ProjR:Embedding Structure Diversity for Knowledge Graph Completion

摘要：

　　Knowledge graph completion aims to find new true links between entities.In this paper,we consider an approach to embed a knowledge graph into a continuous vector space.Embedding methods,such as TransE,TransR and ProjE,are proposed in recent years and have achieved promising predictive performance.We discuss that a lot of substructures related with different relation properties in knowledge graph should be considered during embedding.We list 8 kinds of substructures and find that none of the existing embedding methods could encode all the substructures at the same time.Considering the structure diversity,we propose that a knowledge graph embedding method should have diverse representations for entities in different relation contexts and different entity positions.And we propose a new embedding method ProjR which combines TransR and ProjE together to achieve diverse representations by defining a unique combination operator for each relation.In ProjR,the input head entity-relation pairs with different relations will go through a different combination process.We conduct experiments with link prediction task on benchmark datasets for knowledge graph completion and the experiment results show that,with diverse representations,ProjR performs better compared with TransR and ProjE.We also analyze the performance of ProjR in the 8 different substructures listed in this paper and the results show that ProjR achieves better performance in most of the substructures.

关键词： Diversity structures Knowledge graph embedding Knowledge graph completion

作者: Wen Zhang Juan Li Huajun Chen

作者单位: Zhejiang University,Hangzhou,China

会议类型: 国际会议

会议名称: 2018自然语言处理与中文计算国际会议(NLPCC2018)

会议地点: 呼和浩特

会议语种:英文

页码: 145-157

在线出版日期: 2018-08-26（万方平台首次上网日期，不代表论文的发表时间）