Information: Join today and make your research activities more affordable! Technical workshop participation fees and annual registration fees are available at member rates.
Notice: [Important] Announcement of Changes to Registration Fee Payment and Manuscript Upload Procedures for IEICE Technical Meetings
IEICE Technical Committee Submission System
Conference Paper's Information		 Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2015-12-04 15:15
Method for Detecting Explicit Structural Changes in Time Series Data
Akira Kasuga, Yukio Ohsawa (UTokyo), Takaaki Yoshino, Shunichi Ashida (Daiwa Securities) AI2015-21
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, Anomaly Detection is noticed in order to prevent a risk, perform security system and analyze behaviors. It is common to define the anomaly values using the probabilistic distribution estimation wherein the latent variable is assumed in Anomaly Detection. However, the data we can obtain in business are often heterogeneous and deficient. If the exiting methods are applied to heterogeneous and deficient data, it is difficult to analyze these data accurately and make a decision because the latent variable models result in complicated. In this paper, we propose the method that can detect explicit structural changes from high dimensional data of time series with the aim of detecting changes without assuming the latent variables.
Keyword (in Japanese) (See Japanese page) 
(in English) Change-Point Detection / Time Series / Explicit Change / Chance Discovery / Affinity Propagation / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 337, AI2015-21, pp. 51-55, Dec. 2015.
Paper # AI2015-21 
Date of Issue 2015-11-27 (AI) 
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 AI2015-21

Conference Information
Committee AI  
Conference Date 2015-12-04 - 2015-12-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyutech-Salite 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To AI 
Conference Code 2015-12-AI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Method for Detecting Explicit Structural Changes in Time Series Data 
Sub Title (in English)  
Keyword(1) Change-Point Detection  
Keyword(2) Time Series  
Keyword(3) Explicit Change  
Keyword(4) Chance Discovery  
Keyword(5) Affinity Propagation  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Akira Kasuga  
1st Author's Affiliation University of Tokyo (UTokyo)
2nd Author's Name Yukio Ohsawa  
2nd Author's Affiliation University of Tokyo (UTokyo)
3rd Author's Name Takaaki Yoshino  
3rd Author's Affiliation Daiwa Securities Co. Ltd. (Daiwa Securities)
4th Author's Name Shunichi Ashida  
4th Author's Affiliation Daiwa Securities Co. Ltd. (Daiwa Securities)
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
21st Author's Name  
21st Author's Affiliation ()
22nd Author's Name  
22nd Author's Affiliation ()
23rd Author's Name  
23rd Author's Affiliation ()
24th Author's Name  
24th Author's Affiliation ()
25th Author's Name  
25th Author's Affiliation ()
26th Author's Name / /
26th Author's Affiliation ()
()
27th Author's Name / /
27th Author's Affiliation ()
()
28th Author's Name / /
28th Author's Affiliation ()
()
29th Author's Name / /
29th Author's Affiliation ()
()
30th Author's Name / /
30th Author's Affiliation ()
()
31st Author's Name / /
31st Author's Affiliation ()
()
32nd Author's Name / /
32nd Author's Affiliation ()
()
33rd Author's Name / /
33rd Author's Affiliation ()
()
34th Author's Name / /
34th Author's Affiliation ()
()
35th Author's Name / /
35th Author's Affiliation ()
()
36th Author's Name / /
36th Author's Affiliation ()
()
Speaker Author-1 
Date Time 2015-12-04 15:15:00 
Presentation Time 20 minutes 
Registration for AI 
Paper # AI2015-21 
Volume (vol) vol.115 
Number (no) no.337 
Page pp.51-55 
#Pages 5 
Date of Issue 2015-11-27 (AI) 

[Return to Top Page]

[Return to IEICE Web Page]
The Institute of Electronics, Information and Communication Engineers (IEICE), Japan