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Semantic Resource Matching for Pervasive Environments: The Approach and its Evaluation

Semantic Resource Matching for Pervasive Environments: The Approach and its Evaluation
Semantic Resource Matching for Pervasive Environments: The Approach and its Evaluation
Technological advancements in the past decade have caused a large increase in the number and diversity of electronic devices that have appeared in the home and office and these devices offer an increasingly heterogeneous range of services. This has introduced new challenges for the dynamic discovery of services in pervasive environments. Several discovery mechanisms currently exist such as Salutation, SLP etc. to support service discovery in the device domain. However, these approaches characterise the services either by using predefined service categories and fixed attribute value pairs. Such descriptions are inflexible and difficult to extend to new concepts and characteristics, and since these descriptions do not describe devices or services at a conceptual level, no form of inferencing can be carried out on them. Hence the matching techniques in these approaches are limited to syntactic comparisons based on attributes or interfaces. More recently with the popularity of Semantic Web technologies, there has been an increased interest in the use of ontologies for service descriptions and the application of reasoning mechanisms to support discovery and matching. In this document, we present a semantic matching framework to facilitate effective discovery of device based services in pervasive environments. This offers a ranking mechanism that will order the available services in the order of their suitability; the evaluation of the experimental results have indicated that the results correlate well with human perception.
Semantic Web, Service Matching, Pervasive Computing
s.n.
Bandara, Ayomi
6216d014-bb57-49eb-9666-83c0a75e66ca
Payne, Terry
0bb13d45-2735-45a3-b72c-472fddbd0bb4
Roure, David De
02879140-3508-4db9-a7f4-d114421375da
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Lewis, Tim
b5bf4710-4588-4567-bc7c-18a476f04673
Bandara, Ayomi
6216d014-bb57-49eb-9666-83c0a75e66ca
Payne, Terry
0bb13d45-2735-45a3-b72c-472fddbd0bb4
Roure, David De
02879140-3508-4db9-a7f4-d114421375da
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Lewis, Tim
b5bf4710-4588-4567-bc7c-18a476f04673

Bandara, Ayomi, Payne, Terry, Roure, David De, Gibbins, Nicholas and Lewis, Tim (2008) Semantic Resource Matching for Pervasive Environments: The Approach and its Evaluation s.n. (In Press)

Record type: Monograph (Project Report)

Abstract

Technological advancements in the past decade have caused a large increase in the number and diversity of electronic devices that have appeared in the home and office and these devices offer an increasingly heterogeneous range of services. This has introduced new challenges for the dynamic discovery of services in pervasive environments. Several discovery mechanisms currently exist such as Salutation, SLP etc. to support service discovery in the device domain. However, these approaches characterise the services either by using predefined service categories and fixed attribute value pairs. Such descriptions are inflexible and difficult to extend to new concepts and characteristics, and since these descriptions do not describe devices or services at a conceptual level, no form of inferencing can be carried out on them. Hence the matching techniques in these approaches are limited to syntactic comparisons based on attributes or interfaces. More recently with the popularity of Semantic Web technologies, there has been an increased interest in the use of ontologies for service descriptions and the application of reasoning mechanisms to support discovery and matching. In this document, we present a semantic matching framework to facilitate effective discovery of device based services in pervasive environments. This offers a ranking mechanism that will order the available services in the order of their suitability; the evaluation of the experimental results have indicated that the results correlate well with human perception.

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More information

Accepted/In Press date: 28 February 2008
Keywords: Semantic Web, Service Matching, Pervasive Computing
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 265223
URI: https://eprints.soton.ac.uk/id/eprint/265223
PURE UUID: 767160be-10b3-43fb-b85d-1002a30715f6
ORCID for David De Roure: ORCID iD orcid.org/0000-0001-9074-3016
ORCID for Nicholas Gibbins: ORCID iD orcid.org/0000-0002-6140-9956

Catalogue record

Date deposited: 29 Feb 2008 06:07
Last modified: 06 Jun 2018 13:20

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