A Temporal Knowledge Graph Embedding Model Based on Variable Translation
Yadan Han,
Guangquan Lu,
Shichao Zhang
et al.
Abstract:Knowledge representation learning (KRL) aims to encode entities and relationships in various knowledge graphs into low-dimensional continuous vectors. It is popularly used in knowledge graph completion (or link prediction) tasks. Translation-based knowledge representation learning methods perform well in knowledge graph completion (KGC). However, the translation principles adopted by these methods are too strict and cannot model complex entities and relationships (i.e., N-1, 1-N, and N-N) well. Besides, these … Show more
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