A unified, comprehensive and efficient recommendation library

This is a repository of public data sources for Recommender Systems (RS).

An up-to-date, comprehensive and flexible recommendation library

Efficient and extensible GNNs enhanced recommender library based on RecBole.

This is a library built upon RecBole for cross-domain recommendation algorithms

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RecBole-Debias is a toolkit built upon RecBole for reproducing and developing debiased recommendation algorithms.

Implement Fair Recommendation Model In RecBole

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RecBole-MetaRec is an extended module for RecBole, which aims to help researchers to compare and develop their own models in the meta learning recommendation field.

[CIKM 2023] This is the official source code of "AdaMCT: Adaptive Mixture of CNN-Transformer for Sequential Recommendation" based on RecBole.

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不使用Recbole实现Mamba4Rec

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Jupyter тетрадка с решением Kaggle соревнования Alfa Campus

PyTorch implementation of our paper "Review-aware Graph Convolution Network for explainable recommendation"

Recbole implementation of our paper "Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation", In KDD 2023

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A collection of social datasets for RecBole-GNN.

Framework built on top of Recbole and Recbole-GNN to experiment with graph augmentations for unfairness mitigation during inference and re-training stages

[WWW '23] The official implmentation of our paper "Fine-tuning Partition-aware Item Similarities for Efficient and Scalable Recommendation"

This is a simple item2vec implementation using gensim for recbole( https://recbole.io )

geek center of AIDS of USTC

Set of tools above RecBole framework to experimenting with distillation of knowledge from LLMs

A lightweight UniSRec implementation for production. Reduce dependency on RecBole.

This code is a replay of the Dual Channel Hypergraph Collaborative Filtering paper, using the python language, pytorch, recbole, etc.

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This is a document repository for RecBole-MetaRec

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DeepFM video recommender system model from RecBole library for participation in VKRecSys challenge