摘要： 针对网格服务发现的查全率、查准率效率较低的现状，基于本体技术和粗糙集理论，设计了一个服务发现算法OGSDA-RS，在服务匹配之前先进行3步预处理操作：规范化请求服务，根据请求服务对发布服务进行不相关属性约减和依赖属性约减。实验结果表明，与UDDI和OWL-S相比，服务发现的查全率、查准率要高出50%~75%，而且当发布服务的规模较小时，效率比OWL-S最高能高出 2.7倍。

关键词: 本体, 粗糙集理论, 网格服务发现, 不相关属性约减, 依赖属性约减

Abstract: To improve the recall, precision, and efficiency of grid services discovery, based on ontology technology and rough sets theory, an algorithm OGSDA-RS is designed. Before services matchmaking, according to service request, OGSDA-RS performs the standardization of service request, irrelevant properties reduction and dependent properties reduction. Experiment indicates that the recall and precision of OGSDA-RS tower is above 50%~75% comparing with UDDI and OWL-S. When the number of services advertised is not very large, the efficiency of OGSDA-RS is 2.7 times higher than OWL-S.

Key words: ontology, rough sets theory, grid services discovery, irrelevant properties reduction, dependent properties reduction

中图分类号: 

• TP311