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dc.contributor.authorDong, Hai
dc.contributor.authorHussain, Farookh Khadeer
dc.identifier.citationDong, Hai and Hussain, Farookh Khadeer. 2011. Semantic service matchmaking for digital health ecosystems. Knowledge-Based Systems. 24 (6): pp. 761-774.

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.

dc.publisherElsevier BV
dc.subjectDigital Ecosystems
dc.subjectsemantic service matchmaking
dc.subjectDigital Health Ecosystems
dc.subjectsemantic search
dc.titleSemantic service matchmaking for digital health ecosystems
dc.typeJournal Article
dcterms.source.titleKnowledge-Based Systems

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

curtin.departmentDigital Ecosystems and Business Intelligence Institute (DEBII)
curtin.accessStatusOpen access

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