JSAI2020

Presentation information

General Session

General Session » J-2 Machine learning

[1I3-GS-2] Machine learning: Market analysis

Tue. Jun 9, 2020 1:20 PM - 3:00 PM Room I (jsai2020online-9)

座長:中山心太(NextInt)

1:20 PM - 1:40 PM

[1I3-GS-2-01] Extraction of Latent Event Topic Using Population Data and Topic Mode

〇Tomohiro Mimura1, Shin Ishiguro1,2, Satoshi Kawasaki1,2, Daichi Shimizu1, Yousuke Fukazawa1 (1. NTT DOCOMO, INC., 2. Univ. of Tokyo)

Keywords:Topic model, Generative model, Population data

Predicting the number of visitors to an event is an important issue in reducing congestion. In this paper, we proposed a method to predicting the number of visitors. To predict visitor, we used neural topic model based on Joint Multimodal Variational AutoEncoder (JMVAE) and Student-t Variational Autoencoder with Implicit Optimal Priors. In the experiment, our proposed method showed higher prediction accuracy in root absolute error compared to conventional methods.

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