Volume 3, Issue 7

SMS CLASSIFICATION BASED ON NAIVE BAYES CLASSIFIER AND SEMI-SUPERVISED LEARNING (140926)

DOI :

Abstract : 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 spamor ha m,using various algorithms such as Na´ve 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 exist s in current mobile phone and they are enlisted as Black and White. Na´ve 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.

Pages : 16-25

Downloads : 1584

Publication Date :

Modified Date : 2016-07-20

Cite/Export :

SHEETAL ASHOKRAO SABLE , PROF. P.N. KALAVADEKAR , "SMS CLASSIFICATION BASED ON NAIVE BAYES CLASSIFIER AND SEMI-SUPERVISED LEARNING", IJIERT - International Journal of Innovations in Engineering Research and Technology, Volume 3, Issue 7, ISSN : 2394-3696, Page No. 16-25