no code implementations • 14 Dec 2021 • 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 large-scale corpora in natural language processing.
no code implementations • 6 Feb 2020 • Toru Shimizu, Takahiro Yabe, Kota Tsubouchi
Place embeddings generated from human mobility trajectories have become a popular method to understand the functionality of places.
no code implementations • 26 Nov 2019 • Takahiro Yabe, Kota Tsubouchi, Toru Shimizu, Yoshihide Sekimoto, Satish V. Ukkusuri
Large mobility datasets collected from various sources have allowed us to observe, analyze, predict and solve a wide range of important urban challenges.
no code implementations • ACL 2018 • Toru Shimizu, Nobuyuki Shimizu, Hayato Kobayashi
Recent studies showed that pretraining with unlabeled data via a language model can improve the performance of classification models.