What to Do Next: Modeling User Behaviors by Time-LSTM

@inproceedings{Zhu2017WhatTD,
  title={What to Do Next: Modeling User Behaviors by Time-LSTM},
  author={Yu Zhu and Hao Li and Yikang Liao and Beidou Wang and Ziyu Guan and Haifeng Liu and Deng Cai},
  booktitle={IJCAI},
  year={2017}
}
Recently, Recurrent Neural Network (RNN) solutions for recommender systems (RS) are becoming increasingly popular. The insight is that, there exist some intrinsic patterns in the sequence of users’ actions, and RNN has been proved to perform excellently when modeling sequential data. In traditional tasks such as language modeling, RNN solutions usually only consider the sequential order of objects without the notion of interval. However, in RS, time intervals between users’ actions are of… CONTINUE READING
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