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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
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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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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) 
Topics (in English)  
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)  
Keyword(1) Feature transformation  
Keyword(2) Quantification method 4  
Keyword(3) Relevance component analysis  
Keyword(4) 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
Date of Issue 2010-03-08 (PRMU, HIP) 


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