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Paper Abstract and Keywords
Presentation 2017-05-25 17:00
[Special Talk] Real-time Forecasting of Big Time-series Data: Foundations and Challenges
Yasushi Sakurai (Kumamoto Univ.) SIP2017-11 IE2017-11 PRMU2017-11 MI2017-11
Abstract (in Japanese) (See Japanese page) 
(in English) Time-series data analysis is an important topic that has attracted huge interest in countless domains. Given a large collection of time series, such as IoT device data, web-click logs, electric medical records, how can we efficiently and effectively capture important patterns? How can we statistically summarize all the sequences, and achieve a meaningful segmentation? How do we go about forecasting long-term future events? We develop important data mining techniques that can help us extract meaningful information and knowledge from large-scale time-series data. We review the state of the art in four related fields: (1) pattern discovery and summarization, (2) large-scale non-linear modeling, (3) big tensor analysis, and (4) real-time modeling and forecasting. The emphasis of this talk is to provide the intuition behind these powerful techniques, as well as to introduce case studies that illustrate their practical use.
Keyword (in Japanese) (See Japanese page) 
(in English) Big time-series data / Data streams / Non-linear tensor analysis / Real-time forecasting / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 48, IE2017-11, pp. 61-61, May 2017.
Paper # IE2017-11 
Date of Issue 2017-05-18 (SIP, IE, PRMU, MI) 
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 SIP2017-11 IE2017-11 PRMU2017-11 MI2017-11

Conference Information
Committee PRMU IE MI SIP  
Conference Date 2017-05-25 - 2017-05-26 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IE 
Conference Code 2017-05-PRMU-IE-MI-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Real-time Forecasting of Big Time-series Data: Foundations and Challenges 
Sub Title (in English)  
Keyword(1) Big time-series data  
Keyword(2) Data streams  
Keyword(3) Non-linear tensor analysis  
Keyword(4) Real-time forecasting  
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1st Author's Name Yasushi Sakurai  
1st Author's Affiliation Kumamoto University (Kumamoto Univ.)
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Speaker Author-1 
Date Time 2017-05-25 17:00:00 
Presentation Time 60 minutes 
Registration for IE 
Paper # SIP2017-11, IE2017-11, PRMU2017-11, MI2017-11 
Volume (vol) vol.117 
Number (no) no.47(SIP), no.48(IE), no.49(PRMU), no.50(MI) 
Page p.61 
#Pages 1 
Date of Issue 2017-05-18 (SIP, IE, PRMU, MI) 

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