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Paper Abstract and Keywords
Presentation 2010-03-11 13:20
A study on ranking model optimization by following discrete changes of an evaluation value
Naoyuki Harada, Takuya Hasegawa, Masayuki Karasuyama, Ichiro Takeuchi (Nagoya Inst. of Tech.) NC2009-166
Abstract (in Japanese) (See Japanese page) 
(in English) A well-known ranking method, {\it Ranking SVM}, formulates the ranking problem as the binary classification problem on instance pairs and performs the classification with the Support Vector Machine (SVM).
In Ranking SVM, the loss function penalizes all the misclassified instance pairs equally.
Most of the Information Retrieval (IR) evaluation measures such as Normalized Discounted Cumulative Gain (NDCG), however, put more weight for higher ranked instances.
A typical approach to this problem is to set different costs for each pair using weighted loss function.
In this paper, we optimize these weights in terms of an IR evaluation measure using a {\it path following} algorithm.
Our approach is to explore a piecewise constant path of the IR evaluation measure with respect to the weights.
Experimental results show the effectiveness of our algorithm.
Keyword (in Japanese) (See Japanese page) 
(in English) learning to rank / support vector machine / path following / / / / /  
Reference Info. IEICE Tech. Rep., vol. 109, no. 461, NC2009-166, pp. 461-466, March 2010.
Paper # NC2009-166 
Date of Issue 2010-03-02 (NC) 
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)
Download PDF NC2009-166

Conference Information
Committee NC MBE  
Conference Date 2010-03-09 - 2010-03-11 
Place (in Japanese) (See Japanese page) 
Place (in English) Tamagawa University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General 
Paper Information
Registration To NC 
Conference Code 2010-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A study on ranking model optimization by following discrete changes of an evaluation value 
Sub Title (in English)  
Keyword(1) learning to rank  
Keyword(2) support vector machine  
Keyword(3) path following  
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1st Author's Name Naoyuki Harada  
1st Author's Affiliation Nagoya Institute of Technology (Nagoya Inst. of Tech.)
2nd Author's Name Takuya Hasegawa  
2nd Author's Affiliation Nagoya Institute of Technology (Nagoya Inst. of Tech.)
3rd Author's Name Masayuki Karasuyama  
3rd Author's Affiliation Nagoya Institute of Technology (Nagoya Inst. of Tech.)
4th Author's Name Ichiro Takeuchi  
4th Author's Affiliation Nagoya Institute of Technology (Nagoya Inst. of Tech.)
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Speaker Author-1 
Date Time 2010-03-11 13:20:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2009-166 
Volume (vol) vol.109 
Number (no) no.461 
Page pp.461-466 
#Pages 6 
Date of Issue 2010-03-02 (NC) 

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