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 |
Copyright and reproduction |
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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PRMU2012-140 |
Conference Information |
Committee |
PRMU |
Conference Date |
2013-02-21 - 2013-02-22 |
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(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 |
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K-means Clustering |
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memory-efficient |
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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.) |
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Toshikazu Wada |
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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 |
6 |
Date of Issue |
2013-02-14 (PRMU) |
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