摘 要
本文以基于机器学习的垃圾邮件过滤算法研究为主题，探讨了垃圾邮件的定义、危害以及垃圾邮件过滤的重要性。首先介绍了垃圾邮件过滤的方法和机器学习算法的概述，包括传统机器学习算法和深度学习算法。然后详细研究了传统机器学习算法和深度学习算法在垃圾邮件过滤中的应用，并对不同算法的性能和优缺点进行了对比分析。接着讨论了垃圾邮件过滤存在的问题，包括误判率与漏判率问题、特征提取与选择问题以及实时性与适应性问题。最后提出了基于机器学习的垃圾邮件过滤的对策，包括特征选择与提取、模型优化与调参以及实时更新与适应性。本研究对于提高垃圾邮件过滤的准确率和实时性具有重要意义。
关键词：垃圾邮件 机器学习 过滤算法
Abstract
This paper takes the research of spam filtering algorithm based on machine learning as the theme, discusses the definition, harm and importance of spam filtering. Firstly, the paper introduces the methods of spam filtering and the overview of machine learning algorithms, including traditional machine learning algorithms and deep learning algorithms. Then, the application of traditional machine learning algorithm and deep learning algorithm in spam filtering is studied in detail, and the performance and advantages and disadvantages of different algorithms are compared and analyzed. Then, the problems of spam filtering are discussed, including misjudgment rate and omission rate, feature extraction and selection, real-time performance and adaptability. Finally, the countermeasures of spam filtering based on machine learning are proposed, including feature selection and extraction, model optimization and tuning, real-time update and adaptability. This study is of great significance for improving the accuracy and real-time performance of spam filtering.
Keywords: Spam machine learning filtering algorithms
目 录
1 引言 1
2 理论基础 1
2.1 垃圾邮件的定义和危害 1
2.2 垃圾邮件过滤的重要性 2
2.3 机器学习在垃圾邮件过滤中的应用现状 2
3 相关技术概述 3
3.1 垃圾邮件过滤方法 3
3.2 机器学习算法 3
4 基于机器学习的垃圾邮件过滤算法研究 4
4.1 传统机器学习算法在垃圾邮件过滤中的应用 4
4.2 深度学习算法在垃圾邮件过滤中的应用 4
4.3 对比分析不同算法的性能和优缺点 4
5 垃圾邮件过滤存在的问题 5
5.1 误判率与漏判率问题 5
5.2 特征提取与选择问题 5
5.3 实时性与适应性问题 5
6 基于机器学习的垃圾邮件过滤对策 5
6.1 特征选择与提取 5
6.2 模型优化与调参 6
6.3 实时更新与适应性 6
5 结论 7
致 谢 8
参考文献 9
