A novel semantic approach for Web service discovery using computational linguistics techniques

Background/Objectives: This article proposes a novel methodology based on rubrics and feature-based schemes for the appraisal and comparison of approaches to semantic Web services composition and discovery. Methods/Statistical analysis: In order to evaluate the Semantic Web services composition and discovery approaches we created a new framework called RFSWS. This framework is the combination of traditional feature-based evaluation schemes and newly developed analytic rubrics tables. Five recently introduced prominent Semantic Web services composition approaches were identified, explained, and then evaluated/compared using RFSWS. Findings: In this work we determined aspects of Semantic Web services composition and discovery processes that can be evaluated as performance criteria in rubric tables. This is a novel application of rubrics, which have traditionally been used for grading student performance by teachers. We created a novel framework called RFSWS consisting of rubric tables and a feature-based evaluation scheme for the evaluation and comparison of Semantic Web service discovery and composition approaches, and applied it in the evaluation of five recently introduced prominent Semantic Web services composition approaches. Considering the shortcomings of existing Semantic Web services composition approaches that were discovered through this evaluation, we proposed an idealized dynamic Semantic Web service discovery and composition method, a yardstick by which all future Semantic Web services composition approaches can be evaluated. Application/ Improvements: Our novel RFSWS framework can be applied in the comprehensive and systematic evaluation/comparison of Semantic Web services discovery and composition approaches.

Automated matching of service descriptions is the key to service discovery and composition. In this paper, we propose an approach for web services discovery and composition. The approach relies on (1) SAWSDL, a simple and generic annotation language, (2) an XML representation of a web service that carries both syntactic (e.g., WSDL) and semantic (e.g., SAWSDL) information, and (3) the reuse of available schema matchers. The approach departs from exiting ones because it does not advocate a specific matchmaking algorithm, and it promotes the combination of different schema matchers, allowing multiple discovery and composition strategies.

Efficiently finding Web Services on the Web is a challenge research question in Service Oriented Architecture-SOA. Web services are becoming necessary part of the Semantic Web, and research on Semantic Web Services aims to automate their use. However, finding the adequate service for each individual user becomes a more and more demanding problem. In this paper we suggest a new approach for Web Service Discovery which we believe that is the first attempts that combines clustring techiques with Latent Semantic Indexing. Empirically the proposed method will improve the quality of automated service discovery.

Web services are meaningful only if potential users may find and execute them. Universal description discovery and integration (UDDI) help businesses, organizations, and other web services providers to discover and reach to the service(s) by providing the URI of the WSDL file. However, it does not offer a mechanism to choose a web service based on its quality. The standard also lacks sufficient semantic description in the content of web services. This lack makes it difficult to find and compose suitable web services during analysis, search, and matching processes. In addition, a central UDDI suffers from one centralized point problem and the high cost of maintenance. To get around these problems, the authors propose in this chapter a novel framework based on mobile agent and metadata catalogue for web services discovery. Their approach is based on user profile in order to discover appropriate web services, meeting customer requirements in less time and taking into account the QoS properties.

Service-orientation for the development of complex distributed systems with reusable components (services) has proved to be highly beneficial approach in software engineering. In order to realize its advantages automated techniques and tools for finding services, selecting the ones that match requestor needs, composing them for achieving enhanced functionality and resolving heterogeneity issues are required. Adding semantics to web services has become the key approach for the automation of service-orientation environments. Current paper proposes semantic approach for service selection and integration. It considers the semantic description of web services and involves reasoning on a knowledge base. The proposed approach for web service discovery and integration is based on designing logic based techniques for matching goal description with the semantic annotation of web services. It provides for the automation of web service search which facilitates the design of practical applications in service-oriented environment.

Web services are becoming an important enabler of the semantic Web. Besides the need for a rich description mechanism, Web service information should be made available in an accessible way for machine processing. In this paper, we propose a new P2P based approach for Web services discovery. Peers that store Web services information, such as data item descriptions, are efficiently located using a scalable and robust data indexing structure for peer-to-peer data networks, NIPPERS. We present a theoretical analysis which shows that the communication cost of the query and update operations scale double-logarithmically with the number of NIPPERS nodes. Furthermore, we show that the network is robust with respect to failures fulfilling quality of Web services requirements.

The main objective of today's companies is to cope with rapid changes in the environment. For this, they must ensure the integration and interoperability of their applications. To manage and automate the life cycle of these applications, companies are adopting web services technology. The current problem is that the content of these web services cannot be processed automatically. Only humans can interpret its contents. The semantic web is a new vision of the web that promises to overcome this difficulty. The goal of this technology is to automate the retrieval, assembly, and selection of web services. In this post, we are interested in semantic detection of web services. The main problem is automatically discovering web services on request from clients. Against this background, we first describe the principle of the proposed detection mechanism and then present the designed matchmaking algorithm. Finally, we implement our proposed method. To verify our work, we run tests against various user requests and web service panels. As part of a case study, we consider an online hospital problem. This problem is a typical web service discovery scenario to which the concepts of our method are applied.

Proliferation of web services opens an unleashed opportunity to the service providers compete themselves to satisfy a request. Since numerous functionally similar web services are readily available, identifying pertinent web service to the client's requirement is a challenge. Furthermore, recommending the pertinent web service and not missing the relevant web service are the two complex issues to be addressed in service discovery process. Since the keyword search doesn't bear the underlying semantics and unable to articulate the search query accurately, operation based search has been introduced. The discovery process is matured, if the search must be incorporated with client's QoS requirements. To alleviate the aforementioned difficulties, QoS driven web service discovery approach has been introduced. The gist of the approach is to assist the user to search the pertinent web service based on functional and non functional evaluation. The web services metadata are extracted from the WSDL file and it will be stored in a service pool. The functional and nonfunctional evaluation can be performed by the proposed algorithm, and the aggregated value will be stored in a service pool. The services which are matched with the user query will be provided to the client.

Web services are one of the most important resources on the Internet. Faced with the increasing numbers of Web services and service users, researchers in the services computing field have attempted to address a challenging issue, i.e., how to quickly find the suitable ones according to user queries. Many previous studies have been reported towards this direction. In this work we proposing a new web service discovery approach which is consist of semantics based mining. This approach helps to mine underlying semantics and user to employ web services. First we creating web database which contains dataset which is extracted from well-known registry sites. Clustering is performed to cluster the data which contains similarity i.e. synonyms, abbreviations and disordered fragments using k-means clustering. using clusters, similarity index libraries are created for semantic mining. Semantic mining is performed before receiving request from the user. Finally web service discovery approach is designed which accepts the request from the users and produces related services based on semantic mining. In this we performing data redundancy to avoid time complexity and it lead to faster response time. The experimental results will show better precision and recall rate than existing approaches.

Matching web services and client requirements in the form of goals is a significant challenge in the discovery of semantic web services. The most common but unsatisfactory approach to matching is set‐based, where both the client and web services declare what objects they require and what objects they can provide. Matching then becomes the simple task of comparing sets of objects. This approach is inadequate because it says nothing about the functionality required by the client or the functionality provided by the web service. As an alternative, we use the Frame Logic as implemented in Flora‐2 to specify web service capabilities and client requirements, including their preconditions, postconditions, and ontologies, implement a logic‐based discovery agent using Flora‐2, demonstrate its usefulness in a medical appointment making scenario, and show its efficiency both theoretically and by benchmarking. The result is an expressive yet concise representation scheme for semantic web services, and a practical, efficient, powerful, and fully implemented matching engine based purely on logical inference for web service discovery, with direct applicability to Web Service Modeling Ontology and Web Service Modeling Language, because both are based on Frame Logic.

With the increasing use of web services in everyday tasks, we are entering an era of Internet of Services (IoS). Service discovery and selection has become critical issue in the area of web services. Traditional service discovery approaches are often supported by centralized registries that could suffer from single point failure, performance bottleneck, and scalability issues in large scale systems. To address these issues, in this paper we propose a context-aware service discovery and selection approach in a decentralized peer-to-peer environment. In the approach homophily similarity was used for bootstrapping and distribution of nodes. The discovery process is based on the similarity of nodes, previous interaction and behaviour of the nodes, which will help the discovery process in a dynamic environment. Our approach is not only considering service discovery, but also the selection of the best available web service by taking into account the QoS properties of the web services. Experimental results were based on real world semantic web service dataset, the results showed that the approach achieved better performance and efficiency in both discovery and selection processes.

Due to the emergence of Internet technologies and service-oriented computing, there is a rapid growth in the quantity and variety of services on the web. Discovering the web services as per the request is not an easy task because of the advancement of service-oriented computing which includes web services, cloud services, mobile services, etc. These services are dynamic and published according to the emerging standards in repositories. Web service clustering plays a crucial role in web service discovery. When services are grouped according to the similarity, then it reduces the search space and time, so that services can be discovered efficiently. Many eminent researchers have proposed approaches for efficient web service discovery by incorporating web service clustering. In this paper, we review different approaches that are proposed for web service clustering to enhance the discovery process. A comparison among existing approaches is carried out based on the vector representation approach, dimensionality reduction technique, method to capture semantic relationship among features, clustering technique, type of input dataset, number of web services in dataset and service repository. This review will help the researchers to understand the existing techniques to group services in similar clusters to improvise service discovery and the scope for improvement by future directions.KeywordsService-oriented architectureWeb services/Web APIWeb service clusteringWeb service discovery

Service discovery is the process to find a service that is best meet the user's requirement. Context of the user and the service plays an important role during the process because it takes into consideration more about the user and the service. In order to better implement the personalization of service discovery, and take into full consideration of the user's requirement and feature, a context-based framework for web services discovery is proposed in this paper. User Model and Intention Model are used in our framework to construct the user context. Service discovery and composition are carried out heuristically by considering both the user context and the web services context. And Service discovery is conducted by taking into account not only a published single web service but the combination of web services when a single web service can not be found. Service recommendation is also provided.

Service-oriented computing is gaining wider acceptance. For Web services to become practical, an infrastructure needs to be supported that allows users and applications to discover, deploy, compose and synthesize services automatically. For this automation to be effective, formal semantic descriptions of Web services should be available. In this paper we formally define the Web service discovery and composition problem and present an approach for automatic service discovery and composition based on semantic description of Web services. We also report on an implementation of a semantics-based automated service discovery and composition engine that we have developed. This engine employs a multi-step narrowing algorithm and is efficiently implemented using the constraint logic programming technology. The salient features of our engine are its scalability, i.e., its ability to handle very large service repositories, and its extremely efficient processing times for discovery and composition queries. We evaluate our engine for automated discovery and composition on repositories of different sizes and present the results.

Web service discovery (WSD) is the task of matchmaking a set of relevant web services. Quality of service (QoS) has recently been applied to represent non-functional properties of web services. Therefore, when those services provide the same functionality but have different QoS values, how to effectively filter out the services that cannot satisfy the QoS constraints and rank the remaining services is still an open research issue. In this paper, we propose an integrated approach that allows a service requester to specify a functionality request, multiple QoS constraints and their preferences, and our method discovers a set of the most appropriate ranked services with QoS utility aggregation. By conducting empirical experiments on simulated web services, we validate the feasibility of our service discovery approach. The running example shows that, our approach can find more appropriate services by the satisfiability of multiple QoS constraints and the ranking of aggregated QoS.