SEMANTIC WEB SERVICE DISCOVERY BASED ON USER PREFERENCE CLUSTER

摘要：

In the converged network environment, owing to diversification of user demand and diversification of services, the existing semantic service discovery algorithms almost have the problem of too long service response time. With respect to this current situation, this paper proposes a novel services semantic web service discovery method based on user preference cluster. Firstly, this paper optimizes the design of Unmixed Semantic UDDI Model and then makes use of the clustering technology to preprocess the user preference from the standpoint of user demand before service discovery. For that reason, a user could receive demanded services quickly, which have been thought highly of other users, whose preferences similar to, reducing processing semantic information. Verified by actual test environment, this method can shorten the service discovery response time on condition of not affecting the service discovery accuracy, thereby enhancing the performance of Unmixed Semantic UDDI.

关键词： Semantic UDDI Service Discovery User Preference Ontology

作者: Mo Wang Xiaofeng Li Xiuquan Qiao

作者单位: State Key Laboratory of Networking and Switching Technology,Beijing University of Posts and Telecomm State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecom

会议类型: 国际会议

会议名称: 2010 3rd IEEE International Conference on Broadband Network & Multimedia Technology(2010年第三届IEEE宽带网络与多媒体国际会议 IC-BNMT 2010)

会议地点: 北京

会议语种:英文

页码: 939-944

在线出版日期: 2010-10-26（万方平台首次上网日期，不代表论文的发表时间）