The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component-based software development to promote application interaction and integration within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web services repositories not only be well-structured but also provide efficient tools for an environment supporting reusable software components for both service providers and consumers. As the potential of Web services for service-oriented computing is becoming widely recognized, the demand for an integrated framework that facilitates service discovery and publishing is concomitantly growing.In our research, we propose a framework that facilitates Web service discovery and publishing by combining clustering techniques and leveraging the semantics of the XML-based service specification in WSDL files. We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the Web service domain. Our proposed approach has several appealing features: (1) It minimizes the requirements of prior knowledge from both service providers and consumers, (2) It avoids exploiting domain-dependent ontologies,(3) It is able to visualize the information space of Web services by providing a category map that depicts the semantic relationships among them,(4) It is able to semi-automatically generate Web service taxonomies that reflect both capability and geographic context, and(5) It allows service consumers to combine multiple search strategies in a flexible manner.We have developed a Web service discovery tool based on the proposed approach using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web services repositories. We believe that both service providers and consumers in a service-oriented computing environment can benefit from our Web service discovery approach.

Service-oriented Architecture is now an important issue when it comes to program development. However, there is not yet an efficient and effective way for developer to obtain appropriate component. Current researches mostly focus on either textual meaning or ontology relation of the services. In this research we propose a hybrid approach that integrates both types of information. It starts by defining important attributes and their weights for web service discovery using Multiple Criteria Decision Making. Then a method of similarity calculation based on both textual and ontological information is applied. In the experiment, we collect 103 real-world Web services, and the experimental results show that our approach generally performs better than the existing ones.

This thesis, studies automated methods to achieve web service advertisement and discovery, and presents efficient search and matching techniques based on OWL-S. In the proposed system, the service discovery and matchmaking is performed via a centralized peer-to-peer web service repository. The repository has the ability to run on a software cloud, which improves the availability and scalability of the service discovery. The service advertisement is done semi-automatically on the client side, with an automatic WSDL to OWL-S conversion, and manual service description annotation. An OWL-S based unified ontology -Suggested Upper Merged Ontology- is used during annotation, to enhance semantic matching abilities of the system. The service advertisement and availability are continuously monitored on the client side to improve the accuracy of the query results. User-agents generate query specification using the system ontology, to provide semantic unification between the client and the system during service discovery. Query matching is performed via complex Hilbert Spaces composed of conceptual planes and categorical similarities for each web service. User preferences following the service queries are monitored and used to improve the service match scores in the long run.

Grids are collaborative distributed Internet systems characterized by large scale, heterogeneity, lack of central control, multiple autonomous administrative domains, unreliable components and frequent dynamic change. In such systems, it is desirable to maintain and query dynamic and timely information about active participants such as services, resources and user communities. The web services vision promises that programs are made more flexible, adaptive and powerful by querying Internet databases (registries) at runtime in order to discover information and network attached building blocks, enabling the assembly of distributed higher-level components. In support of this vision, we introduce the Web Service Discovery Architecture (WSDA), we introduce the hyper registry, which is a centralized database node for discovery of dynamic distributed content. It supports XQueries over a tuple set from a dynamic XML data model.

With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.

The Web turns out to be a collection of services that interoperate through the Internet. As the number of services increase, it is getting more and more diffucult for users to find, filter and integrate these services depending on their requirements. Automatic techniques are being developed to fulfill these tasks. The first step toward automatic composition is the discovery of services needed. UDDI which is one of the accepted web standards, provides a registry of web services. However representation capabilities of UDDI are insufficient to search for services on the basis of what they provide. Semantic web initiatives like OWL and OWL-S are promising for locating exact services based on their capabilities. In this thesis, a new semantic service discovery mechanism is implemented based on OWL-S service profiles. The service profiles of an advertisement and a request are matched based on OWL ontologies describing them. In contrast to previous work on the subject, the ontologies of the advertisement and the request are not assumed to be same. In case they are different, schema matching algorithms are applied. Schema matching algorithms find the mappings between the given schema models. A hybrid combination of semantic, syntactic and structural schema matching algorithms are applied to match ontologies

Web Service technology is one of the most rapidly developing contemporary technologies. Nowadays, Web Services are being used by a large number of projects and academic studies all over the world. As the use of Web service technology is increasing, it becomes harder to find the most suitable web service which meets the Quality of Service (QoS) as well as functional requirements of the user. In addition, quality of the web services (QoS) that take part in the software system becomes very important. In this thesis, we develop a method to track the QoS primitives of Web Services and an algorithm to automatically calculate QoS values for Web Services. The proposed method is realized within a domain specific web service discovery system, namely DSWSD-S, Domain Specific Web Service Discovery with Semantics. This system searches the Internet and finds web services that are related to a domain and calculates QoS values through some parameters. When a web service is queried, our system returns suitable web services with their QoS values. How to calculate, keep track of and store QoS values constitute the main part of this study.

In this thesis, we present a hybrid semantic web service discovery framework that exploits both the signatures and specifications of a web service, whilst adopting logical and non-logical service matching methods. For signature level service matching, we have developed two techniques: (i) logical similarity measures applied to the services’ input/output concepts; and (b) non-logical matching based on a Structure Preserving Semantic Matching algorithm. For specification level service matching, we have applied a unique short sentence matching approach on the textual-description of a web service. We evaluated the performance of our S5 Web Service Matchmaker using the OWLS-TC dataset, and furthermore compared its performance with the OWLS-MX discovery model. Our results indicate that S5 Web Service Matchmaker offers an improved web service matching performance with a significant increase in recall and subtle improvements in precision. / Web services are independent software systems designed to offer machine-to-machine interactions over the WWW to achieve well-described operations. The description of a web service entails (a) a syntactic component detailing the service’s operations and data structures in terms of the Web Services Description Language (WSDL), and (b) a semantic component that offers a semantic description, in terms of an ontology, of the services’ data and operations. Typically, service providers expose their services to the public by providing brief descriptions of the service’s operations; the challenge is to discover the right service based on rather sparse service descriptions in response to a specific service request. In this thesis, we present a hybrid semantic web service discovery framework that offer semantic web service discovery at both the signature and specification levels of a web service, whilst exploiting logical and non-logical service matching methods. For signature level service matching, we have developed two techniques: (i) logical similarity measures applied to the services’ input/output concepts; and (b) non-logical matching based on a Structure Preserving Semantic Matching algorithm. For specification level service matching, we have applied a unique short sentence matching approach on the textual-description of a web service. The cumulative similarly measures determine the overall similarity of a services’ description with the service request. We evaluated the performance of our S5 Web Service Matchmaker using the OWLS-TC dataset, and furthermore compared its performance with the OWLS-MX discovery model. Our results indicate that S5 Web Service Matchmaker offers an improved web service matching performance with a significant increase in recall and subtle improvements in precision.

Les travaux de recherche menés autour de la description de services Web utilisent de plus en plus des modèles sémantiques pour fournir une représentation interprétable automatiquement. Toutefois, nous avons décelé des lacunes dans les approches sémantiques actuelles qui engendrent ambiguïté et non pertinence au niveau de l’appariement et de la découverte de services Web. Pour remédier à ces lacunes nous proposons des contributions à la description et à la découverte de services Web sémantiques. En ce qui concerne la description de services, nous avons défini un langage basé sur une recommandation W3C. En plus d’une annotation métier sémantique des éléments d’un service, notre principale contribution à la description sémantique consiste à spécifier la nature de ces annotations en utilisant une ontologie technique que nous avons définie. Cette ontologie met en relation plusieurs concepts sémantiques de services Web que nous avons identifiés dans des approches existantes et intègrera d’autres concepts qu’on définira ultérieurement sans pour autant modifier notre langage de description ou nos techniques d’appariement associées. Nous avons également défini un algorithme d’appariement entre une requête de service et les descriptions des services publiés. Cet algorithme se base sur un appariement entre éléments d’une requête et un service publié et trois techniques d’agrégation des résultats d’appariements élémentaires. L’algorithme tire avantage de la description sémantique que nous avons définie. Il a été mis en œuvre dans un annuaire de services Web sémantiques et a été également comparé aux algorithmes de référence. Les expérimentations montrent clairement l’efficacité de notre approche en termes de temps de réponse et de précision / Researches conducted around Web service description use more and more of semantic models to provide an automatically interpretable representation. However, we identified gaps in current approaches that generate semantic ambiguity and impertinence at Web service matching and discovery. To address these shortcomings we propose contributions about semantic Web service description and discovery. As for the Web services description, we have defined a language based on a W3C Recommendation. In addition to a semantic business annotation of service components, our main contribution about the semantic description is to specify the nature of these annotations using a technical ontology that we have defined. This ontology merges several semantic concepts of web services that we identified in existing approaches and may include other concepts that can be defined later without changing our description language or our matching techniques. We also defined a matching algorithm between a service request and published service descriptions. This algorithm is based on matching between elements of a service request and descriptions of published services. This matching is may be computed by three aggregation techniques of the results of those elements’ matching. The algorithm takes advantage of the semantic description we have defined. It was implemented in a semantic web services registry and was also compared to referenced algorithms. The experiments clearly demonstrate the effectiveness of our approach in terms of response time and precision

In this thesis, a semantically aided web service and restful service search mechanism is presented that makes use of an ontology. The mechanism relates method names, input and output parameters for ontology guided matches and offers results with varying relevance corresponding to the matching degree. The mechanism is demonstrated using an experimental domain that is tourism and travel. An ontology is created to support a set of web services that exist in this domain.