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Article
Publication date: 6 April 2010

Ayomi Bandara, Terry Payne, David De Roure, Nicholas Gibbins and Tim Lewis

There has been an increased interest in the use of semantic description and matching techniques, to support service discovery and to overcome the limitations in the…

Abstract

Purpose

There has been an increased interest in the use of semantic description and matching techniques, to support service discovery and to overcome the limitations in the traditional syntactic approaches. However, the existing semantic matching approaches lack certain desirable properties that must be present in an effective solution to support service discovery. The purpose of this paper is to present a solution to facilitate the effective semantic matching of resource requests and advertisements in pervasive environments.

Design/methodology/approach

The paper presents a semantic description and matching approach to facilitate resource discovery in pervasive environments; the approach includes a ranking mechanism that orders services according to their suitability and also considers priorities placed on individual requirements in a request.

Findings

The solution has been evaluated for its effectiveness and the results have shown that the matcher results agree reasonably well with human judgement. The solution was also evaluated for its efficiency/scalability and from the experimental results obtained, it can be observed that for most practical situations, matching time can be considered acceptable for reasonable numbers of advertisements and request sizes.

Originality/value

The proposed approach improves existing semantic matching solutions in several key aspects. Specifically; it presents an effective approximate matching and ranking criterion and incorporates priority consideration in the matching process. As shown in the evaluation experiments, these features significantly improve the effectiveness of semantic matching.

Details

International Journal of Pervasive Computing and Communications, vol. 6 no. 1
Type: Research Article
ISSN: 1742-7371

Keywords

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