Framework For Web Service Discovery Research Articles

Self-adaptive mobile web service discovery framework for Dynamic Mobile Environment

This paper proposes a self-adaptive mobile web service (MWS) discovery framework for a dynamic mobile environment (DME) to deal with MWS proliferation, dynamic context, and irrelevant MWS discovery challenges. The main contribution of this research includes an improvement of the matchmaking algorithm, enhanced MWS categorization approach, and extensible meta-context ontology that represents the context information in DME. This was achieved by enabling the self-adaptive matchmaker to learn MWS relevance using a Modified-Negative Selection Algorithm (M-NSA) and retrieve the most relevant MWS based on the current context of the discovery. To assess the proposed framework, series of experiments was carried out using publicly-available datasets. The performance of the framework is evaluated against the state-of-the-art frameworks. It was found that the proposed framework is more effective and attained better binary and graded relevance when subjected to context variations which are prevalent in DME. This is useful for service-based application designers and other MWS clients.

Semantics Mining&Indexing-Based Rapid Web Services Discovery Framework

Web services, as an effective realization technology of SOA, have been deployed largely on the Internet. Comparing with the traditional Web pages, the information island problem existing in Web services field is more serious. Web services with specific functions not only submerge in the Web services library, but also submerge in the traditional Web pages library. As a result, finding web service rapidly and accurately becomes a problem needing solving, and this promots the research on the field of web services discovery. In this paper, we propose a semantics mining&indexing-based rapid Web services discovery framework. First, focus on the Web services formalizing model with the basic information of Web service or composition. Then propose a Web services matching engine with high accurency, and there is no semantics ontology dependence in matching engine, also, we propose a Web services discovery framework basing index library, which can help providing a low processing time in request searching. When creating the index library, we apply semantics mining to overcome the shortcoming of low searching accurancy in traditional index framework. Finally, the experiments are tested that the Web service discovery framework shows high precision rate and recall rate, which can provides a solution to the problem of persuiting both low searching processing time and high search accurancy in Web service discovery field.

An QoS based multifaceted matchmaking framework for web services discovery

With the increasing demand, the web service has been the prominent technology for providing good solutions to the interoperability of different kind of systems. Web service supports mainly interoperability properties as it is the major usage of this promising technology. Although several technologies had been evolved before web service technology and this has more advantage of other technologies. This paper has concentrated mainly on the Multifaceted Matchmaking framework for Web Services Discovery using Quality of Services parameters. Traditionally web services have been discovered only with the functional properties like input, output, precondition and effect. Nowadays there is an increase in number of service providers leads to increase in the web services with same functionality. So user need to discover the best services so Quality of Service factors has been evolved. The traditional discovery supports only few quality parameters and so the discovery is easy in retrieval of services. As the parameter increases the matchmaking will be complex during service discovery. So in this proposed work, we have identified 21 QoS parameters which are suitable for service discovery. The information retrieval techniques are used to evaluate the results and results show that the proposed framework is better.

Similarity analysis and bootstrapping framework for web service discovery in the field of medical applications using quality of experience and quality of service

Similarity analysis and bootstrapping framework for web service discovery in the field of medical applications using quality of experience and quality of service

A Similarity Measure across Ontologies for Web Services Discovery

Given the critical and difficult nature of discovering Web services in the development process of service oriented architectures, several studies have been proposed to solve this problem. There is a real need to work for matching semantic Web services which use different ontologies. In responding to this need, measuring semantic similarity between SWS may be reduced to the calculation of similarity between ontological concepts. This work is a contribution to achieve semantic interoperability for Web services in a multi-ontology environment, for which the authors present a generic framework for Web services discovery. Here their focus is on the semantic similarity measure-based core of their framework and the authors present a novel algorithm for concepts matching between different ontologies. Results of the experiments confirm the viability of the semantic similarity measure.

A bio-inspired, incremental clustering algorithm for semantics-based web service discovery

Web service discovery is a challenging task due to the widespread availability of published services on the web. In this paper, a service crawler-based web service discovery framework is proposed, that employs information retrieval techniques to effectively retrieve available, published service descriptions. Their functional semantics is extracted for similarity computation and tag generation using natural language processing techniques. The framework is inherently dynamic in nature as new service descriptions may be continually added during periodic crawler runs or existing ones may be removed if service is unavailable. To deal with these issues, a dynamic, incremental clustering approach based on bird flocking behaviour is proposed. Experimental results show that semantic analysis and automatic tagging captured the services' functional semantics in a meaningful way. The algorithm effectively handled the dynamic requirements of the proposed framework by eliminating cluster recomputation overhead and achieved a speed-up factor of 61.8% when compared to hierarchical clustering.

OWLS-CSM: A Service Profile Based Similarity Framework for Web Service Discovery

This paper presents OWLS-CSM framework, an OWL-S Service Profile based framework for web service discovery in cloud environment. In the proposed framework, services are presented as advertisements; their concepts are semantically defined and described in a hierarchal ontology to facilitate service matchmaking. In matchmaking process advertisements and query are represented as objects and three levels of similarities are used, based on OWL-S Service Profile, to matching, namely taxonomical similarity, functional similarity and non-functional similarity. Milestone method is adopted in the matchmaking algorithm to match the concepts according to their position in the hierarchal ontology. The results obtained from OWLS-CSM are analyzed and compared with other similar works to prove and evaluate the efficiency of our work.

Semantic Web service discovery using natural language processing techniques

This paper proposes a semantic Web service discovery framework for finding semantic Web services by making use of natural language processing techniques. The framework allows searching through a set of semantic Web services in order to find a match with a user query consisting of keywords. By specifying the search goal using keywords, end-users do not need to have knowledge about semantic languages, which makes it easy to express the desired semantic Web services. For matching keywords with semantic Web service descriptions given in WSMO, techniques like part-of-speech tagging, lemmatization, and word sense disambiguation are used. After determining the senses of relevant words gathered from Web service descriptions and the user query, a matching process takes place. The performance evaluation shows that the three proposed matching algorithms are able to effectively perform matching and approximate matching.

A Study on Knowledge Discovery of Relevant Web Services with Semantic and Syntactic approaches

Web mining is the application of data mining techniques to discover patterns from the Web. Web services defines set of standards like WSDL(Web Service Description Language), SOAP(Simple Object Access Protocol) and UDDI(Universal Description Discovery and Integration) to support service description, discovery and invocation in a uniform interchangeable format between heterogeneous applications. Due to huge number of Web services and short content of WSDL description, the identification of correct Web services becomes a time consuming process and retrieves a vast amount of irrelevant Web services. This emerges the need for the efficient Web service mining framework for Web service discovery. Discovery involves matching, assessment and selection. Various complex relationships may provide incompatibility in delivering and identifying efficient Web services. As a result the web service requester did not attain the exact useful services. A research has emerged to develop method to improve the accuracy of Web service discovery to match the best services. In the discovery of Web services there are two approaches are available namely Semantic based approach and Syntactic based approach. Semantic based approach gives high accuracy than Syntactic approach but it takes high processing time. Syntactic based approach has high flexibility. Thus, this paper presents a survey of semantic based and syntactic based approaches of Web service discovery system and it proposed a novel approach which has better accuracy and good flexibility than existing one. Finally, it compares the existing approaches in web service discovery.

Service Discovery Framework Supported by EM Algorithm and Bayesian Classifier

Abstract Service oriented computing has become the main stream research field nowadays. Meanwhile, machine learning is a promising AI technology which can enhance the performance of traditional algorithm. Therefore, aiming at solving service discovery problem, this paper imports Bayesian classifier to web service discovery framework, which can improve service querying speed. In this framework, services in service library become training set of Bayesian classifier, service query becomes a testing sample. Service matchmaking process can be executed in related service class, which has fewer services, thus can save time. Due to don’t know the class of service in training set, EM algorithm is used to estimate prior probability and likelihood functions. Experiment results show that the EM algorithm and Bayesian classifier supported method outperforms other methods in time complexity.

A Framework for Automatic Web Service Discovery Based on Semantics and NLP Techniques

As a greater number of Web Services are made available today, automatic discovery is recognized as an important task. To promote the automation of service discovery, different semantic languages have been created that allow describing the functionality of services in a machine interpretable form using Semantic Web technologies. The problem is that users do not have intimate knowledge about semantic Web service languages and related toolkits. In this paper, we propose a discovery framework that enables semantic Web service discovery based on keywords written in natural language. We describe a novel approach for automatic discovery of semantic Web services which employs Natural Language Processing techniques to match a user request, expressed in natural language, with a semantic Web service description. Additionally, we present an efficient semantic matching technique to compute the semantic distance between ontological concepts.

Structural and Role-Oriented Web Service Discovery with Taxonomies in OWL-S

In this paper, we describe and evaluate a Web service discovery framework using OWL-S advertisements, combined with the distinction between service and Web service of the WSMO discovery framework. More specifically, we follow the Web service discovery model, which is based on abstract and lightweight semantic Web service descriptions, using the service profile ontology of OWL-S. Our goal is to determine fast an initial set of candidate Web services for a specific request. This set can then be used in more fine-grained discovery approaches, based on richer Web service descriptions. Our Web service matchmaking algorithm extends object-based matching techniques used in structural case-based reasoning, allowing 1) the retrieval of Web services not only based on subsumption relationships, but exploiting also the structural information of OWL ontologies and 2) the exploitation of Web services classification in profile taxonomies, performing domain-dependent discovery. Furthermore, we describe how the typical paradigm of profile input/output annotation with ontology concepts can be extended, allowing ontology roles to be considered as well. We have implemented our framework in the OWLS-SLR system, which we extensively evaluate and compare to the OWLS-MX matchmaker.

Semantic Web service discovery framework based on WSMO-QoS

Currently, OWL-S and Web Service Modeling Ontology (WSMO) are two popular frameworks that are used to describe semantic Web service. However, since they mainly focus on the description of the functional part, it is difficult for them to select the best service with little consideration of Quality of Service (QoS). To solve this problem, the WSMO specification was extended and an ontology-based meta-model of QoS called WSMO-QoS was presented. Furthermore, a QoS-based discovery framework for semantic Web service was proposed, which supported service discovery from three levels: basic description, Input-Output-Precondition-Effects (IOPE) and QoS. The experimental results validate the effectiveness of the framework.