关于垃圾短信识别的外文文献

以下是几篇关于垃圾短信识别的外文文献：

1. "A review of machine learning approaches to spam filtering" by T. F. Ahmed, M. S. Hossain, M. A. Matin, and M. A. Islam. This paper provides an overview of various machine learning techniques used for spam filtering, including Naive Bayes, Support Vector Machines (SVM), and Random Forest.

2. "A survey of techniques for email spam filtering" by S. Al-Subaihin and M. Al-Salman. This paper discusses different techniques for email spam filtering, including rule-based methods, content-based filtering, and machine learning approaches.

3. "Spam detection using machine learning techniques: a review" by S. U. Khan and K. A. Khan. This paper provides a review of different machine learning techniques used for spam detection, including Decision Trees, Naive Bayes, and Artificial Neural Networks.

4. "Comparing machine learning algorithms for spam email classification" by T. A. Alghamdi and H. M. Alshammari. This paper compares the effectiveness of different machine learning algorithms, including Naive Bayes, SVM, and k-Nearest Neighbor (k-NN), for spam email classification.

5. "A hybrid approach for spam detection using machine learning and rule-based techniques" by A. Alazzawi and S. Albahadily. This paper proposes a hybrid approach that combines both machine learning and rule-based techniques for more accurate spam detection.

这些文献可以帮助你深入了解垃圾短信识别技术的发展和应用。