Improving Multi-modal Recommender Systems by Denoising and Aligning Multi-modal Content and User Feedback

Author:

Xv Guipeng1ORCID,Li Xinyu1ORCID,Xie Ruobing2ORCID,Lin Chen1ORCID,Liu Chong2ORCID,Xia Feng2ORCID,Kang Zhanhui2ORCID,Lin Leyu2ORCID

Affiliation:

1. School of Informatics, Xiamen University, Xiamen, Fujian, China

2. Tencent, Beijing, China

Funder

Young Elite Scientists Sponsorship Program by CAST

Natural Science Foundation of China

Publisher

ACM

Reference39 articles.

1. Heterogeneous Graph Contrastive Learning Network for Personalized Micro-video Recommendation

2. Group-based social diffusion in recommendation

3. Yewen Fan, Nian Si, and Kun Zhang. 2023. Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023.

4. Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, and Lars Schmidt-Thieme. 2012. Personalized Ranking for Non-Uniformly Sampled Items. In Proceedings of KDD Cup 2011 competition, San Diego, CA, USA, 2011 (JMLR Proceedings, Vol. 18). 231--247.

5. Cross-Platform Item Recommendation for Online Social E-Commerce;Gao Chen;IEEE Trans. Knowl. Data Eng.,2023

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