NDLI: Transfer learning based maximum entropy clustering

Content Provider	IEEE Xplore Digital Library
Author	Shouwei Sun Yizhang Jiang Pengjiang Qian
Copyright Year	2014
Description	Author affiliation: Sch. of Digital Media, Jiangnan Univ., Wuxi, China (Shouwei Sun; Yizhang Jiang; Pengjiang Qian)
Abstract	The classical maximum entropy clustering (MEC) algorithm can only work on a single dataset, which might result in poor effectiveness in the condition that the capacity of the dataset is insufficient. To resolve this problem, using the strategy of transfer learning, this paper proposed the novel transfer learning based maximum entropy clustering (TL_MEC) algorithm. TL_MEC employs the historical cluster centers and membership of the past data as the references to guide the clustering on the current data, which promotes its performance distinctly from three aspects: clustering effectiveness, anti-noise, as well as privacy protection. Thus TL_MEC can work well on those small dataset if enough historical data are available. The experimental studies verified and demonstrated the contributions of this study.
Starting Page	829
Ending Page	832
File Size	107834
Page Count	4
File Format	PDF
e-ISBN	9781479948086
DOI	10.1109/ICIST.2014.6920605
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-04-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Knowledge Transfer Privacy Source domain privacy protection Maximum Entropy Clustering (MEC) Clustering algorithms Educational institutions Linear programming Entropy Transfer Rules Equations
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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