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| Presentation | 2022-01-21 16:00 [Short Paper] Definition of a new feature of location activeness using Inverse Discrete Fourier Transform Shunei Inoue, Yutaka Arakawa, Shigemi Ishida (Kyushu Univ.)  SeMI2021-76 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | It is important to promote Evidence-Based Policy Making (EBPM) to conduct effective tourism policies with unique tourism resources. We are developing an EBPM platform that visualizes people flows relating to events and tourism policies. Our EBPM platform has an automatic event detector that detects ``where'' and ``how large'' an event is held. When an event is detected, the platform notifies local government officers and encourages them to enter the event information to link the event and corresponding people flow. Although, we can use anomaly detection methods to detect events from people flow data, these methods take no considerations on periodic changes in people flow. In this paper, a new feature, i.e., location activeness, is defined as time-series people flow data, excluding periodic changes. We also present an event detection method base on peak detection on the location activeness. The evaluation conducted with location data of Kyushu University Ito Campus and surrounding areas demonstrated that more than 75% of detected events were actual events, as we could find out. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Evidence-Based Policy Making (EBPM) / Location Data / Event Detection / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 333, SeMI2021-76, pp. 92-97, Jan. 2022. | |
| Paper # | SeMI2021-76 | |
| Date of Issue | 2022-01-13 (SeMI) | |
| ISSN | 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 | SeMI2021-76 |
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| Conference Information | |
| Committee | SeMI |
| Conference Date | 2022-01-20 - 2022-01-21 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SeMI |
| Conference Code | 2022-01-SeMI |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Definition of a new feature of location activeness using Inverse Discrete Fourier Transform |
| Sub Title (in English) | |
| Keyword(1) | Evidence-Based Policy Making (EBPM) |
| Keyword(2) | Location Data |
| Keyword(3) | Event Detection |
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| 1st Author's Name | Shunei Inoue |
| 1st Author's Affiliation | Kyushu University (Kyushu Univ.) |
| 2nd Author's Name | Yutaka Arakawa |
| 2nd Author's Affiliation | Kyushu University (Kyushu Univ.) |
| 3rd Author's Name | Shigemi Ishida |
| 3rd Author's Affiliation | Kyushu University (Kyushu Univ.) |
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| Speaker | Author-1 |
| Date Time | 2022-01-21 16:00:00 |
| Presentation Time | 10 minutes |
| Registration for | SeMI |
| Paper # | SeMI2021-76 |
| Volume (vol) | vol.121 |
| Number (no) | no.333 |
| Page | pp.92-97 |
| #Pages | 6 |
| Date of Issue | 2022-01-13 (SeMI) |
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