NDLI: A Fusion of Multiple Classifiers Approach Based on Reliability function for Text Categorization

Content Provider	IEEE Xplore Digital Library
Author	Qingxuan Chen Dequan Zheng Tiejun Zhao Sheng Li
Copyright Year	2008
Description	Author affiliation: MOE-MS Key Lab. of Natural Language Process. & Speech, Harbin Inst. of Technol., Harbin (Qingxuan Chen; Dequan Zheng; Tiejun Zhao; Sheng Li)
Abstract	With the development of Internet and the rapid expansion of electronic resource, text classification technology is becoming an effective organization and management tool to deal with information. In this paper, a method for text categorization based on the fusion of multiple classifiers was presented, reliability function was introduction to select the text that hard to give determine by the main classifier, for these texts, multiple classifiers were used to give the determine which category the unlabeled documents belong to by voting. Experiments showed that the performance of text classification improved by the proposed method. Compared with single classifier, this method achieved better performance, only increasing a small amount of time than using single main classifier. Besides this, this method is more stable than using single classifier for text categorization task, especially when using different corpuses to check the performance of various methods.
Starting Page	338
Ending Page	342
File Size	245050
Page Count	5
File Format	PDF
ISBN	9780769533056
DOI	10.1109/FSKD.2008.373
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Laboratories text categorization reliability function Support vector machines Voting Text categorization Support vector machine classification Frequency shift keying Natural language processing Internet multiple classifiers Speech processing Fuzzy systems main classifier
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library 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

Hierarchical Text Categorization Based on Multiple Feature Selection and Fusion of Multiple Classifiers Approaches

Opinion analysis based on a fusion of multiple classifiers approach

Digital modulation recognition using support vector machine classifier

Combining Multiple SVM Classifiers for Radar Emitter Recognition

Combining Multiple Support Vector Machines using Fuzzy Integral for Classification

An approach of multi-hierarchy text classification

One-against-one fuzzy support vector machine text categorization classifier

A Weighting Approach for Features Based on Real Rough Set

Classification Based on Specific Vocabulary

A Fusion of Multiple Classifiers Approach Based on Reliability function for Text Categorization

Similar Documents

Hierarchical Text Categorization Based on Multiple Feature Selection and Fusion of Multiple Classifiers Approaches

Opinion analysis based on a fusion of multiple classifiers approach

Digital modulation recognition using support vector machine classifier

Combining Multiple SVM Classifiers for Radar Emitter Recognition

Combining Multiple Support Vector Machines using Fuzzy Integral for Classification

An approach of multi-hierarchy text classification

One-against-one fuzzy support vector machine text categorization classifier

A Weighting Approach for Features Based on Real Rough Set

Classification Based on Specific Vocabulary

A Fusion of Multiple Classifiers Approach Based on Reliability function for Text Categorization