NDLI: Fast text classification: a training-corpus pruning based approach

Content Provider	IEEE Xplore Digital Library
Author	Shuigeng Zhou Tok Wang Ling Jihong Guan Jiangtao Hu Aoying Zhou
Copyright Year	2003
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Fudan Univ., Shanghai, China (Shuigeng Zhou)
Abstract	With the rapid growth of on-line information available, text classification is becoming more and more important. kNN is a widely used text classification method of high performance. However, this method is inefficient because it requires a large amount of computation for evaluating the similarity between a test document and each training document. In this paper, we propose a fast kNN text classification approach based on pruning the training corpus. By using this approach, the size of training corpus can be condensed sharply so that time-consuming on kNN searching can be cut off significantly, and consequently classification efficiency can be improved substantially while classification performance is preserved comparable to that of without pruning. Effective, algorithm for text corpus pruning is designed. Experiments over the Reuters corpus are carried out, which validate the practicability of the proposed approach. Our approach is especially suitable for on-line text classification applications.
Sponsorship	Commun. Res. Lab. Hitachi Kyoto Univ
Starting Page	127
Ending Page	136
File Size	464536
Page Count	10
File Format	PDF
ISBN	0769518958
DOI	10.1109/DASFAA.2003.1192376
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-03-26
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Text categorization Testing High performance computing Information retrieval Content based retrieval Machine learning Computer science Drives Algorithm design and analysis Supervised learning
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	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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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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