Proceedings of the 2nd International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2023, June 2–4, 2023, Nanchang, China

Research Article

Research on Criminal Law Response to Telecom Network Fraud based on Natural Language Processing Algorithm

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  • @INPROCEEDINGS{10.4108/eai.2-6-2023.2334619,
        author={Yunliang  Sun and Dianyong  Yu},
        title={Research on Criminal Law Response to Telecom Network Fraud based on Natural Language Processing Algorithm},
        proceedings={Proceedings of the 2nd International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2023, June 2--4, 2023, Nanchang, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2023},
        month={8},
        keywords={telecom fraud; machine learning; natural language processing},
        doi={10.4108/eai.2-6-2023.2334619}
    }
    
  • Yunliang Sun
    Dianyong Yu
    Year: 2023
    Research on Criminal Law Response to Telecom Network Fraud based on Natural Language Processing Algorithm
    ICIDC
    EAI
    DOI: 10.4108/eai.2-6-2023.2334619
Yunliang Sun1,*, Dianyong Yu1
  • 1: Shan Dong University
*Contact email: 2895399190@qq.com

Abstract

Telecom network fraud is one of the serious problems facing the society today. In this digital age, Internet fraud has become a criminal means, and many people cheat through Internet fraud. Therefore, how to deal with telecom network fraud has become one of the important challenges facing the current judicial organs. This paper proposes a criminal law response to telecom network fraud based on natural language processing algorithm. The algorithm includes text classification, keyword extraction, information extraction, entity recognition and other technologies, which can effectively identify and judge the key information and characteristics in telecom network fraud cases, improve the ac-curacy and efficiency of the judgment. To sum up, this paper proposes a study of criminal law response to telecom network fraud based on natural language processing algorithm, which can effectively identify and judge the key information and characteristics of telecom network fraud cases and improve the accuracy and efficiency of judgment.