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Received:April 10, 2017 Revised:April 26, 2017
Received:April 10, 2017 Revised:April 26, 2017
中文摘要: 科学技术的进步，推进着军事武器装备的快速更新. 在高度信息化的时代，急需智能化军事信息处理技术. 本文针对飞行器、坦克车辆、火炮弹炮、导弹武器等军事文本中的武器命名实体，提出了基于词向量、词状态的特征，利用深度神经网络模型的识别方法. 实验表明：在测试语料上取得F-1值0.9102的效果.
Abstract:The development of computer science makes military weapons and equipment update fast. In the highly-informed society, the intelligent information processing technology in military, is badly needed. This paper proposes an identification method with the model of deep neural network based on the character of word vector and state. It's for weaponry in electronic text, such as aircraft, tank vehicle, artillery missile and missile weapon. The experiment shows the value of F-1 which equals 0.9102 on the test corpus.
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游飞,张激,邱定,于铭华.基于深度神经网络的武器名称识别.计算机系统应用,2018,27(1):239-243
YOU Fei,ZHANG Ji,QIU Ding,YU Ming-Hua.Weapon Named Entity Recognition Based on Deep Neural Network.COMPUTER SYSTEMS APPLICATIONS,2018,27(1):239-243
游飞,张激,邱定,于铭华.基于深度神经网络的武器名称识别.计算机系统应用,2018,27(1):239-243
YOU Fei,ZHANG Ji,QIU Ding,YU Ming-Hua.Weapon Named Entity Recognition Based on Deep Neural Network.COMPUTER SYSTEMS APPLICATIONS,2018,27(1):239-243
