Corpus ID: 210116486

Deep Time-Stream Framework for Click-Through Rate Prediction by Tracking Interest Evolution

@article{Shi2020DeepTF,
  title={Deep Time-Stream Framework for Click-Through Rate Prediction by Tracking Interest Evolution},
  author={Shuting Shi and Wenhao Zheng and Jie Tang and Qingguo Chen and Yao Hu and Jianke Zhu and Ming Li},
  journal={ArXiv},
  year={2020},
  volume={abs/2001.03025}
}
  • Shuting Shi, Wenhao Zheng, +4 authors Ming Li
  • Published in AAAI 2020
  • Computer Science, Mathematics
  • ArXiv
  • Click-through rate (CTR) prediction is an essential task in industrial applications such as video recommendation. Recently, deep learning models have been proposed to learn the representation of users' overall interests, while ignoring the fact that interests may dynamically change over time. We argue that it is necessary to consider the continuous-time information in CTR models to track user interest trend from rich historical behaviors. In this paper, we propose a novel Deep Time-Stream… CONTINUE READING

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