NDLI: Clustering by data competition

Content Provider	Springer Nature Link
Author	Lu, ZhiMao Zhang, Qi
Copyright Year	2012
Abstract	Clustering analysis is an unsupervised method to find out hidden structures in datasets. Most partitional clustering algorithms are sensitive to the selection of initial exemplars, the outliers and noise. In this paper, a novel technique called data competition algorithm is proposed to solve the problems. First the concept of aggregation field model is defined to describe the partitional clustering problem. Next, the exemplars are identified according to the data competition. Then, the members will be assigned to the suitable clusters. Data competition algorithm is able to avoid poor solutions caused by unlucky initializations, outliers and noise, and can be used to detect the coexpression gene, cluster the image, diagnose the disease, distinguish the variety, etc. The provided experimental results validate the feasibility and effectiveness of the proposed schemes and show that the proposed approach of data competition algorithm is simple, stable and efficient. The experimental results also show that the proposed approach of data competition clustering outperforms three of the most well known clustering algorithms K-means clustering, affinity propagation clustering, hierarchical clustering.
Starting Page	1
Ending Page	13
Page Count	13
File Format	PDF
ISSN	1674733X
Journal	Science in China Series : Information Sciences
Volume Number	56
Issue Number	1
e-ISSN	18691919
Language	English
Publisher	SP Science China Press
Publisher Date	2012-08-17
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	data mining clustering analysis partitional clustering data competition Information Systems and Communication Service
Content Type	Text
Resource Type	Article
Subject	Computer Science

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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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