华东师范大学学报（自然科学版）Issue(3)：55-66,12.DOI:10.3969/j.issn.1000-5641.2018.03.007
面向企业知识图谱构建的中文实体关系抽取
Chinese named entity relation extraction for enterprise knowledge graph construction
摘要
Abstract
The enterprise knowledge graph is a kind of domain knowledge base for the financial field to describe business relationships between enterprises.Although the domain knowledge graph is not broadly covered in the field,the precision of the knowledge is better than with an open knowledge graph.Despite the fact that open knowledge graphs have made significant advancements in recent years,vertical fields-especially business-have not seen in-depth applications in practice;this has resulted in significant demands on the enterprise knowledge graph.This paper proposes a Chinese entity relation extraction method based on classification for the limitation of extraction results.In this method,the maximum entropy model is used to analyze the data of selected companies' announcements to determine the optimal feature template.The results show that accuracy rates reach over 85％ in the enterprise bulletin data set.关键词
企业知识图谱/实体关系抽取/最大熵模型Key words
enterprise knowledge graph/named entity relation extraction/maximum entropy分类
信息技术与安全科学引用本文复制引用
孙晨,付英男,程文亮,钱卫宁..面向企业知识图谱构建的中文实体关系抽取[J].华东师范大学学报（自然科学版）,2018,(3):55-66,12.基金项目
国家重点研发计划(2016YFB1000905) （2016YFB1000905）
国家自然科学基金广东省联合重点项目(U1401256) （U1401256）
国家自然科学基金(61672234,61402177) （61672234,61402177）
华东师范大学信息化软科学研究课题(41600-10201-562940/018). （41600-10201-562940/018）
