SMS Classification Based on Naive Bayes Classifier and Semi supervised Learning
Short Message Service is one of the most important media of communication due to the rapid increase of mobile users. A hybrid system of SMS classification is used to detect spam or ham, using various algorithms such as Naive Bayes classifier and Apriori Algorithm. So there is needed to perform SMS collection, feature selection, pre processing, vector creation, filtering process and updating system. Two types of SMS classification exists in current mobile phone and they are enlisted as Black and White. Naive Bayes is considered as one of the most effectual and significant learning algorithms for data mining and machine learning and also has been treated as a core technique in information retrieval. KEYWORDS Short Message Service (SMS) Naive Bayes; Apriori algorithm; ham; spam.