计算机科学与探索2018，Vol.12Issue(7)：1064-1074,11.DOI:10.3778/j.issn.1673-9418.1709092
基于互信息的知识图谱实体关联关系建模与补全
Mutual Information Based Modeling and Completion of Correlations in Knowl-edge Graphs
摘要
Abstract
The completion of missing relationships between entities in knowledge graph (KG) is the topic with great attention in the field of KG research. With the rapid development of Web2.0, the association between entities reflected by the user-generated data (UGD) is complementary to the knowledge described in KG. In the knowledge reasoning method based on KG path, there are sparse or wrong entity relations and poor connectivity, which leads to the inac-curate relationship extracted from entities. For this problem, this paper proposes a method for complementing KG by using correlation between entities in UGD. Firstly, based on the UGD, this paper uses mutual information to cal-culate the relationship between entity nodes and build the entity association graph (EAG), and then proposes a super-position method to quantify the potential correlation between non-adjacent entities in the EAG, so the association impact values are obtained. Finally, the multiple correlation effects between non-adjacent entity nodes are superposed to determine whether there is a strong correlation between the entities. By adding the edges between non-adjacent entity nodes with associations, KG completion can be fulfilled. The experimental results based on real data sets show the efficiency and effectiveness of the proposed KG completion.关键词
知识图谱/补全/用户生成数据/互信息/关联影响Key words
knowledge graph/completion/user-generated data/mutual information/association impact分类
信息技术与安全科学引用本文复制引用
夏维,王珊蕾,尹子都,岳昆..基于互信息的知识图谱实体关联关系建模与补全[J].计算机科学与探索,2018,12(7):1064-1074,11.基金项目
The National Natural Science Foundation of China under Grant No. 61472345(国家自然科学基金) （国家自然科学基金）
the Program for Excellent Young Talents of Yunnan University under Grant No. WX173602(云南大学青年英才培育计划) （云南大学青年英才培育计划）
the Innovative Research Foundation for Graduate Students of Yunnan University under Grant No.YDY17017(云南大学研究生科研创新基金项目). （云南大学研究生科研创新基金项目）
