Case-Based Planning with User Preferences for Web Service Composition

Case-Based Planning with User Preferences for Web Service Composition

Yamina Hachemi (Djillali Liabes University of Sidi Bel Abbes, Sidi Bel Abbes, Algeria) and Sidi Mohamed Benslimane (LabRi Laboratory, École Supérieure en Informatique, Sidi Bel Abbes, Algeria)
Copyright: © 2014 |Pages: 14
DOI: 10.4018/IJWP.2014100104
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Abstract

Web services composition has emerged as a solution to answer the requester's requirements. However, the selection of an appropriate Web service has become a difficult task due to the number of Web services present on the Web and mostly they offer similar functionalities. User preferences are a key factor that can be used to rank candidate services and retain only the best ones. To improve the process of web service composition the authors propose a Case-Based Planning (CBP) approach based on preferences which uses successful experiences in past to solve similar problems at present or/and in the future. How to make a choice base on non-functional factors becomes a problem that need to be solved. This paper, argues that the selection should be considered in a global manner based on the user's preferences. The authors present a framework that deals with web service composition based on user preferences and CBP method. Results obtained offer more than a solution to the user and taking both functional and non-functional requirements.
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Artificial Intelligence techniques can provide a solution to the problem of service composition. In particular, there have been several proposals using AI planning.

Case-based reasoning (CBR) (Aamodt & Plaza, 1994) is a problem solving methodology based on reutilizing specific knowledge of previously experienced and concrete problem situations (cases). Case-based planning is the application of the CBR methodology to planning, and as such, it is planning as remembering (Hammond, 1990).

Different approaches based on CBR and CBP have been proposed for the composition of Web services. In this section, we review selected works based on their relevance for our approach.

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