14 research outputs found

    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

    Modélisation thématique probabiliste des services web

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    Les travaux sur la gestion des services web utilisent généralement des techniques du domaine de la recherche d'information, de l'extraction de données et de l'analyse linguistique. Alternativement, nous assistons à l'émergence de la modélisation thématique probabiliste utilisée initialement pour l'extraction de thèmes d'un corpus de documents. La contribution de cette thèse se situe à la frontière de la modélisation thématique et des services web. L'objectif principal de cette thèse est d'étudier et de proposer des algorithmes probabilistes pour modéliser la structure thématique des services web. Dans un premier temps, nous considérons une approche non supervisée pour répondre à différentes tâches telles que la découverte et le regroupement de services web. Ensuite, nous combinons la modélisation thématique avec l'analyse de concepts formels pour proposer une méthode de regroupement hiérarchique de services web. Cette méthode permet une nouvelle démarche de découverte interactive basée sur des opérateurs de généralisation et spécialisation des résultats obtenus. Enfin, nous proposons une méthode semi-supervisée pour l'annotation automatique de services web. Nous avons concrétisé nos propositions par un moteur de recherche en ligne appelé WS-Portal. Nous offrons alors différentes fonctions facilitant la gestion de services web, par exemple, la découverte et le regroupement de services web, la recommandation des tags, la surveillance des services, etc. Nous intégrons aussi différents paramètres tels que la disponibilité et la réputation de services web et plus généralement la qualité de service pour améliorer leur classement (la pertinence du résultat de recherche).The works on web services management use generally the techniques of information retrieval, data mining and the linguistic analysis. Alternately, we attend the emergence of the probabilistic topic models originally developed and utilized for topics extraction and documents modeling. The contribution of this thesis meets the topics modeling and the web services management. The principal objective of this thesis is to study and propose probabilistic algorithms to model the thematic structure of web services. First, we consider an unsupervised approach to meet different tasks such as web services clustering and discovery. Then we combine the topics modeling with the formal concept analysis to propose a novel method for web services hierarchical clustering. This method allows a novel interactive discovery approach based on the specialization and generalization operators of retrieved results. Finally, we propose a semi-supervised method for automatic web service annotation (automatic tagging). We concretized our proposals by developing an on-line web services search engine called WS-Portal where we incorporate our research works to facilitate web service discovery task. Our WS-Portal contains 7063 providers, 115 sub-classes of category and 22236 web services crawled from the Internet. In WS- Portal, several technologies, i.e., web services clustering, tags recommendation, services rating and monitoring are employed to improve the effectiveness of web services discovery. We also integrate various parameters such as availability and reputation of web services and more generally the quality of service to improve their ranking and therefore the relevance of the search result

    Découverte et recommandation de services web basées sur l'extraction d'information et la réputation symbolique

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    International audienceCet article montre que le problème de représentation de services web est crucial et analyse les différents facteurs qui l’influencent. Il discute une représentation classique et en propose deux nouvelles. La première représentation que nous proposons provient du domaine du traitement du langage naturel et est basée sur des règles pour annoter les descriptions de services et ainsi extraire les informations utiles pour l’indexation sémantique de services. La seconde méthode proposée, appelée réputation symbolique, est calculée à partir des relations entre les services considérés et est utilisée pour la recommandation de services web. L’impact de ces représentations pour la découverte et la recommandation est étudié et discuté à la lumière de nos expérimentations utilisant des services web réels

    Semantic Divergence based Evaluation of Web Service Communities

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    International audienceThe number of community detection algorithms is growing continuously adopting a topological based approach to discover optimal subgraphs or communities. In this paper, we propose a new method combining both topology and semantic to evaluate and rank community detection algorithms. To achieve this goal we consider a probabilistic topic based approach to define a new measure called semantic divergence of communities. Combining this measure with others related to prior knowledge, we compute a score for each algorithm to evaluate the effectiveness of its communities and propose a ranking method. We have evaluated our approach considering communities of real web services

    Multiple Representations of Web Services: Discovery, Clustering and Recommendation

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    International audienceThis paper analyses several web services representations based on web services descriptions and more generally on the content of WSDL files. We introduce also a new representation called symbolic reputation which is computed from relationships between web services. Different implementation issues are discussed and the results considering real world web services are analysed to determine the usefulness of the introduced representations for three main tasks: web services discovery, clustering and recommendation

    Représentation de services web : impact sur la découverte et la recommandation

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    National audienceLes descriptions utilisées par les services web sont en langage naturel, multilingues et inter-domaines. Générer des représentations de services web est donc un défi majeur. Cet article présente une représentation classique et en propose deux nouvelles. L’impact de ces représentations pour la découverte et la recommandation est étudié et discuté à la lumière de nos expérimentations utilisant des services web réels

    Probabilistic Approach for Diversifying Web Services Discovery and Composition

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    International audienceDue to the increasing number of available web services, discovering the best service that matches a user requirement is still a challenge. In most cases the discovery system returns a set of very similar services and sometimes it is unable to find results for some complex queries. Therefore, integrating web service discovery and composition, taking into account the diversity of discovered results, in a unified way is still a big issue for web services. In this paper, we propose a novel service ranking algorithm for diversifying web services discovery results in order to minimize the redundancy in the search results. This algorithm chooses a set of selected web services based on relevancy, service diversity and service density. We also propose a new method to generate service dependency network using the Formal Concept Analysis (FCA) framework. The generated graph is used to select the composition of discovered web services set. Experimental results show that our method performs better than others baseline approaches

    Représentation de services web : impact sur la découverte et la recommandation

    No full text
    National audienceLes descriptions utilisées par les services web sont en langage naturel, multilingues et inter-domaines. Générer des représentations de services web est donc un défi majeur. Cet article présente une représentation classique et en propose deux nouvelles. L’impact de ces représentations pour la découverte et la recommandation est étudié et discuté à la lumière de nos expérimentations utilisant des services web réels

    Probabilistic Approach for Diversifying Web Services Discovery and Composition

    No full text
    International audienceDue to the increasing number of available web services, discovering the best service that matches a user requirement is still a challenge. In most cases the discovery system returns a set of very similar services and sometimes it is unable to find results for some complex queries. Therefore, integrating web service discovery and composition, taking into account the diversity of discovered results, in a unified way is still a big issue for web services. In this paper, we propose a novel service ranking algorithm for diversifying web services discovery results in order to minimize the redundancy in the search results. This algorithm chooses a set of selected web services based on relevancy, service diversity and service density. We also propose a new method to generate service dependency network using the Formal Concept Analysis (FCA) framework. The generated graph is used to select the composition of discovered web services set. Experimental results show that our method performs better than others baseline approaches
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