340 research outputs found

    Web Service Discovery Based on Past User Experience

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    Web service technology provides a way for simplifying interoperability among different organizations. A piece of functionality available as a web service can be involved in a new business process. Given the steadily growing number of available web services, it is hard for developers to find services appropriate for their needs. The main research efforts in this area are oriented on developing a mechanism for semantic web service description and matching. In this paper, we present an alternative approach for supporting users in web service discovery. Our system implements the implicit culture approach for recommending web services to developers based on the history of decisions made by other developers with similar needs. We explain the main ideas underlying our approach and report on experimental results

    QoS based Effective and Efficient Selection of Web Service and Retrieval of Search Information

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    Web services are integrated software components for the support of interoperable machine to machine interaction over a network. Web services have been widely employed for building service-oriented applications in both industry and academia in recent years. The number of publicly available Web services is steadily increasing on the Internet. However, this proliferation makes it hard for a user to select a proper Web service among a large amount of service candidates. An inappropriate service selection may cause many problems to the resulting applications. In this paper, a novel collaborative filtering-based Web service recommender system is proposed to help the users and select services with optimal QoS performance. Our recommender system employ an effective and efficient selection of web services and relevant retrieval of information and makes personalized service recommendation to users based on the clustering results. Compared with existing service recommendation methods, the proposed approach achieves considerable improvement on the recommendation accuracy and the QoS performance metrics adopted in this paper shows the better accuracy and relevant web services

    Web Services Discovery and Recommendation Based on Information Extraction and Symbolic Reputation

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    This paper shows that the problem of web services representation is crucial and analyzes the various factors that influence on it. It presents the traditional representation of web services considering traditional textual descriptions based on the information contained in WSDL files. Unfortunately, textual web services descriptions are dirty and need significant cleaning to keep only useful information. To deal with this problem, we introduce rules based text tagging method, which allows filtering web service description to keep only significant information. A new representation based on such filtered data is then introduced. Many web services have empty descriptions. Also, we consider web services representations based on the WSDL file structure (types, attributes, etc.). Alternatively, we introduce a new representation called symbolic reputation, which is computed from relationships between web services. The impact of the use of these representations on web service discovery and recommendation is studied and discussed in the experimentation using real world web services

    Reputation Revision Method for Selecting Cloud Services Based on Prior Knowledge and a Market Mechanism

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    The trust levels of cloud services should be evaluated to ensure their reliability. The effectiveness of these evaluations has major effects on user satisfaction, which is increasingly important. However, it is difficult to provide objective evaluations in open and dynamic environments because of the possibilities of malicious evaluations, individual preferences, and intentional praise. In this study, we propose a novel unfair rating filtering method for a reputation revision system. This method uses prior knowledge as the basis of similarity when calculating the average rating, which facilitates the recognition and filtering of unfair ratings. In addition, the overall performance is increased by a market mechanism that allows users and service providers to adjust their choice of services and service configuration in a timely manner. The experimental results showed that this method filtered unfair ratings in an effective manner, which greatly improved the precision of the reputation revision system

    Orchestration de web services fiables

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    L’Informatique Orienté Services représente un paradigme pour construire des applications distribuées sur Internet. L’Architecture Orientée Services(SOA) est un style architectural qui permet le développement de ces applications à base de services. Au cours de la dernière décennie, l’orchestration des services Web est devenue un domaine très actif dans la recherche scientifique et académique. Bien que de nombreux défis liés à l’orchestration aient été abordés, la fiabilité de l’orchestration et de sa vérification restent encore un sujet ouvert, prérequis et important de fait que ces orchestrations affectent aujourd’hui plusieurs activités quotidiennes. Cette thèse focalise sur le sujet d’orchestration des Services Web Fiables. En particulier, elle contribue avec un ensemble d’approches, de techniques et d’outils pour améliorer la sélection et l’orchestration des services web fiables. Premièrement, elle affine les phases du cycle de vie d’orchestration de services web afin d’assurer une vérification continuée de fiabilité lors des phases de conception et d’exécution. En outre, elle propose une architecture conceptuelle basée sur un registre de service amélioré, pour la mise en œuvre d’orchestrations fiables. Deuxièmement, elle présente une approche de mesure de similarité entre les services web. L’approche repose sur la comparaison des interfaces WSDL de services. L’approche sert à identifier les relations de similarité, de substituabilité et de composabilité entre services. L’outil WSSIM a été développé pour mettre en œuvre l’approche proposée. Pour validation, l’outil a été expérimenté avec un ensemble important de services web réels. Troisièmement, la thèse contribue avec une approche pour l’identification des substituts de services simples et complexes. L’approche utilise les techniques de mesure de similarité, la classification de service avec FCA et l’analyse de fiabilité pour identifier et sélectionner les meilleures substitutes. Un ensemble d’algorithmes aient été proposés pour décrire le processus d’identification. Quatrièmement, pour examiner la réputation des services comme un autre critère de fiabilité, la thèse introduit un Framework et un modèle mathématique pour la gestion de réputation de service We
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