Dpopgcf: a fairness-driven graph convolutional collaborative filtering model with flexible negative sampling
- 29 January 2026
- journal article
- research article
- Published by Springer Nature in International Journal of Machine Learning and Cybernetics
- Vol. 17 (2) , 45
Abstract
No abstract availableKeywords
This publication has 32 references indexed in Scilit:
- A graph neural network with topic relation heterogeneous multi-level cross-item information for session-based recommendationInformation Systems, 2024
- How graph convolutions amplify popularity bias for recommendation?Frontiers of Computer Science, 2023
- Flexibly manipulating popularity bias for tackling trade-offs in recommendationInformation Processing & Management, 2023
- DMMP: A distillation-based multi-task multi-tower learning model for personalized recommendationKnowledge-Based Systems, 2023
- HN-GCCF: High-order neighbor-enhanced graph convolutional collaborative filteringKnowledge-Based Systems, 2023
- Item Attribute-aware Graph Collaborative FilteringExpert Systems with Applications, 2023
- A Debiasing Autoencoder for Recommender SystemIEEE Transactions on Consumer Electronics, 2023
- Sapling Similarity: A performing and interpretable memory-based tool for recommendationKnowledge-Based Systems, 2023
- De-Biasing user conformity bias and item popularity bias in Group recommendation2023
- BSPR: Basket-sensitive personalized ranking for product recommendationInformation Sciences, 2020