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Paper Abstract and Keywords
Presentation 2017-03-07 10:00
Safe Pruning Rule for Predictive Sequential Pattern Mining and Its Application to Bio-logging Data Analysis
Kaoru Kishimoto (NITech), Masayuki Karasuyama (NIT), Kazuya Nakagawa (NITech), Kotaro Kimura (Osaka Univ.), Ken Yoda (Nagoya Univ.), Yuta Umezu, Shinsuke Kajioka (NITech), Koji Tsuda (UTokyo), Ichiro Takeuchi (NITech) IBISML2016-105
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, the analysis for time-series logging data of animal behaviors, called bio-logging data, has attracted a wide attention in ethology because of development of a variety of logging devices including GPS. Most of bio-logging data are records of time-series movements of animals which can be represented as a sequence of patterns. In this paper, we consider mining predictive patterns from the sequence data by building a sparse prediction model. However, a huge number of possible patterns exist by which a naive application of machine learning algorithms is prohibitive. We propose an efficient approach to the predictive pattern mining by combining sequential pattern mining and the safe screening technique, which enable us to prune a bunch of unnecessary sub-sequences without losing the model optimality.
Keyword (in Japanese) (See Japanese page) 
(in English) Sequential pattern mining / Safe screening / Bio-logging data / / / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 500, IBISML2016-105, pp. 41-48, March 2017.
Paper # IBISML2016-105 
Date of Issue 2017-02-27 (IBISML) 
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 IBISML  
Conference Date 2017-03-06 - 2017-03-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokyo Institute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Statistical Mathematics, Machine Learning, Data Mining, etc. 
Paper Information
Registration To IBISML 
Conference Code 2017-03-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Safe Pruning Rule for Predictive Sequential Pattern Mining and Its Application to Bio-logging Data Analysis 
Sub Title (in English)  
Keyword(1) Sequential pattern mining  
Keyword(2) Safe screening  
Keyword(3) Bio-logging data  
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1st Author's Name Kaoru Kishimoto  
1st Author's Affiliation Nagoya Institute of Technology (NITech)
2nd Author's Name Masayuki Karasuyama  
2nd Author's Affiliation Nagoya Institute of Technology (NIT)
3rd Author's Name Kazuya Nakagawa  
3rd Author's Affiliation Nagoya Institute of Technology (NITech)
4th Author's Name Kotaro Kimura  
4th Author's Affiliation Osaka University (Osaka Univ.)
5th Author's Name Ken Yoda  
5th Author's Affiliation Nagoya University (Nagoya Univ.)
6th Author's Name Yuta Umezu  
6th Author's Affiliation Nagoya Institute of Technology (NITech)
7th Author's Name Shinsuke Kajioka  
7th Author's Affiliation Nagoya Institute of Technology (NITech)
8th Author's Name Koji Tsuda  
8th Author's Affiliation The University of Tokyo (UTokyo)
9th Author's Name Ichiro Takeuchi  
9th Author's Affiliation Nagoya Institute of Technology (NITech)
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Speaker Author-1 
Date Time 2017-03-07 10:00:00 
Presentation Time 30 minutes 
Registration for IBISML 
Paper # IBISML2016-105 
Volume (vol) vol.116 
Number (no) no.500 
Page pp.41-48 
#Pages 8 
Date of Issue 2017-02-27 (IBISML) 

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