Research On Ontology-based Semantic Interoperability

With the rapid development of Internet technology, network technology and application, represented by the Internet of Things, Web service etc, have already benefited the public. The information and service become the mainstream of society. In this era of service, the main goal is user-centered, service on demand and providing high-quality and efficient services for people. In the process of building the business process of BPEL, research on semantic interoperability between user and service entity is to pursue the goal. Through it, we can analyse user-centered demand and provide the best services or solutions for people and improve creating efficiency of business process and service experience quality.Based on national973projects, we studies some key issues of semantic interoperability between user and service entity. By using semantic Web technology——ontology, this paper analyses the semantic of user demand and understands the demand accurately and makes the correct response according to different needs. The main research contents are as follows:In order to provide better service to user, this paper puts forward the semantic interoperability Framework——Comprehension Response Framework (CRF), which is used by service entity to realize interoperability. The whole framework consists of four parts:IO interface module, demand comprehension module, demand response module and the database module. By means of ontology technology, the process of semantic interoperability is studied. The detailed contents is understanding the users’real intention based on ontology from the fuzzy original demand set and making the different responses according to the different demands. In the demand comprehension module, by means of the advantage of ontology in the semantic understanding, we analyse the user fuzzy demand and find the correct demand. In the demand response module, by means of the advantage of ontology in the semantic reasoning, we ananlyse the relation of sevices and provide the best candidate services.In order to obtain user accurate demand from the fuzzy original demand, an optimization algorithm of demand is proposed. In this algorithm, user’s demand is formatted into standard demand set. Then from the set, by using the maximum portfolio and ontology base, we search user’s real purpose and find the accurate demand as much as possible. The accurate demand is the foundation to provide the best service for users.In order to meet the users’ demand of simple service discovery, an ontology-based service matching algorithm is put forward. In this algorithm, by using query rewriting theory, the key word query is rewritten into ontology query. Because the key word can not been divided, query granularity is the minimum. The attributes of ontology is corresponding to the key words. So the query granularity of ontology is bigger than key word. Because there is incidence relation between ontology base and Web service base, we can provide better candidate services for user.Aiming at personalized demand, in order to provide best services, a data fusion based service discovery is proposed. The personalized demand is in the Web service base, searching Web services whose performance-price-ratio index is high. The importances of these indexes are not the same. In this algorithm, through data fusion, more indexes are fused into single index. Based on the algorithm, a service discovery algorithm is put forward to provide suitable result set.Aiming at the demand of service recommendation, in order to provide candidate services which can satisfy user demand, an ontology based service recommendation algorithm is put forward. In the algorithm, dynamic programming theory is used. In the result set of service recommendation, the membership as measure index is used to divide high relative services and low relative services. High relative services are recommended for the users. So it can improve creating efficiency of business process and service experience quality.