NDLI: News story clustering using L-GEM based RBFNN

Content Provider	IEEE Xplore Digital Library
Author	Ng, W.W.Y. Xin Ran Chan, P.P.K. Yeung, D.S.
Copyright Year	2011
Description	Author affiliation: Machine Learning and Cybernetic Research Center, School of Computer Science and Engineering, South China University of Technology, Guangzhou, China (Ng, W.W.Y.; Xin Ran; Chan, P.P.K.; Yeung, D.S.)
Abstract	With the explosive growth of video resources on the Internet and Internet connected mobile devices, the needs of efficient video retrieval and video clustering are increasing. Video clustering is important because video resources on the Internet may be duplicate and highly similar. To reduce the use of bandwidth, users would like to fetch only one representative video resource instead of a number of highly similar or duplicated videos. In this paper, we first summarize current research development of video retrieval. Then, we propose a new video clustering method based on a Radial Basis Function Neural Network (RBFNN) trained via a minimization of the Localized Generalization Error (L-GEM). The L-GEM provides estimation on the generalization capability of the RBFNN which helps to cluster news video from different channels with higher accuracy. Experimental results show that the proposed method outperforms RBFNN trained without the L-GEM.
Starting Page	85
Ending Page	90
File Size	431535
Page Count	6
File Format	PDF
ISBN	9781457703058
ISSN	21601348
e-ISBN	9781457703089
DOI	10.1109/ICMLC.2011.6016747
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training TV Neurons Mobile handsets Internet Machine learning Cybernetics Radial basis function neural networks (RBFNN) Video clustering Localized Generalization Error Model (L-GEM)
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
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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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