SMS Classification Based on Naive Bayes Classifier and Apriori Algorithm Frequent Itemset
As the mobile phone market is rapidly expanding and the modern life is heavily dependent on cell phones, Short Message Service (SMS) has become one of the important media of communications. In this paper, the authors propose a hybrid system of SMS classification to detect spam or ham, using Naive Bayes classifier and Apriori algorithm. Though this technique is fully logic based, its performance will rely on statistical character of the database. Naive Bayes is considered as one of the most effectual and significant learning algorithms for machine learning and data mining and also has been treated as a core technique in information retrieval.