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情報処理学会 第62回UBI研究会にて学生奨励賞を受賞しました
Received the Student Paper Award at IPSJ-SIGUBI 62th workshop

以下の論文が、情報処理学会 第62回UBI研究会学生奨励賞(http://sigubi.ipsj.or.jp/excellent/:外部サイト)を受賞いたしました。

Predicting Urban Dynamics with GPS data by Multi-Order Poisson Regression Model
Chen Yanru*, 早川 裕太*, 坪内 孝太, 下坂 正倫*     *東京工業大学

本研究は、都市における活動人口予測の課題に対して、Multi-Orderポアソン回帰モデルを提案し、検証しました。特徴量の増減と手法の組み合わせでどのような予測パフォーマンスを実現できるか確かめたbaselineを整理した論文でもあります。

The following paper won the Student Paper Award at IPSJ-SIGUBI 62th workshop (http://sigubi.ipsj.or.jp/excellent/:external site).

Predicting Urban Dynamics with GPS data by Multi-Order Poisson Regression Model
Chen Yanru*, Yuta Hayakawa*, Kota Tsubouchi, Masamichi Shimosaka*   *Tokyo Institute of Technology

We propose a Multi-Order Poisson Regression Model for urban dynamics prediction based on an enriched and generalized feature representation. In the proposed method, new features are produced by employing a variety of polynomial combinations of multiple factors which greatly affect people flow (e.g., time-of-the-day, day-of-the-week, weather situation, holiday information). The results obtained from an experiment with a massive GPS dataset show that the proposed method is capable of producing models which have higher prediction accuracy compared to the state-of-the-art method.