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Paper Abstract and Keywords
Presentation 2024-03-01 10:10
A PoI Localization Method using Time-series SNS Posts with Photos
Kohei Sawano (NAIST), Yuki Matsuda (NAIST/RIKEN AIP), Hiroki Ouchi (NAIST), Hirohiko Suwa, Keiichi Yasumoto (NAIST/RIKEN AIP) SeMI2023-80
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, with the easing of COVID-19 movement restrictions, there has been a trend towards the recovery of tourism demand. In tourist destinations, tourists increasingly use social media not only for disseminating information but also for gathering information. It is common for them to decide their destinations based on information posted by others. However, posts with location information typically involve tagging posts with locations registered in existing databases, which means unregistered locations cannot be tagged. This poses a challenge as there is also a trend in social media towards hiding location information for privacy protection. To apply these posts to tourist information services, it is necessary to estimate the Point of Interest (PoI) locations. This study proposes a method for estimating PoI locations based on the temporal sequence of photo and text posts on social media. Experiments were conducted to investigate the effectiveness of the proposed method, particularly the location estimation technique, and applied to experimental data. The data collection was carried out in Tateyama Town, Toyama Prefecture, with four participants, resulting in 285 image-accompanied posts. Applying the proposed location estimation method with varying weights demonstrated that the smallest error in comparison to the actual location was approximately 6.5 meters.
Keyword (in Japanese) (See Japanese page) 
(in English) PoI location estimation / Time Series Analysis / NLP / / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 400, SeMI2023-80, pp. 54-59, Feb. 2024.
Paper # SeMI2023-80 
Date of Issue 2024-02-22 (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)
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Conference Information
Committee SeMI IPSJ-UBI IPSJ-MBL  
Conference Date 2024-02-29 - 2024-03-01 
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 2024-02-SeMI-UBI-MBL 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A PoI Localization Method using Time-series SNS Posts with Photos 
Sub Title (in English)  
Keyword(1) PoI location estimation  
Keyword(2) Time Series Analysis  
Keyword(3) NLP  
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1st Author's Name Kohei Sawano  
1st Author's Affiliation Nara Institute Science and Technology (NAIST)
2nd Author's Name Yuki Matsuda  
2nd Author's Affiliation Nara Institute Science and Technology/RIKEN Center for Advanced Intelligence Project (NAIST/RIKEN AIP)
3rd Author's Name Hiroki Ouchi  
3rd Author's Affiliation Nara Institute Science and Technology (NAIST)
4th Author's Name Hirohiko Suwa  
4th Author's Affiliation Nara Institute Science and Technology/RIKEN Center for Advanced Intelligence Project (NAIST/RIKEN AIP)
5th Author's Name Keiichi Yasumoto  
5th Author's Affiliation Nara Institute Science and Technology/RIKEN Center for Advanced Intelligence Project (NAIST/RIKEN AIP)
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Speaker Author-1 
Date Time 2024-03-01 10:10:00 
Presentation Time 20 minutes 
Registration for SeMI 
Paper # SeMI2023-80 
Volume (vol) vol.123 
Number (no) no.400 
Page pp.54-59 
#Pages 6 
Date of Issue 2024-02-22 (SeMI) 

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