Open AccessImproving Semantic Web Services Composition Performance, Using Data Mining Techniques
Author(s) -
Shahab Bayati,
Ardeshir Bahreininejad,
Ali Farahmand Nejad,
Ssdegh Kharazmi
Publication year - 2010
Publication title -
journal of algorithms and computational technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.234
H-Index - 13
eISSN - 1748-3026
pISSN - 1748-3018
DOI - 10.1260/1748-3018.4.4.409
Subject(s) - web service , computer science , world wide web , ws policy , data web , web standards , web modeling , web intelligence , services computing , web mining , social semantic web , semantic web stack , semantic web , ws i basic profile , composition (language) , web development , web application security , linguistics , philosophy
There are many usages for the Web services in the World Wide Web. For creating new services we can compose other developed services in the way we want to use them. The large amount of Web services make composing of services a time consuming and impossible job. So to compose services some automated and semi-automated ways were developed. One of these ways is semantic Web services (SWS). In this paper we propose a method based on data mining techniques on Web services to find the best composition among possible compositions to improve quality and performance of Web service composition. Association rules, Classification and clustering are used as data mining approach to improve performance of the Web Service Composition