%0 Journal Article
%T A Novel Multi label Text Classification Model using Semi supervised learning
%A Shweta C. Dharmadhikari
%A Maya Ingle
%A Parag Kulkarni
%J International Journal of Data Mining & Knowledge Management Process
%D 2012
%I Academy & Industry Research Collaboration Center (AIRCC)
%X Automatic text categorization (ATC) is a prominent research area within Information retrieval. Throughthis paper a classification model for ATC in multi-label domain is discussed. We are proposing a new multi label text classification model for assigning more relevant set of categories to every input text document. Our model is greatly influenced by graph based framework and Semi supervised learning. We demonstrate the effectiveness of our model using Enron , Slashdot , Bibtex and RCV1 datasets. Our experimental results indicate that the use of Semi Supervised Learning in MLTC greatly improves the decision making capability of classifier.
%K Automatic text categorization
%K Multi-label text classification
%K graph based framework
%K semi supervised learning.
%U http://airccse.org/journal/ijdkp/papers/2412ijdkp02.pdf