Research On Web Service Discovery Technology Based On Ontology

With the fast development of Internet, the growing number of web services available on the Web raises new and challenging search problems: efficiently locating functionality-desired web services among numbers of web services and selecting a best one among large numbers of functionality-similar web services. While these just are the task of web service discovering. However, there are still some drawbacks that cannot be completely resolved with existing technologies. The fact that Web Services are described in terms of XML syntax without a well-defined semantics results in that computers can not process the interactions of Web Services automatically.This is where the Semantic Web comes to play. The purpose of Semantic web is to extend the current Web, makes the information on the Web semantic and understood, managed by machine. So semantic-based web service discovering technology is becoming a hot research topic. The researches show that the use of semantic description and ontology of web service can improve the result of service discovering.Automatic Web Services Discovery is the basic issue of Semantic Web Services' research. This paper describes a model for flexible discovery of Semantic Web Services by researching Semantic Web Services discovery. The proposed approach has three main features compared with other approaches.Firstly, OWL-S is used to describe the Web Services. As both a language and an ontology, OWL-S is widely used to add semantic annotations to Web Services and enable automatic discovery of Web Services. However, OWL-S is still evolving and has some shortcomings, especially that it can not describe the reputation of Web Services. In order to overcome this, the Reputation description for Web Services is defined by the author in this paper. The proposed Reputation description can describe whether a Web Service is trusty, as well as the Quality of Service and other things.Furthermore, we design a services discovery system based on semantic function and quality match. The system is a service discovery strategy using level-classified match, we describe the matching algorithm in every level detailedly. It realizes complexity matching between advertisement profile and request profile. It increases search efficiency.Thirdly, the Reputation Manager of Web Services is introduced in the Semantic-Based Web Services Discovery Model. It is responsible for reputation management of Web Services. In the ideal concept model of Reputation Manager, there is a third-part Reputation Authority which is in charge of the measurement of Reputation for Web Services. But currently the third-part Reputation Authority does not exist, so a feedback mechanism is used by the Reputation Manager which collects the feedback from the clients and save them in a persistent database.