Paper Abstract and Keywords |
Presentation |
2017-03-02 09:10
Extracting Information on Traffic Changes from Social Media Data for Predictive Traffic Engineering Kota Kawashima, Yuichi Ohsita, Masayuki Murata (Osaka Univ.) IN2016-98 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The amount of traffic through networks is increasing both in quantity and in fluctuation as the mobile terminals become popular.
Predictive Traffic Engineering (TE) is one approach to accommodating the fluctuating traffic.
Predictive TE allocates the resources in advance before the traffic changes by using the predicted traffic.
For predictive TE, the accurate prediction of the future traffic is important.
Thus, many methods to predict the future traffic from the traffic rates in the previous time slots have been proposed. However, these method cannot predict the traffic changes whose signs are not included in the previously observed traffic. On the other hand, the signs may be included in social media data reflecting the real world. In this paper, we investigate the signs of the traffic changes caused by the events in the real world included in the social media data. To investigate them, we propose a method to extract information related to the real-world events, and a method to forecast the unusual traffic changes based on the extracted information. We evaluate our forecasting method compared with a method to forecast based on the total traffic rate. Based on the results, we discuss the signs of the traffic changes caused by the events in the real world. The results indicate that the signs of the unusual traffic changes are included in social media data. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Traffic Engineering / Traffic Prediction / Forecasting Unusual Traffic Changes / Social Media Data / Twitter / / / |
Reference Info. |
IEICE Tech. Rep., vol. 116, no. 485, IN2016-98, pp. 7-12, March 2017. |
Paper # |
IN2016-98 |
Date of Issue |
2017-02-23 (IN) |
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) |
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IN2016-98 |
Conference Information |
Committee |
NS IN |
Conference Date |
2017-03-02 - 2017-03-03 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
OKINAWA ZANPAMISAKI ROYAL HOTEL |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
General |
Paper Information |
Registration To |
IN |
Conference Code |
2017-03-NS-IN |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Extracting Information on Traffic Changes from Social Media Data for Predictive Traffic Engineering |
Sub Title (in English) |
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Keyword(1) |
Traffic Engineering |
Keyword(2) |
Traffic Prediction |
Keyword(3) |
Forecasting Unusual Traffic Changes |
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Social Media Data |
Keyword(5) |
Twitter |
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1st Author's Name |
Kota Kawashima |
1st Author's Affiliation |
Osaka University (Osaka Univ.) |
2nd Author's Name |
Yuichi Ohsita |
2nd Author's Affiliation |
Osaka University (Osaka Univ.) |
3rd Author's Name |
Masayuki Murata |
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Osaka University (Osaka Univ.) |
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Speaker |
Author-1 |
Date Time |
2017-03-02 09:10:00 |
Presentation Time |
20 minutes |
Registration for |
IN |
Paper # |
IN2016-98 |
Volume (vol) |
vol.116 |
Number (no) |
no.485 |
Page |
pp.7-12 |
#Pages |
6 |
Date of Issue |
2017-02-23 (IN) |
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