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General Information
    • ISSN: 2010-3700 (Online)
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

IJMLC 2012 Vol.2(4): 423-426 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2012.V2.158

A Comparative Study on Different Types of Approaches to Text Categorization

Pratiksha Y. Pawar and S. H. Gawande

Abstract—Text Categorization is a pattern classification task for text mining and necessary for efficient management of textual information systems. The documents can be classified by three ways unsupervised, supervised and semi supervised methods. Text categorization refers to the process of assign a category or some categories among predefined ones to each document, automatically. This paper presents a comparative study on different types of approaches to text categorization.

Index Terms—Text categorizatin, classifier, documents.

Authors are with the Department of Computer Engineering, Government College of Engineering & Research, Awasari, Pune, India (e-mail: patu_pawar@yahoo.co.in; shgawande@yahoo.co.in)


Cite: Pratiksha Y. Pawar and S. H. Gawande, "A Comparative Study on Different Types of Approaches to Text Categorization," International Journal of Machine Learning and Computing vol. 2, no. 4, pp. 423-426, 2012.

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