TY - GEN
T1 - GEO-BLEU
T2 - 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL GIS 2022
AU - Shimizu, Toru
AU - Tsubouchi, Kota
AU - Yabe, Takahiro
N1 - Publisher Copyright:
© 2022 Owner/Author.
PY - 2022/11/1
Y1 - 2022/11/1
N2 - In recent geospatial research, the importance of modeling and generating human mobility trajectories is rising. Whereas there are already plenty of feasible approaches applicable to geospatial sequence modeling itself, there seems to be room to improve with regard to evaluation, specifically about measuring the similarity between generated and reference trajectories. In this work, we propose a novel similarity measure, GEO-BLEU, which can be especially useful in the context of geospatial sequence modeling and generation. As the name suggests, this work is based on BLEU, one of the most popular measures used in machine translation research, while introducing spatial proximity to the idea of n-gram. We compare this measure with an established method, dynamic time warping, applying both measures to simple artificial sequences and examining differences in their characteristics.
AB - In recent geospatial research, the importance of modeling and generating human mobility trajectories is rising. Whereas there are already plenty of feasible approaches applicable to geospatial sequence modeling itself, there seems to be room to improve with regard to evaluation, specifically about measuring the similarity between generated and reference trajectories. In this work, we propose a novel similarity measure, GEO-BLEU, which can be especially useful in the context of geospatial sequence modeling and generation. As the name suggests, this work is based on BLEU, one of the most popular measures used in machine translation research, while introducing spatial proximity to the idea of n-gram. We compare this measure with an established method, dynamic time warping, applying both measures to simple artificial sequences and examining differences in their characteristics.
KW - evaluation
KW - human trajectory
KW - sequence modeling
UR - http://www.scopus.com/inward/record.url?scp=85143597965&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85143597965&partnerID=8YFLogxK
U2 - 10.1145/3557915.3560951
DO - 10.1145/3557915.3560951
M3 - Conference contribution
AN - SCOPUS:85143597965
T3 - GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
BT - 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2022
A2 - Renz, Matthias
A2 - Sarwat, Mohamed
A2 - Nascimento, Mario A.
A2 - Shekhar, Shashi
A2 - Xie, Xing
PB - Association for Computing Machinery
Y2 - 1 November 2022 through 4 November 2022
ER -