abstract

    A digital ecosystem is a widespread type of ubiquitous computing environment comprised of ubiquitous, geographically dispersed, and heterogeneous species, technologies and services. As a subdomain of the digital ecosystems, digital health ecosystems are crucial for the stability and sustainable development of the digital ecosystems. However, since the service information in the digital health ecosystems exhibits the same features as those in the digital ecosystems, it is difficult for a service consumer to precisely and quickly retrieve a service provider for a given health service request. Consequently, it is a matter of urgency that a technology is developed to discover and classify the health service information obtained from the digital health ecosystems. A survey of state-of-the-art semantic service discovery technologies reveals that no significant research effort has been made in this area. Hence, in this paper, we present a framework for discovering and classifying the vast amount of service information present in the digital health ecosystems. The framework incorporates the technology of semantic focused crawler and social classification. A series of experiments are conducted in order to respectively evaluate the framework and the employed mathematical model.

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