Disentangled variational auto-encoder enhanced by counterfactual data for debiasing recommendation

Disentangled variational auto-encoder enhanced by counterfactual data for debiasing recommendation

Abstract Recommender system always suffers from various recommendation biases, seriously hindering its development. In this light, a series of debias methods have been proposed in the recommender system, especially for two most common biases, i.e., popularity bias and amplified subjective bias. Howe...

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Bibliographic Details
Main Authors: Yupu Guo, Fei Cai, Jianming Zheng, Xin Zhang, Honghui Chen
Format: Article
Language:English
Published: Springer 2024-01-01
Series:Complex & Intelligent Systems
Subjects:
Recommender systems
Debias
Data sparsity
Online Access:https://doi.org/10.1007/s40747-023-01314-x

Internet

https://doi.org/10.1007/s40747-023-01314-x

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