Semantic Web Service Discovery Method Research Articles

A semantic similarity measure integrating multiple conceptual relationships for web service discovery

The process of Web service discovery identifies the most relevant services to requesters’ service queries. We propose a new measure of semantic similarity integrating multiple conceptual relationships (SIMCR) for Web service discovery. The new measure enables more accurate service-request comparison by treating different conceptual relationships in ontologies such as is-a, has-a and antonomy differently. Each service or request is represented by vectors of terms (or words) that characterize both the interface signature and textual description. The overall semantic similarity is computed as a weighted aggregation of interface similarity and description similarity. The experimental results confirm the effectiveness of the proposed semantic similarity measure. As demonstrated in this study, the semantic Web service discovery method based on the proposed similarity measure outperforms existing state-of-the-art discovery methods in terms of precision, recall and F-measure. The proposed semantic similarity measure has wider applications such as to improve document classification or clustering, and to more accurately represent and apply knowledge in expert and intelligent systems.

AN IMPROVED LIGHT-WEIGHT MATCHMAKING MECHANISM FOR DISCOVERING OWL-S SERVICES BASED ON SPARQL, BIPARTITE AND NLP APPROACH

Semantic Web services integrate the meaningful content of the Semantic Web with the business logic of Web services and thus enable industries and individuals to access these services. But as the number of available Web services increase, there is a growing demand for a mechanism for effective retrieval of required services. We propose an improved Semantic Web service discovery method for finding OWL-S (Web Ontology Language for Services) services by combining functional similarity matching (using bipartite graph) and textual similarity matching. However, discovering relevant Semantic Web service is a heavyweight task. Performance of service discovery is significantly reduced when the number of services increases. To overcome this issue, a lightweight filtering stage is also introduced before the discovery mechanism. Filtering is performed by semantic-based SPARQL (Simple Protocol and RDF Query Language) query. It will significantly reduce the input for the discovery process. Thus the search space and the time required to find the relevant services will be reduced. The proposed techniques are applied to a sample test collection and experimental results are presented, which demonstrate the effectiveness of the idea. ( Keywords: discovery, filtering, OWL-S, Semantic Web service, SPARQL )

A QoS-assured Trust-driven Semantic Web Service Discovery Method

It have become very difficult that users can find the best, credible web service for some proposed semantic web service discovery methods, because web service environment has become open, autonomic, dynamic, and deceptive. This paper proposes a QoS-assured trust-driven semantic web service discovery method i.e. TDSWSD. This method, firstly, describes and labels web services by ontology technology, and then makes use of the existing keyword matching method to carry basic matching; secondly, function matching will be done by ontology-based concept semantic similarity calculation method; finally, QoS-assured trust measure method will be designed to carry credible QoS matching. Compared with existing methods, the experimental results show that this method can not only automatically find the service to meet user’ requirements, but also ensure the validity and reliability of service discovery.

A Semantic Web Service Discovery Method Based on Ontology

Many methods have been used such as UDDI and DWS to discovery requested web services. But they are just a kind of simple syntax match based on keywords and have a low ratio and precision. This paper proposes A Semantic Web Service Discovery Method Based on Ontology. It uses tree-form data structure to describe the web services and give all the nodes a weight value by certain strategy, then compute the semantic similarity between the web services requested and the services registered. To validate the feasibility and effectiveness of the algorithm, we construct a self-developed prototype system to show how well it works. The experiments prove that this algorithm has high recall and precision than other methods.

A Method for Semantic Web Service Discovery Based on Context Inference

Constrained by the context around user, the service discovery result mostly does not fulfill the context expectation of user′s when we apply traditional semantic Web service discovery method. An approach for Web service discovery based on context and inference rules is proposed in the paper. The result of Web service discovery will fulfill the user′s context in this way. The user context ontology and Web service context ontology are proposed respectively to describe context information. And the inference meta-rules between user context and service context are proposed as the foundation to refine results of Web service discovery. The context inference algorithm is proposed and implemented in the context inference module finally. Comparing to existing approach for semantic Web service discovery, it is proved by the experiment that the more appropriate result of Web service discovery will be obtained for the user while reasonable time cost is added.