JOURNAL ARTICLE

Study of Chinese spam filtering Based on Improved Naive Bayesian Classification Algorithm

Kaiying Zuo

Year: 2021 Journal:   Journal of Physics Conference Series Vol: 2083 (4)Pages: 042079-042079   Publisher: IOP Publishing

Abstract

Abstract Spam is a growing threat to mobile communications. This paper puts forward some mitigation technologies, including white list and blacklist, challenge response and content-based filtering. However, none are perfect and it makes sense to use an algorithm with higher accuracy for classification. Bayesian classification method shows high accuracy in spam processing, so it has attracted extensive attention. In this paper, a Bayesian classification method based on annealing evolution algorithm is introduced into Chinese spam filtering to improve the accuracy of classification. Our simulation results show that the algorithm has better performance in spam filtering.

Keywords:
Blacklist Computer science Naive Bayes classifier Simulated annealing Bayesian probability Statistical classification Data mining Artificial intelligence Machine learning Algorithm Pattern recognition (psychology) Support vector machine

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Citation History

Topics

Spam and Phishing Detection
Physical Sciences →  Computer Science →  Information Systems
Network Security and Intrusion Detection
Physical Sciences →  Computer Science →  Computer Networks and Communications
Internet Traffic Analysis and Secure E-voting
Physical Sciences →  Computer Science →  Artificial Intelligence
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