Personalized Transfer of User Preferences for Cross-domain Recommendation-Reference-Cited by-同舟云学术

Personalized Transfer of User Preferences for Cross-domain Recommendation

Published:2022-02-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
language:
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Author:

Zhu Yongchun¹,Tang Zhenwei²,Liu Yudan³,Zhuang Fuzhen⁴,Xie Ruobing³,Zhang Xu³,Lin Leyu³,He Qing⁵

Affiliation:

1. Institute of Computing Technology, Chinese Academy of Sciences; & University of Chinese Academy of Sciences; & Tencent, Beijing, China

2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, Saudi Arabia

3. Tencent, Beijing, China

4. Beihang University, Beijing, China

5. Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China

Funder

the National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3488560.3498392

Reference45 articles.

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4. Deeply Fusing Reviews and Contents for Cold Start Users in Cross-Domain Recommendation Systems

5. Xiaobo Hao Yudan Liu Ruobing Xie Kaikai Ge Linyao Tang Xu Zhang and Leyu Lin. 2021. Adversarial Feature Translation for Multi-domain Recommendation. In KDD . 2964--2973. Xiaobo Hao Yudan Liu Ruobing Xie Kaikai Ge Linyao Tang Xu Zhang and Leyu Lin. 2021. Adversarial Feature Translation for Multi-domain Recommendation. In KDD . 2964--2973.

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