Call For Paper Volume:4 Issue:10 Oct'2017 |

SMS Classification Based on Naïve Bayes Classifier and Semi-supervised Learning

Publication Date : 07/03/2016



Author(s) :

Sheetal Ashokrao Sable , Prof.P.N. Kalavadekar.


Volume/Issue :
Volume 3
,
Issue 2
(03 - 2016)



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 spam or ham, using various algorithms such as Naïve Bayes classifier and Apriori Algorithm. So there is need to perform SMS collection, feature selection, preprocessing, 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. Naïve 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.


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SMS Classification Based on Naïve Bayes Classifier and Semi-supervised Learning

February 25, 2016