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| Entity Recognition of Intelligence Method Based on Deep Learning: Taking Area of Security Intelligence for Example |
Lianjie Xiao1,2( ),Tao Meng1,2,Wei Wang1,2,Zhixiang Wu3 |
1School of Information Management, Nanjing University, Nanjing 210023, China
2Jiangsu Key Laboratory of Data Engineering and Knowledge Service, Nanjing 210023, China
3School of Economics and Management, Nanjing University of Technology, Nanjing 211800, China |
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Abstract [Objective] This paper provides directions for a new scholarly system, aiming to identify and summarize intelligence analysis methods for security intelligence. [Methods] Firstly, we retrieved full-text security intelligence literature, and tagged them using Character-level method. Then, we constructed the corpus for the extraction of intelligence analysis methods. Finally, we compared the performance of two deep learning models with the experimental data. [Results] For the BiLSTM model, the precision, recall and F1 values were 81.71%, 77.26%, and 79.36% respectively. For the BiLSTM-CRF model, the precision, recall and F1 values were 84.71%, 79.25%, and 81.83%. [Limitations] The pronouns that represent intelligence analysis methods are not taken into consideration. [Conclusions] We could use deep learning model to extract intelligence analysis methods for security intelligence.
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Received: 29 October 2018
Published: 25 November 2019
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Corresponding Authors:
Lianjie Xiao
E-mail: 1061939301@qq.com
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