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City2City: Translating Place Representations across Cities

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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cover image ACM Conferences
SIGSPATIAL '19: Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
November 2019
648 pages
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Published: 05 November 2019

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Author Tags

  1. human mobility
  2. machine translation
  3. mobile phone data
  4. place representations
  5. urban functions

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SIGSPATIAL '19 Paper Acceptance Rate 34 of 161 submissions, 21%;
Overall Acceptance Rate 257 of 1,238 submissions, 21%

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