NDLI: A novel feature selection based on information gain using WordNet

Content Provider	IEEE Xplore Digital Library
Author	Patil, L.H. Atique, M.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Sant Gadge Baba Amravati Univ., Amravati, India (Patil, L.H.; Atique, M.)
Abstract	Text Classification and Feature Selection are mostly used for organizing the text document in the digitized form. Due to the enormous increased in number of documents in digitized form, text categorization and feature selection approach becomes most important and promising in the last decades. The problem arises for text categorization is the large number of features available in the document. Now a day, with the rapid speed in development of web large numbers of documents are available on the internet. Digital libraries, news article, magazines, World Wide Web and large companies surge more and more. However the major problem is the high dimensionality of data. Most of the features are noisy, redundant which misleads for classifier. Therefore to reduce the dimensionality of the feature space and improve the performance and accuracy of text categorization, feature selection becomes an important parameter. In this paper we discuss how document preprocessing and feature selection approaches are useful for dimensionality reduction. To deal with the massive amount of data, document preprocessing and feature selection methods become an important parameter for dimensionality reduction. Until now large number of methods deals with feature selection approaches. Still the problems arise of attribute reduction, therefore to improve the performance a hybrid method has been designed for feature selection. Our approaches is on document preprocessing and selects the important feature with information gain based on entropy and calculate the probability of class to reduce the high dimensionality of the feature.
Starting Page	625
Ending Page	629
File Size	889583
Page Count	5
File Format	PDF
ISBN	9780989319300
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-07
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	The Science and Information Organization
Subject Keyword	Computer science Databases Information gain Text categorization Introduction Document preprocessing Feature extraction Knowledge discovery Entropy Feature selection approaches
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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	Mr. Siddhartha Mukherjee siddhartha@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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	ndl-support@iitkgp.ac.in
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7	National Digital Libarray of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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