Transcription of Knowledge Graph Embedding via Dynamic Mapping Matrix
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Knowledge Graph Embedding via Dynamic Mapping Matrix
Knowledge Graph Embedding via Dynamic Mapping Matrix Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu and Jun Zhao National Laboratory of Pattern recognition (NLPR). Institute of Automation Chinese Academy of Sciences, Beijing, 100190, China Abstract completion is to predict relations between entities based on existing triplets in a Knowledge Graph . In Knowledge graphs are useful resources for the past decade, much work based on symbol and numerous AI applications, but they are far logic has been done for Knowledge Graph comple- from completeness. Previous work such as tion, but they are neither tractable nor enough con- TransE, TransH and TransR/CTransR re- vergence for large scale Knowledge graphs. Re- gard a relation as translation from head en- cently, a powerful approach for this task is to en- tity to tail entity and the CTransR achieves code every element (entities and relations) of a state-of-the-art performance.
National Laboratory of Pattern Recognition (NLPR) Institute of Automation Chinese Academy of Sciences, Beijing, 100190, China fguoliang.ji,shizhu.he,lhxu,kliu,jzhao g@nlpr.ia.ac.cn ... two vectors to represent a named sym-bol object (entity and relation). The rst one represents the meaning of a(n) entity (relation), the other one is used to con ...
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