Mobile SMS Classification an Application of Text Classification
Deepshikha Patel1, Monika Bhatnagar2

1Deepshikha Patel, Information Technology, Rajeev Gandhi Technical University, Bhopal, India.
2Monika Bhatnagar, Information Technology, Rajeev Gandhi Technical University, Bhopal, India.
Manuscript received on February 24, 2011. | Revised Manuscript received on March 02, 2011. | Manuscript published on March 05, 2011. | PP: 47-49 | Volume-1 Issue-1, March 2011. | Retrieval Number: A013021111
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Abstract: Text Classification is the process of classifying documents into predefined classes based on its content. Text classification is important in many web applications like document indexing, document organization, spam filtering etc. In this paper we analyze the concept of a new classification model which will classify Mobile SMS into predefined classes such as jokes, shayri, festival etc. All sms are converted into text documents. After preprocessing vector space model is prepared and weight is assigned to each term. In the proposed model we have used entropy term weighting scheme and then PCA is used for reparameterization. Artificial Neural Network is used for classification.
Keywords: Text Classification, Short messaging service (sms), feature selection, Principal Component Analysis, Neural Network.