Generating contextual trajectories from user profiles
Author:
Affiliation:
1. University of Notre Dame
2. Ford Motor Company
Funder
Ford Motor Company
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3423335.3428166
Reference23 articles.
1. Yasunori Akagi Takuya Nishimura Takeshi Kurashima and Hiroyuki Toda. 2018. A Fast and Accurate Method for Estimating People Flow from Spatiotemporal Population Data.. In IJCAI. 3293--3300. Yasunori Akagi Takuya Nishimura Takeshi Kurashima and Hiroyuki Toda. 2018. A Fast and Accurate Method for Estimating People Flow from Spatiotemporal Population Data.. In IJCAI. 3293--3300.
2. Mihael Ankerst Markus M Breunig Hans-Peter Kriegel and Jörg Sander. 1999. OPTICS: ordering points to identify the clustering structure. ACM Sigmod record 28 2 (1999) 49--60. Mihael Ankerst Markus M Breunig Hans-Peter Kriegel and Jörg Sander. 1999. OPTICS: ordering points to identify the clustering structure. ACM Sigmod record 28 2 (1999) 49--60.
3. BerlinMOD: a benchmark for moving object databases
4. A density-based algorithm for discovering clusters in large spatial databases with noise;Ester Martin;Kdd,1996
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1. The 3rd ACM SIGSPATIAL International Workshop on Geospatial Simulation;SIGSPATIAL Special;2021-01-25
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