On Learning Associative Relationship Memory among Knowledge Concepts

Abstract

Knowledge graph is firstly put forward by Google in 2012 [1], which uses graph structure to represent knowledge information on conceptual items. In knowledge graph, each graph node denotes a knowledge concept, and edges equipped with labels represent semantic relations among knowledge nodes. Knowledge graph is a very useful tool to represent and store the information in natural language text, and has been widely and successively applied to natural translation [2], question-answer system [3], and natural language understanding [4].