基于属性词补全的武器装备属性抽取研究  

Extracting Weapon Attributes Based on Word Completion

作　　者：丁晟春[1] 游伟静 王小英 Ding Shengchun;You Weijing;Wang Xiaoying(School of Economics and Management,Nanjing University of Science and Technology,Nanjing 210094,China)

机构地区：[1]南京理工大学经济管理学院,南京210094

出　　处：《数据分析与知识发现》2022年第2期289-297,共9页Data Analysis and Knowledge Discovery

基　　金：江苏省社会科学基金项目(项目编号:20TQB004)的研究成果之一。

摘　　要：【目的】解决军事领域基于依存句法关系只能抽取单名词武器装备属性词的问题。【方法】分析描述武器装备技术和性能属性文本的特征,编写正则表达式获取属性值,再基于依存句法分析抽取属性词,最后依据词性将属性词补全。【结果】在军事新闻数据集上进行实验,开源属性词抽取的准确率和召回率分别达到91.53%和72.78%;属性词补全的准确率高达96.95%,且每种类别属性词的准确率均高于90%。【局限】武器装备除了有技术和性能属性,还有所属国家、服役状态等基础属性,而本研究并未涉及。【结论】实验结果表明,本文所提基于词性补全属性词的方法是可行且高效的,应用此方法能够获得含义更加明确的属性词。[Objective]This paper tries to address the issue facing dependency syntactic relation,which could only extract single noun attributes for military equipment.[Methods]First,we analyzed features of the text describing the technology and performance of weapons and equipment.Then,we wrote regular expressions to obtain the attribute values.Third,we extracted the attribute words based on dependency parsing.Finally,we completed the attribute word lists with the part of speech.[Results]We examined our new model with military news data sets and found the accuracy and recall rates for extracting open-source attribute words reached 91.53%and 72.78%.The accuracy of attribute word completion was up to 96.95%,and the accuracy for each category of attribute words was higher than 90%.[Limitations]This paper did not try to extract weapon attributes like the belonging country and the state of service.[Conclusions]The proposed method could effectively extract explicit attribute words.

关 键 词：武器装备 属性抽取 属性词补全 依存句法 

分 类 号：E91[军事] TP391[自动化与计算机技术—计算机应用技术]