Open AccessRecognition of Spam Messages Based on Text Mining
Author(s) -
Yajie Fang,
Ping Zhang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1624/5/052024
Subject(s) - artificial intelligence , computer science , machine learning , naive bayes classifier , big data , support vector machine , decision tree , value (mathematics) , data mining
With the rapid development of science and technology, the application of artificial intelligence technology is becoming more and more extensive. The maturity of artificial intelligence technology is inseparable from big data and machine learning. Big data is the foundation of artificial intelligence, while machine learning is the core. To mine the value hidden in big data, in order to achieve text classification, data prediction, and provide strategic decision basis, we need the power of Machine Learning. This article will introduce the classic algorithm in machine learning, Naive Bayes, KNN nearest neighbor, and support vector machine algorithm, and apply them to text mining of spam text sets. It shows that Machine Learning is the fundamental way to make machines as intelligent as humans.