Paper Abstract and Keywords |
Presentation |
2010-03-16 13:35
Feature Transformation Reflecting User's Relevance Takahiro Takamiya, Toshikazu Wada (Wakayama Univ.), Shunji Maeda, Hisae Shibuya (Hitachi,Ltd.) PRMU2009-305 HIP2009-190 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
It is often pointed out by researchers working on similar image search that human and computer similarity measures are quite different. For solving this problem, metric learning method has been investigated based on relevance or preference scores given by users. This method is useful for some specific problems but cannot be combined with general classification problems. On the other hand, feature transformation methods, such as quantification method 4 and principal coordinate analysis that locates similar patterns closer and dissimilar patterns further. Since these methods use mutual similarity matrix for feature transformations, 1) they cannot transform input features without similarity scores to reference features, 2) an input feature transform causes feature transformations of all learnt data. Because of these limitations, these methods are mainly applied to data visualization tasks. In this report, we propose a feature transformation method free from these limitations by combining Relevance Component Analysis and quantification method 4. In the experiment, we applied SVM for classifying “Pen-Based Recognition of Handwritten Digits” in UCI repository and confirmed that our feature transformation improves the classification rate about 7%. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Feature transformation / Quantification method 4 / Relevance component analysis / k-means clustering / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 109, no. 470, PRMU2009-305, pp. 425-430, March 2010. |
Paper # |
PRMU2009-305 |
Date of Issue |
2010-03-08 (PRMU, HIP) |
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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PRMU2009-305 HIP2009-190 |
Conference Information |
Committee |
PRMU HIP |
Conference Date |
2010-03-15 - 2010-03-16 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Kagoshima Univ. |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
PRMU |
Conference Code |
2010-03-PRMU-HIP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Feature Transformation Reflecting User's Relevance |
Sub Title (in English) |
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Keyword(1) |
Feature transformation |
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Quantification method 4 |
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Relevance component analysis |
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k-means clustering |
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1st Author's Name |
Takahiro Takamiya |
1st Author's Affiliation |
Wakayama University (Wakayama Univ.) |
2nd Author's Name |
Toshikazu Wada |
2nd Author's Affiliation |
Wakayama University (Wakayama Univ.) |
3rd Author's Name |
Shunji Maeda |
3rd Author's Affiliation |
Production Engineering Research Laboratory, Hitachi,Ltd. (Hitachi,Ltd.) |
4th Author's Name |
Hisae Shibuya |
4th Author's Affiliation |
Production Engineering Research Laboratory, Hitachi,Ltd. (Hitachi,Ltd.) |
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Speaker |
Author-1 |
Date Time |
2010-03-16 13:35:00 |
Presentation Time |
25 minutes |
Registration for |
PRMU |
Paper # |
PRMU2009-305, HIP2009-190 |
Volume (vol) |
vol.109 |
Number (no) |
no.470(PRMU), no.471(HIP) |
Page |
pp.425-430 |
#Pages |
6 |
Date of Issue |
2010-03-08 (PRMU, HIP) |
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