期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2012
卷号：2
期号：4
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Automatic text categorization (ATC) is a prominent research area within Information retrieval. Through this 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.
关键词：Automatic text categorization; Multi-label text classification; graph based framework ; semi supervised;learning.
