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    Semantic service matchmaking for digital health ecosystems

    172088_172088.pdf (1011.Kb)
    Access Status
    Open access
    Authors
    Dong, Hai
    Hussain, Farookh Khadeer
    Date
    2011
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Dong, Hai and Hussain, Farookh Khadeer. 2011. Semantic service matchmaking for digital health ecosystems. Knowledge-Based Systems. 24 (6): pp. 761-774.
    Source Title
    Knowledge-Based Systems
    DOI
    10.1016/j.knosys.2011.02.005
    ISSN
    0950-7051
    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 Knowledge-Based Systems. 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 Knowledge-Based Systems, Vol.24, no.6 (August 2011). DOI: 10.1016/j.knosys.2011.02.005

    URI
    http://hdl.handle.net/20.500.11937/45588
    Collection
    • Curtin Research Publications
    Abstract

    The vision of Digital Ecosystems was initiated by the European Commission, with the purpose of constructing an information and communication technology environment to facilitate the sustainable development of small and medium enterprises. As a key subdomain of Digital Ecosystems, Digital Health Ecosystems provide crucial services to maintain the health of the main participants of Digital Ecosystems. We are concerned with the large-scale, ambiguous, heterogeneous, and untrustworthy health service information in Digital Health Ecosystems. An intensive survey found that current research cannot support accurate and trustworthy matchmaking between health service requests and health service advertisements in Digital Health Ecosystems. Therefore, in this paper, we propose a framework of a semantic service matchmaker, by taking into account the ambiguous, heterogeneous nature of service information in Digital Health Ecosystems. This framework is designed to make four major contributions, which are health service domain knowledge modeling, online health service information disambiguation, health service query disambiguation and health service quality evaluation and ranking. In order to thoroughly evaluate this framework, we implement a prototype – a Semantic Health Service Search Engine, and execute a series of experiments on the prototype using a functional testing and simulation approach.

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