Multi-domain Recommendation with Embedding Disentangling and Domain Alignment

Author:

Ning Wentao1ORCID,Yan Xiao2ORCID,Liu Weiwen3ORCID,Cheng Reynold1ORCID,Zhang Rui4ORCID,Tang Bo2ORCID

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

Reference69 articles.

1. Amazon. Deep graph library. "https://dgl.ai". Amazon. Deep graph library. "https://dgl.ai".

2. No Task Left Behind: Multi-Task Learning of Knowledge Tracing and Option Tracing for Better Student Assessment

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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