A method to recognize spams based on Dynamic-LSTM

Zhixuan Xiao; Suyao Zhao; RuiHeng Liu; YiXiang Zhang; AngAng Feng; RunJiu Hu

doi:10.1117/12.2637102

15 June 2022 A method to recognize spams based on Dynamic-LSTM

Zhixuan Xiao, Suyao Zhao, RuiHeng Liu, YiXiang Zhang, AngAng Feng, RunJiu Hu

Proceedings Volume 12285, International Conference on Advanced Algorithms and Neural Networks (AANN 2022); 122850O (2022) https://doi.org/10.1117/12.2637102
Event: International Conference on Advanced Algorithms and Neural Networks (AANN 2022), 2022, Zhuhai, China

Abstract

Nowadays, people are increasingly inseparable from electronic communication tools. Email is one of the important means of communication, but the existence of spams seriously affects the users' usage. This paper focuses on the spam classification problem in a practical context. Real email messages are collected and the classification is performed using the Dynamic_LSTM model. By comparing with algorithms of traditional machine learning as well as ordinary RNN, it is shown that the accuracy of Dynamic_LSTM is increased by 8%.In addition, it is not affected by the max-feature. The experimental results show that the Dynamic_LSTM model performs better at the classification accuracy.

Citation Download Citation

Zhixuan Xiao, Suyao Zhao, RuiHeng Liu, YiXiang Zhang, AngAng Feng, and RunJiu Hu "A method to recognize spams based on Dynamic-LSTM", Proc. SPIE 12285, International Conference on Advanced Algorithms and Neural Networks (AANN 2022), 122850O (15 June 2022); https://doi.org/10.1117/12.2637102

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