16 citations · 45 across the 6 of their papers we have counts for
8 papers
Early Warning of COVID-19 Hotspots using Mobility of High Risk Users from Web Search Queries
Takahiro Yabe, Kota Tsubouchi, Satish V Ukkusuri
COVID-19 has disrupted the global economy and well-being of people at an unprecedented scale and magnitude. To contain the disease, an effective early warning system that predicts…
Non-Compulsory Measures Sufficiently Reduced Human Mobility in Tokyo during the COVID-19 Epidemic
Takahiro Yabe, Kota Tsubouchi, Naoya Fujiwara +3
While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan on h…
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…
Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search Behavior
Takahiro Yabe, Kota Tsubouchi, Toru Shimizu +2
Predicting the evacuation decisions of individuals before the disaster strikes is crucial for planning first response strategies. In addition to the studies on post-disaster analys…