基于属性权重和粗糙集的网格服务发现算法

摘要

To solve the low efficiency problem of grid service discovery, based on ontology technology, the theory of decision table, and knowledge representation system of rough sets, the paper put forward an optimized service discovery algorithm that considered the weight of the service properties. By rule extraction of the service invocation history and the calculation of the service properties weight, two main phases of the service discovery algorithm: information pre-processing and rough set service matching could be achieved. This article also gave theoretical analysis and experimental verification on both precision rate and recall rate. The results show that the proposed algorithm can provide higher precision and recall rate; besides, the ranking results of the candidate services are more preferable.%针对网格服务发现中发现效率低的问题,基于本体技术及知识表示系统和决策表的理论,提出一种优化的考虑服务属性权重的服务发现算法.通过对服务调用历史记录的规则抽取和属性权重计算,给出了包含信息预处理、粗糙集服务匹配的两个阶段服务发现算法实现,并分别从查准率和查全率两个方面进行了理论分析和实验验证.结果表明,所提算法有较高的查全率和查准率；同时,候选服务的排序结果更符合用户的需求.