论知识概念间联想记忆的学习

Int. J. Networked Distributed Comput. Pub Date : 2020-05-01 DOI:10.2991/ijndc.k.200515.005

Zhenping Xie, Kun Wang, Yuan Liu

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引用次数: 3

摘要

知识图谱(Knowledge graph)最早由Google于2012年提出[1]，它采用图形结构来表示概念性项目的知识信息。在知识图中，每个图节点表示一个知识概念，带有标签的边表示知识节点之间的语义关系。知识图是表示和存储自然语言文本中信息的一种非常有用的工具，在自然翻译[2]、问答系统[3]、自然语言理解[4]等领域得到了广泛而先后的应用。

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On Learning Associative Relationship Memory among Knowledge Concepts

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].

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Int. J. Networked Distributed Comput.

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