Application of an Improved Synthetical Semantic Similarity Method in Water Knowledge Graph

Abstract

In order to integrate different kinds of information in the water affairs field, this paper proposes an improved comprehensive semantic similarity algorithm and applies it to the construction of water affairs ontology. In this article, the algorithm is to give the concept instance similarity algorithm and concept definition similarity algorithm appropriate weight. First, we apply the three algorithms to the concept of the local ontology of smart water, and then calculate the similarity between the concepts to judge the similarity between the concepts to merge the smart water data, and finally compare the similarities of the three algorithms Degree value and calculation and comparison of three similarity variance values prove the effectiveness of the method. It can be seen from the experimental results that the variance of the comprehensive similarity calculation method is smaller than that of the other two methods, and it is easier to determine the similarity between two concepts.