关键词: 马尔可夫聚类, 知识库, 实体间关系

Abstract: Recent years, the development of knowledge bases is very fast. They store large scale of entities and the relations between entities. However, most of the relations which have the same meanings are not in the same form. It is necessary to resolute the relations. For this purpose, this paper proposes an approach based on Markov cluster algorithm to cluster the relation with same meanings. Firstly, this paper calculates the semantic similarity between every two relations, and then it uses the relation similarity as weighted-edge to build a graph. Finally, this paper runs a Markov cluster algorithm on the graph and gets the result of relation clusters. Experiments show that the proposed approach has a higher purity than hierarchy cluster and k-means cluster.

Key words: Markov cluster, knowledge base, relation between entities