基于深度学习与图数据库构建中文商业知识图谱的探索研究

摘要

将知识图谱应用到商业领域是大数据时代企业的迫切需求。文章通过引入深度学习算法中的深度置信网络，自动提取领域信息中蕴含的知识单元及单元之间的关系，以此解决知识单元提取这一难点。同时，采用Neo4j图形数据库来存储知识图谱中包含的知识单元及其关系。当需要对知识图谱中包含的知识单元进行查询时，可以采用该图形数据库的Cypher查询语言进行查询。文章的研究方法可为商业领域快速构建知识图谱提供借鉴。%Application of Knowledge graph to business areas is the urgent need of the enterprises in big data era. In or-der to solve the knowledge element extraction difficulties, the author tries to automatically extract the knowledge units and its relationships contained in the given field by introducing the deep belief network learning algorithm. At the same time, the knowledge unit and its relationship in the knowledge graph are stored by using the Neo4j graphics database. When you need to query the knowledge unit in the knowledge graph, the Cypher query language of the graph database can be used. The research method of this paper can provide reference for the rapid construction of knowledge graph in the commercial field.