NDLI: Hybrid Intelligent Technique for Text Categorization

Content Provider	IEEE Xplore Digital Library
Author	Sadiq, A.T. Abdullah, S.M.
Copyright Year	2012
Abstract	Text categorization is the task in which documents are classified into one or more of predefined categories based on their contents. This paper shows that the proposed system consists of three main steps: document representation, classifier construction and performance evaluation. In the first step, a set of pre-classified documents is provided. Input documents are initially pre-processed in order to be split into features and eliminate non-informative features. The remaining features are next weighted based on the frequency of each feature in that document and standardized by reducing a feature to its root using the stemming process. Due to the large number of features even after the non-informative features removal and the stemming process, the proposed system applies specific thresholds to extract distinct features which represent the input document. In the second step, the text categorization model (classifier) is built by learning the distinct features which represent all the pre-classified documents, this process can be achieved by using one of the supervised classification techniques that is called the rough set theory. The model uses a pair of precise concepts from the above theory that are called lower and upper approximations to classify any test document into one or more of main categories and sub-categories. In the final step, the performance of the proposed system is evaluated. It has achieved good results up to 96%, when applied to a number of test documents for each sub-category of main categories.
Starting Page	238
Ending Page	245
File Size	192442
Page Count	8
File Format	PDF
ISBN	9781467358323
e-ISBN	9780769549590
DOI	10.1109/ACSAT.2012.50
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-26
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Text Mining Rough Set Theory Text Categorization
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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