NDLI: Parallel K-Medoids clustering algorithm based on Hadoop

Content Provider	IEEE Xplore Digital Library
Author	Yaobin Jiang Jiongmin Zhang
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Sci. & Technol., East China Normal Univ., Shanghai, China (Yaobin Jiang; Jiongmin Zhang)
Abstract	The K-Medoids clustering algorithm solves the problem of the K-Means algorithm on processing the outlier samples, but it is not be able to process big-data because of the time complexity[1]. MapReduce is a parallel programming model for processing big-data, and has been implemented in Hadoop. In order to break the big-data limits, the parallel K-Medoids algorithm HK-Medoids based on Hadoop was proposed. Every submitted job has many iterative MapReduce procedures: In the map phase, each sample was assigned to one cluster whose center is the most similar with the sample; in the combine phase, an intermediate center for each cluster was calculated; and in the reduce phase, the new center was calculated. The iterator stops when the new center is similar to the old one. The experimental results showed that HK-Medoids algorithm has a good clustering result and linear speedup for big-data.
Starting Page	649
Ending Page	652
File Size	140593
Page Count	4
File Format	PDF
ISBN	9781479932788
ISSN	23270594
e-ISBN	9781479932795
DOI	10.1109/ICSESS.2014.6933652
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Computational modeling Clustering algorithms Hadoop Programming Educational institutions Partitioning algorithms Indexes Clustering Analysis K-Medoids Big-Data MapReduce
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
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