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MMRec

<div align="center"> <a href="https://github.com/enoche/MultimodalRecSys"><img width="300px" height="auto" src="https://github.com/enoche/MMRec/blob/master/images/logo.png"></a> </div>

$\text{MMRec}$: A modern <ins>M</ins>ulti<ins>M</ins>odal <ins>Rec</ins>ommendation toolbox that simplifies your research arXiv.
:point_right: Check our comprehensive survey on MMRec, arXiv.
:point_right: Check the awesome multimodal recommendation resources.

Toolbox

<p> <img src="./images/MMRec.png" width="500"> </p>

Supported Models

source code at: src\models

ModelPaperConference/JournalCode
General models
SelfCFSelfCF: A Simple Framework for Self-supervised Collaborative FilteringACM TORS'23selfcfed_lgn.py
LayerGCNLayer-refined Graph Convolutional Networks for RecommendationICDE'23layergcn.py
Multimodal models
VBPRVBPR: Visual Bayesian Personalized Ranking from Implicit FeedbackAAAI'16vbpr.py
MMGCNMMGCN: Multi-modal Graph Convolution Network for Personalized Recommendation of Micro-videoMM'19mmgcn.py
ItemKNNCBFAre We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation ApproachesRecSys'19itemknncbf.py
GRCNGraph-Refined Convolutional Network for Multimedia Recommendation with Implicit FeedbackMM'20grcn.py
MVGAEMulti-Modal Variational Graph Auto-Encoder for Recommendation SystemsTMM'21mvgae.py
DualGNNDualGNN: Dual Graph Neural Network for Multimedia RecommendationTMM'21dualgnn.py
LATTICEMining Latent Structures for Multimedia RecommendationMM'21lattice.py
SLMRecSelf-supervised Learning for Multimedia RecommendationTMM'22slmrec.py
Newly added
BM3Bootstrap Latent Representations for Multi-modal RecommendationWWW'23bm3.py
FREEDOMA Tale of Two Graphs: Freezing and Denoising Graph Structures for Multimodal RecommendationMM'23freedom.py
MGCNMulti-View Graph Convolutional Network for Multimedia RecommendationMM'23mgcn.py
DRAGONEnhancing Dyadic Relations with Homogeneous Graphs for Multimodal RecommendationECAI'23dragon.py
MGMirror Gradient: Towards Robust Multimodal Recommender Systems via Exploring Flat Local MinimaWWW'24trainer.py
LGMRecLGMRec: Local and Global Graph Learning for Multimodal RecommendationAAAI'24lgmrec.py

Please consider to cite our paper if this framework helps you, thanks:

@inproceedings{zhou2023bootstrap,
author = {Zhou, Xin and Zhou, Hongyu and Liu, Yong and Zeng, Zhiwei and Miao, Chunyan and Wang, Pengwei and You, Yuan and Jiang, Feijun},
title = {Bootstrap Latent Representations for Multi-Modal Recommendation},
booktitle = {Proceedings of the ACM Web Conference 2023},
pages = {845–854},
year = {2023}
}

@article{zhou2023comprehensive,
      title={A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions}, 
      author={Hongyu Zhou and Xin Zhou and Zhiwei Zeng and Lingzi Zhang and Zhiqi Shen},
      year={2023},
      journal={arXiv preprint arXiv:2302.04473},
}

@inproceedings{zhou2023mmrec,
  title={Mmrec: Simplifying multimodal recommendation},
  author={Zhou, Xin},
  booktitle={Proceedings of the 5th ACM International Conference on Multimedia in Asia Workshops},
  pages={1--2},
  year={2023}
}