A scholarly semantic web system for advanced search functions

Tho, Q.T., Fong, A.C.M. and Hui, S.C. (2007) A scholarly semantic web system for advanced search functions. Online Information Review, 31(3), pp. 353-364. (doi: 10.1108/14684520710764113)

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Abstract

Purpose – The semantic web gives meaning to information so that humans and computers can work together better. Ontology is used to represent knowledge on the semantic web. Web services have been introduced to make the knowledge conveyed by the ontology on the semantic web accessible across different applications. This paper seeks to present the use of these latest advances in the context of a scholarly semantic web (or SSWeb) system, which can support advanced search functions such as expert finding and trend detection in addition to basic functions such as document and author search as well as document and author clustering search.<p></p> Design/methodology/approach – A distributed architecture of the proposed SSWeb is described, as well as semantic web services that support scholarly information retrieval on the SSWeb.<p></p> Findings – Initial experimental results indicate that the proposed method is effective.<p></p> Research limitations/implications – The work reported is experimental in nature. More work is needed, but early results are encouraging and the authors wish to make their work known to the research community by publishing this paper so that further progress can be made in this area of research.<p></p> Originality/value – The work is presented in the context of scholarly document retrieval, but it could also be adapted to other types of documents, such as medical records, machine-fault records and legal documents. This is because the basic principles are the same.<p></p>

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Fong, Dr Alvis Cheuk Min
Authors: Tho, Q.T., Fong, A.C.M., and Hui, S.C.
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Online Information Review
ISSN:1468-4527
ISSN (Online):1468-4535

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