The effect of using Naive Bayes to detect spam email - Sun Zehui (ITM Web of Conferences)
The rapid growth of the Internet has made email a huge help in business, life, and education. However, it has also become a channel for spreading undesirable information, such as content from hackers, viruses, violence, pornography, and superstition. Spam, which is unsolicited commercial email, often carries such undesirable information. It wastes network bandwidth, consumes users’ precious time, and interferes with normal life. Therefore, spam detection and filtering have become especially urgent and of great practical importance. This paper focuses on the spam detection method based on the plain Bayesian algorithm. The plain Bayesian algorithm is particularly suitable for spam detection due to its high detection accuracy and its wide application in text classification tasks. The results and analysis of the experimental dataset demonstrate that the accuracy of Park’s Bayesian algorithm in spam detection reaches an impressive 99.193%. This high level of accuracy underscores the effectiveness of the Bayesian approach in identifying and filtering out spam, thereby enhancing the overall efficiency and security of email communication.