83 citations · 197 across the 15 of their papers we have counts for
5 papers · 1 filter
MoE-TransMov: A Transformer-based Model for Next POI Prediction in Familiar & Unfamiliar Movements
Ruichen Tan, Jiawei Xue, Kota Tsubouchi +2
Accurate prediction of the next point of interest (POI) within human mobility trajectories is essential for location-based services, as it enables more timely and personalized reco…
GEO-BLEU: Similarity Measure for Geospatial Sequences
Toru Shimizu, Kota Tsubouchi, Takahiro Yabe
In recent geospatial research, the importance of modeling large-scale human mobility data and predicting trajectories is rising, in parallel with progress in text generation using…
Learning Fine Grained Place Embeddings with Spatial Hierarchy from Human Mobility Trajectories
Toru Shimizu, Takahiro Yabe, Kota Tsubouchi
Place embeddings generated from human mobility trajectories have become a popular method to understand the functionality of places. Place embeddings with high spatial resolution ar…
City2City: Translating Place Representations across Cities
Takahiro Yabe, Kota Tsubouchi, Toru Shimizu +2
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 hav…
VLUC: An Empirical Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction
Renhe Jiang, Zekun Cai, Zhaonan Wang +5
Nowadays, massive urban human mobility data are being generated from mobile phones, car navigation systems, and traffic sensors. Predicting the density and flow of the crowd or tra…