L’apprentissage à base de cas pour la composition des services web

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2016-01-21
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Résumé (Français et/ou Anglais) : Distributed applications converge quickly towards the adoption of a paradigm based on service-oriented architectures (SOA), in which an application is obtained by the composition of a set of services. Web service selection is an indispensable process for web service composition. However, it became a difficult task as many web services are increased on the web and mostly they offer similar functionalities, which service will be the best. User preferences are the key to select and retain only the best services for the composition. In this work, we have proposed a web service composition model based on user preferences. To improve the process of web service composition we propose to combine two techniques of artificial intelligence that are planning and reasoning by memorization. In this work, we use the case-based planning approach with user preferences, which uses successful experiences of the past to solve similar problems. In our approach we integrate user preferences in the phase of selection, adaptation and planning. Our main contributions are a new method of case retrieval, an extended algorithm of adaptation and planning with user preferences. Results obtained offer more than a solution to the user and taking both functional and non-functional requirements.
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Doctorat en Sciences
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