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Paper Abstract and Keywords
Presentation 2026-01-09 10:20
Destination Prediction Using Weighted Sum Integration of Aggregate and Segmented Models using Mobile Phone Location Data
Yoichi Midorikawa, Takuya Nagata, Hideki Yoshii, Toshiaki Seki (SBKK), Hiroshi Yoshiura, Masatsugu Ichino (UEC) ICM2025-30 LOIS2025-45
Abstract (in Japanese) (See Japanese page) 
(in English) In destination prediction, segmented models focused on specific attributes often face difficulties due to data sparsity, whereas aggregate models covering all users struggle to capture region-specific mobility trends. To address these challenges, this paper proposes a method that uses a weighted sum to integrate the outputs of an aggregate model, which learns overall mobility trends, and segmented models, which learn trends specific to residential areas. This approach utilizes mobility trajectories generated from location registration data of mobile phone base stations linked with user attributes. Experimental results using data from users residing in Tokyo showed that the proposed method achieved higher prediction accuracy than standalone models. These findings suggest that the broad prediction capability of the aggregate model and the reflection of region-specific trends by the segmented models effectively complement each other, demonstrating the feasibility of attribute-aware prediction while avoiding data sparsity.
Keyword (in Japanese) (See Japanese page) 
(in English) mobile phone base stations / location registration information / destination prediction / / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 312, LOIS2025-45, pp. 42-47, Jan. 2026.
Paper # LOIS2025-45 
Date of Issue 2026-01-01 (ICM, LOIS) 
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 ICM2025-30 LOIS2025-45

Conference Information
Committee LOIS ICM  
Conference Date 2026-01-08 - 2026-01-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Saga Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Practical Use of Lifelog, Office Information System, Business Management, etc. 
Paper Information
Registration To LOIS 
Conference Code 2026-01-LOIS-ICM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Destination Prediction Using Weighted Sum Integration of Aggregate and Segmented Models using Mobile Phone Location Data 
Sub Title (in English)  
Keyword(1) mobile phone base stations  
Keyword(2) location registration information  
Keyword(3) destination prediction  
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1st Author's Name Yoichi Midorikawa  
1st Author's Affiliation SoftBank Corp. (SBKK)
2nd Author's Name Takuya Nagata  
2nd Author's Affiliation SoftBank Corp. (SBKK)
3rd Author's Name Hideki Yoshii  
3rd Author's Affiliation SoftBank Corp. (SBKK)
4th Author's Name Toshiaki Seki  
4th Author's Affiliation SoftBank Corp. (SBKK)
5th Author's Name Hiroshi Yoshiura  
5th Author's Affiliation The University of Electro-Communications (UEC)
6th Author's Name Masatsugu Ichino  
6th Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2026-01-09 10:20:00 
Presentation Time 25 minutes 
Registration for LOIS 
Paper # ICM2025-30, LOIS2025-45 
Volume (vol) vol.125 
Number (no) no.311(ICM), no.312(LOIS) 
Page pp.42-47 
#Pages 6 
Date of Issue 2026-01-01 (ICM, LOIS) 

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