基于改进语义熵最大化模型的服务发现算法

Service discovery of semantic Web based on improved semantic entropy maximum model

语义匹配与发现是语义Web的核心内容之一。提出一种新的基于语义熵的服务发现与匹配算法。该算法通过引入语义熵的概念,把最大熵原理运用到语义识别与匹配领域,并对传统的熵最大模型进行了经验修正。通过实验对比分析,可以看出修正后的最大熵模型在服务发现计算方面具有较好的性能,该模型在一个真实的中文语义Web的语义识别项目中得到了应用,也体现出较好的精确度和性能。

The service discovery is one of the core technologies of semantic Web. This paper brought forward a novel discovery approach of the semantic service based on the SEM （ Semantic Entropy Maximum）. This approach applied the entropy maximum algorithm to the matching and the recognizing of the semantic service, and meanwhile, it compared this algorithm with other related algorithms. The results of this experiment show that the SEM model has preferable performance. In a practical enterprise application of semantic Web, the SEM is proved to be useful in recognizing and matching the semantic of Chinese.