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Mediation Spaces for Similarity-Based Semantic Web Services Selection

Mediation Spaces for Similarity-Based Semantic Web Services Selection

Stefan Dietze (The Open University, UK), Alessio Gugliotta (Innova Spa, Italy), John Domingue (The Open University, UK), and Michael Mrissa (Université de Lyon – CNRS, France)
Copyright: © 2011 |Volume: 8 |Issue: 1 |Pages: 20
ISSN: 1545-7362|EISSN: 1546-5004|EISBN13: 9781613509715|DOI: 10.4018/jwsr.2011010101
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MLA

Dietze, Stefan, et al. "Mediation Spaces for Similarity-Based Semantic Web Services Selection." IJWSR vol.8, no.1 2011: pp.1-20. https://doi.org/10.4018/jwsr.2011010101

APA

Dietze, S., Gugliotta, A., Domingue, J., & Mrissa, M. (2011). Mediation Spaces for Similarity-Based Semantic Web Services Selection. International Journal of Web Services Research (IJWSR), 8(1), 1-20. https://doi.org/10.4018/jwsr.2011010101

Chicago

Dietze, Stefan, et al. "Mediation Spaces for Similarity-Based Semantic Web Services Selection," International Journal of Web Services Research (IJWSR) 8, no.1: 1-20. https://doi.org/10.4018/jwsr.2011010101

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Abstract

Semantic Web Services (SWS) aim at the automated discovery, selection and orchestration of Web services based on comprehensive, machine-interpretable semantic descriptions. The latter are, in principle, deployed by multiple possible actors (i.e., service providers and service consumers); thus, a high level of heterogeneity between distinct SWS annotations is expected. Therefore, mediation between concurrent semantic representations of services is a key requirement to fully implement the SWS vision. In this paper, the authors argue that “semantic-level mediation” is necessary to identify semantic similarities across distinct SWS representations. The authors formalize and implement a mediation approach based on “Mediation Spaces” (MS), which enables the implicit representation of semantic similarities among distinct SWS descriptions. As a result, given a specific SWS approach and the proposed MS, a general purpose algorithm is implemented to empower SWS selection with the automatic computation of semantic similarities between a given SWS request and a set of SWS offers. A prototypical application illustrates the approach and highlights the benefits w.r.t. current mediation approaches.

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