计算机工程与应用2018，Vol.54Issue(9)：145-150,6.DOI:10.3778/j.issn.1002-8331.1710-0153
基于三支决策的两阶段实体关系抽取研究
Research on two-stage entity relation extraction based on three-way decisions
摘要
Abstract
As one of the important research topics in information extraction, entity relationship extraction is of great significance to the construction of knowledge graph data layer.This paper proposes a two-stage classification technique based on three-way decisions to extract the entity relationship.Firstly,the SVM three-decisions classifier is constructed to implement the first phase entity relation extraction.The softmax multi-class function is used as a probability function of three-way decisions,Then, the KNN classifier is used to classify the three-way decisions middle domain sample into two-stage classification.According to the corpus of ACE2005 as the experimental data,the results of the three-way decisions two-stage classification are compared with the traditional SVM method.The experimental results show that the two-stage entity relation extraction method based on three-way decisions has achieved good classification effect.关键词
实体关系抽取/三支决策/支持向量机(SVM)/K最近邻(KNN)/softmax函数Key words
entity relation extraction/three-way decisions/Support Vector Machine(SVM)/K-Nearest Neighbor(KNN)/softmax function分类
信息技术与安全科学引用本文复制引用
朱艳辉,李飞,胡骏飞,钱继胜,王天吉..基于三支决策的两阶段实体关系抽取研究[J].计算机工程与应用,2018,54(9):145-150,6.基金项目
国家自然科学基金(No.61402165) （No.61402165）
模式识别国家重点实验室开放课题(No.201700009) （No.201700009）
湖南省教育厅重点项目(No.15A049) （No.15A049）
湖南工业大学重点项目(No.17ZBLWT001KT006) （No.17ZBLWT001KT006）
湖南省研究生创新基金(No.CX2017B688). （No.CX2017B688）
