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Mediation spaces for similarity-based semantic web services selection

Dietze, Stefan; Gugliotta, Alessio; Domingue, John and Mrissa, Michael (2011). Mediation spaces for similarity-based semantic web services selection. International Journal of Web Services Research, 7(4)

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Semantic Web Services (SWS) aim at the automated discovery, selection and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. However, heterogeneities between distinct SWS representations pose strong limitations w.r.t. interoperability and reusability. Hence, semantic-level mediation, i.e. mediation between concurrent semantic representations of services, is a key requirement to allow SWS matchmaking algorithms to compare capabilities of distinct SWS. In that, semantic-level mediation requires to identify similarities across distinct SWS representations. Since current approaches to mediate between distinct service annotations rely either on manual one-to-one mappings or on semiautomatic mappings based on the exploitation of linguistic or structural similarities, these are perceived to be costly and error-prone. We propose a mediation approach enabling the implicit representation of similarities across distinct SWS by grounding these in so-called Mediation Spaces (MS). Given a set of SWS and their respective MS grounding, a general-purpose mediator automatically computes similarities to identify the most appropriate SWS for a given request. A prototypical application illustrates our approach.

Item Type: Journal Item
Copyright Holders: 2011 IGI Global
ISSN: 1546-5004
Keywords: web services; service discovery; semantic web services; semantic mediation; conceptual spaces; integration; interoperability
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 24375
Depositing User: Kay Dave
Date Deposited: 07 Dec 2010 09:39
Last Modified: 15 Jan 2019 06:08
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