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City2City: Translating Place Representations across Cities

Authors:

Kota Tsubouchi,

Yoshihide Sekimoto, and

Satish V. UkkusuriAuthors Info & Claims

SIGSPATIAL '19: Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2019

Pages 412 - 415

https://doi.org/10.1145/3347146.3359063

Published: 05 November 2019 Publication History

Abstract

Large mobility datasets collected from various sources have allowed us to observe, analyze, predict and solve a wide range of important urban challenges. In particular, studies have generated place representations (or embeddings) from mobility patterns in a similar manner to word embeddings to better understand the functionality of different places within a city. However, studies have been limited to generating such representations of cities in an individual manner and has lacked an inter-city perspective, which has made it difficult to transfer the insights gained from the place representations across different cities. In this study, we attempt to bridge this research gap by treating cities and languages analogously. We apply methods developed for unsupervised machine language translation tasks to translate place representations across different cities. Real world mobility data collected from mobile phone users in 2 cities in Japan are used to test our place representation translation methods. Translated place representations are validated using landuse data, and results show that our methods were able to accurately translate place representations from one city to another.

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Cited By

Haikal CAlizadeh PRodrigues CChongke BHong JBures MPark JCerny T(2022)Place embedding across cities in location-based social networksProceedings of the 37th ACM/SIGAPP Symposium on Applied Computing10.1145/3477314.3506992(539-546)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3477314.3506992
Sun TWang FZhang ZWu LXu Y(2022)Human Mobility Identification by Deep Behavior Relevant Location RepresentationDatabase Systems for Advanced Applications10.1007/978-3-031-00126-0_33(439-454)Online publication date: 8-Apr-2022
https://doi.org/10.1007/978-3-031-00126-0_33
Shimizu TYabe TTsubouchi K(2021)Improving Land Use Classification using Human Mobility-based Hierarchical Place Embeddings2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops51409.2021.9431083(305-311)Online publication date: 22-Mar-2021
https://doi.org/10.1109/PerComWorkshops51409.2021.9431083
Show More Cited By

Index Terms

City2City: Translating Place Representations across Cities
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
2. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile devices

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Published In

cover image ACM Conferences

SIGSPATIAL '19: Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2019

648 pages

ISBN:9781450369091

DOI:10.1145/3347146

Copyright © 2019 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 November 2019

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Poster
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Refereed limited

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National Science Foundation

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SIGSPATIAL '19

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SIGSPATIAL

SIGSPATIAL '19: 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 5 - 8, 2019

IL, Chicago, USA

Acceptance Rates

SIGSPATIAL '19 Paper Acceptance Rate 34 of 161 submissions, 21%;

Overall Acceptance Rate 220 of 1,116 submissions, 20%

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Cited By

Haikal CAlizadeh PRodrigues CChongke BHong JBures MPark JCerny T(2022)Place embedding across cities in location-based social networksProceedings of the 37th ACM/SIGAPP Symposium on Applied Computing10.1145/3477314.3506992(539-546)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3477314.3506992
Sun TWang FZhang ZWu LXu Y(2022)Human Mobility Identification by Deep Behavior Relevant Location RepresentationDatabase Systems for Advanced Applications10.1007/978-3-031-00126-0_33(439-454)Online publication date: 8-Apr-2022
https://doi.org/10.1007/978-3-031-00126-0_33
Shimizu TYabe TTsubouchi K(2021)Improving Land Use Classification using Human Mobility-based Hierarchical Place Embeddings2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops51409.2021.9431083(305-311)Online publication date: 22-Mar-2021
https://doi.org/10.1109/PerComWorkshops51409.2021.9431083
Pang YTsubouchi KYabe TSekimoto Y(2020)Intercity Simulation of Human Mobility at Rare Events via Reinforcement LearningProceedings of the 28th International Conference on Advances in Geographic Information Systems10.1145/3397536.3422244(293-302)Online publication date: 3-Nov-2020
https://dl.acm.org/doi/10.1145/3397536.3422244
Shimizu TYabe TTsubouchi K(2020)Enabling Finer Grained Place Embeddings using Spatial Hierarchy from Human Mobility TrajectoriesProceedings of the 28th International Conference on Advances in Geographic Information Systems10.1145/3397536.3422229(187-190)Online publication date: 3-Nov-2020
https://dl.acm.org/doi/10.1145/3397536.3422229

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