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Paper Abstract and Keywords
Presentation 2013-02-21 14:30
Memory Efficient K-means Clustering Using HDD
Hiroshi Oike, Kazuyoshi Kishi, Toshikazu Wada (Wakayama Univ.) PRMU2012-140
Abstract (in Japanese) (See Japanese page) 
(in English) This report presents an “external” k-means clustering on HDD. K-means clustering is widely used for many applications. For example, codebook creation for Bag of Visual Words requires k-means clustering on huge amount of local feature vectors to obtain Visual Words (codebook entries). Standard “internal” k-means clustering loads the whole vector data on the main memory and performs clustering. This working memory can explode for huge amount of data. As a solution of this problem, we propose an “external” clustering algorithm on HDD. This is a multi-path algorithm, which scans the whole data in each path. In the first stage, cluster centroids are updated gradually, providing the data sequentially. Through this path, the number and the sum of the data are recorded for each cluster, and the belonging cluster is recorded for each data. In the following paths, each data is provided and the cluster center is updated for those data that changes belonging cluster. By adjusting this update frequency, the number of distance computation can be reduced and the performance can be improved.
Keyword (in Japanese) (See Japanese page) 
(in English) K-means Clustering / memory-efficient / large-scale database / / / / /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 441, PRMU2012-140, pp. 61-66, Feb. 2013.
Paper # PRMU2012-140 
Date of Issue 2013-02-14 (PRMU) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee PRMU  
Conference Date 2013-02-21 - 2013-02-22 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To PRMU 
Conference Code 2013-02-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Memory Efficient K-means Clustering Using HDD 
Sub Title (in English)  
Keyword(1) K-means Clustering  
Keyword(2) memory-efficient  
Keyword(3) large-scale database  
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1st Author's Name Hiroshi Oike  
1st Author's Affiliation Wakayama University (Wakayama Univ.)
2nd Author's Name Kazuyoshi Kishi  
2nd Author's Affiliation Wakayama University (Wakayama Univ.)
3rd Author's Name Toshikazu Wada  
3rd Author's Affiliation Wakayama University (Wakayama Univ.)
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Speaker Author-1 
Date Time 2013-02-21 14:30:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2012-140 
Volume (vol) vol.112 
Number (no) no.441 
Page pp.61-66 
#Pages
Date of Issue 2013-02-14 (PRMU) 


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