语义网格中的相似度算法研究

Study on Semantic Similarity Algorithms Based on Semantic Grid

在网格中实现更加准确有效的服务发现、查询及其动态分配和替换,需要在语法匹配的基础上进一步实现语义匹配。语义匹配的关键在于语义相似度的计算。本文首先分析传统的相似度计算方法的特点以及存在的问题,提出一种新的改进算法。改进的算法考虑了深度影响因素,并引入多种语义关系且对这些关系分别赋予不同的权值,最后给信息量赋予了一种新的度量方法;文章最后给出相关实验结果,并比较了各算法的有效性。

For better achievement in service discovery and service replacement dynamically, we have to accomplish matching based on semantic.Semantic similarity measurement can be applied in many different fields and has variety of ways to measure it.After studying these measures, we find some existing problems and propose some measures.We explore a upgrading method by considering the depth effect and more semantic relations extensively.Further, we grant the different relations different weight.Finally, the paper presents the result of the proposed measure and other approaches.