指挥控制与仿真2016，Vol.38Issue(4)：58-63,6.DOI:10.3969/j.issn.1673-3819.2016.04.013
结合词语规则和 SVM 模型的军事命名实体关系抽取方法∗
A Military Named Entities Relation Extraction Method Based on SVM Integrated with Word Rules
摘要
Abstract
The semantic extraction of operation document can benefit the option of operation processing, and a core technol-ogy in the semantic extraction is Military Named Entities (MNEs) and their relationships discovery. In this paper, we pro-posed a MNEs relation extraction method, which integrated the word rules and SVM model. We first combined the successive MNEs with word rules, which is an important preprocessing of SVM model. Then we modeled some features of MNEs rela-tion, such as word windows, POS and distances which cannot be implemented conveniently in traditional rule template. Ex-periments show that, the performance of our method to MNEs relation extraction can be improved obviously, the precise and recall rate is 8. 73% and 41. 71% higher than simple SVM model.关键词
军事命名实体/SVM 模型/实体关系抽取/词语规则Key words
military named entity/SVM/entity relation extraction/word rules分类
信息技术与安全科学引用本文复制引用
单赫源,吴照林,张海粟,刘培磊..结合词语规则和 SVM 模型的军事命名实体关系抽取方法∗[J].指挥控制与仿真,2016,38(4):58-63,6.基金项目
国防预研基金项目 （）
