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Context-aware semantic Web service discovery through metric-based situation representations

Dietze, Stefan; Domingue, John; Mrissa, Michael and Gugliotta, Alessio (2010). Context-aware semantic Web service discovery through metric-based situation representations. In: Sheng, Quan Z.; Yu, Jian and Dustdar, Schahram eds. Enabling Context-Aware Web Services: Methods, Architectures, and Technologies. Boca Raton, Florida, USA: Chapman and Hall/CRC, pp. 365–391.

DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1201/EBK1439809853-c13
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Abstract

Semantic Web Services (SWS) enable the automatic discovery of distributed Web services based on comprehensive semantic representations. However, although SWS technology supports the automatic allocation of Web services for a given well-defined task, it does not entail their discovery according to a given situational context. Whereas tasks are highly dependent on the situational context in which they occur, SWS technology does not explicitly encourage the representation of domain situations. Moreover, describing the complex notion of a specific situation in all its facets is a costly task and may never reach sufficient semantic expressiveness. Particularly, following the symbolic SWS approach leads to ambiguity issues and does not entail semantic meaningfulness. Apart from that, not any real-world situation completely equals another, but has to be matched to a finite set of semantically defined parameter descriptions to enable context-adaptability. To overcome these issues, we propose Conceptual Situation Spaces (CSS) that are aligned to established SWS standards. CSS enable the description of situation characteristics as members in geometrical vector spaces following the idea of Conceptual Spaces. Semantic similarity between situations is calculated in terms of their Euclidean distance within a CSS. Extending merely symbolic SWS descriptions with context information through CSS enables similarity-based matchmaking between real-world situation characteristics and predefined resource representations as part of SWS descriptions. To prove its feasibility, we apply our approach to the E-Learning and E-Business domains and provide a proof-of-concept prototype.

Item Type: Book Chapter
Copyright Holders: 2010 by Taylor and Francis Group, LLC
ISBN: 1-4398-0985-2, 978-1-4398-0985-3
Academic Unit/Department: Knowledge Media Institute
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 23016
Depositing User: Kay Dave
Date Deposited: 21 Sep 2010 11:39
Last Modified: 23 Oct 2012 14:29
URI: http://oro.open.ac.uk/id/eprint/23016
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