Multi-domain Recommendation with Embedding Disentangling and Domain Alignment
Author:
Affiliation:
1. The University of Hong Kong, Hong Kong, Hong Kong
2. Southern University of Science and Technology, Shenzhen, China
3. Huawei Noah's Ark Lab, Shenzhen, China
4. ruizhang.info, Beijing, China
Funder
The University of Hong Kong
HKU-TCL Joint Research Center for Artificial Intelligence
the Guangdong?Hong Kong-Macau Joint Laboratory Program 2020
the Guangdong Provincial Key Laboratory
The Hong Kong Jockey Club Charities Trust (HKJC)
the Shenzhen Fundamental Research Program
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3583780.3614977
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3. A. Ariza-Casabona , B. Twardowski , and T. K. Wijaya . Exploiting graph structured cross-domain representation for multi-domain recommendation. CoRR, abs/2302.05990 , 2023 . A. Ariza-Casabona, B. Twardowski, and T. K. Wijaya. Exploiting graph structured cross-domain representation for multi-domain recommendation. CoRR, abs/2302.05990, 2023.
4. DisenCDR
5. Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck
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