Disentangling Long and Short-Term Interests for Recommendation

Author:

Zheng Yu1,Gao Chen1,Chang Jianxin2,Niu Yanan2,Song Yang2,Jin Depeng1,Li Yong1

Affiliation:

1. Tsinghua University, China

2. Beijing Kuaishou Technology Co., Ltd., China

Publisher

ACM

Reference55 articles.

1. Martín Abadi , Paul Barham , Jianmin Chen , Zhifeng Chen , Andy Davis , Jeffrey Dean , Matthieu Devin , Sanjay Ghemawat , Geoffrey Irving , Michael Isard , 2016 . Tensorflow: A system for large-scale machine learning. In 12th {USENIX} symposium on operating systems design and implementation ({OSDI} 16). 265–283. Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, 2016. Tensorflow: A system for large-scale machine learning. In 12th {USENIX} symposium on operating systems design and implementation ({OSDI} 16). 265–283.

2. Neural News Recommendation with Long- and Short-term User Representations

3. Andreas Argyriou , Miguel González-Fierro , and Le Zhang . 2020 . Microsoft Recommenders: Best Practices for Production-Ready Recommendation Systems. In Companion Proceedings of the Web Conference 2020. 50–51. Andreas Argyriou, Miguel González-Fierro, and Le Zhang. 2020. Microsoft Recommenders: Best Practices for Production-Ready Recommendation Systems. In Companion Proceedings of the Web Conference 2020. 50–51.

4. Mathilde Caron Ishan Misra Julien Mairal Priya Goyal Piotr Bojanowski and Armand Joulin. 2020. Unsupervised learning of visual features by contrasting cluster assignments. arXiv preprint arXiv:2006.09882(2020). Mathilde Caron Ishan Misra Julien Mairal Priya Goyal Piotr Bojanowski and Armand Joulin. 2020. Unsupervised learning of visual features by contrasting cluster assignments. arXiv preprint arXiv:2006.09882(2020).

5. Controllable Multi-Interest Framework for Recommendation

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