Wednesday, 2022/05/25

  • CS/AI
  • C
  • TITECH
  • Switch Language
    • ja日本語 (Japanese)
    • enEnglish

Shimosaka Research Group

pursuing MIUBIQ (machine intelligence in UbiComp Research)

  • Home
    • Members
    • Location
  • News
  • Projects
  • Publications
  • Awards
  • Archives
    • Codes
    • Datasets
Navigation
News Presenting our paper on Forecasting Urban Dynamics with Mobility Logs at UbiComp2015 (September, 2015 @Osaka)

Presenting our paper on Forecasting Urban Dynamics with Mobility Logs at UbiComp2015 (September, 2015 @Osaka)

2015/10/05 | NewsPresentations | 2121 views |

We proudly presented our work on forecasting urban dynamics (daily people flow in a city) with mobility logs at The 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2015) held at Osaka, Japan September 2015.

We propose a low-rank bilinear model, which enables us to predict urban dynamics using external factors e.g. national holiday, day of week, and weather. Experimental results show that our model performs better predictive performance than existing models. In addition, we introduce various applications of our model such as event detection, and urban dynamics simulation.

9/10 Late Morning 11:30 – 12:40, Room 1+2
UbiComp/Urban Dynamics

Forecasting Urban Dynamics with Mobility Logs by Bilinear Poisson Regression
Masamichi Shimosaka*, Keisuke Maeda**, Takeshi Tsukiji**, Kota Tsubouchi***
(*Tokyo Institute of Technology, **The University of Tokyo, ***Yahoo! JAPAN Research, Japan)

The (open accessible) paper is available on acm.org.

  • tweet

Comments are disabled for this post

Social Networks

  • twitter
  • rss

Recent News

  • Presenting our paper on Efficient Indoor Localization Model Construction by Sequential Recommendation of Data Gathering Position based on Bayesian Optimization at IPIN2021 2021/11/29
  • Adaptive incremental beacon placement optimization for crowd density monitoring applications 2021/11/01
  • Presenting 2 papers at ACM SIGSPATIAL 2021 2021/11/01
  • Fine-grained Urban Dynamics Prediction using Large-Scale Mobile Phone Location Data 2021/10/05
  • Robustifying Wi-Fi localization by Between-Location data augmentation 2021/09/28
  • Our paper on robustifying Wi-Fi localization by “Between-Location” data augmentation has been published in IEEE Sensors Journal 2021/09/17
  • Driving behavior modeling at un-signalized intersection with inverse reinforcement learning on sequential MDPs 2021/07/12
  • Presenting our paper on driving behavior modeling with inverse reinforcement learning at un-signalized intersection on sequential MDPs on IV2021 2021/07/07
  • Presenting our paper on fine-grained urban dynamics prediction with hierarchical Bayes on PAKDD 2021 2021/05/11
  • New members of April 2021 2021/04/07

Search

Copyright 2015 · Shimosaka Research Group at TITECH