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Framework adopted

We sincerely thank for the robust support provided by the SELFRec framework for this project.

SELFRec is a Python framework for self-supervised recommendation (SSR) which integrates commonly used datasets and metrics, and implements many state-of-the-art SSR models. SELFRec has a lightweight architecture and provides user-friendly interfaces. It can facilitate model implementation and evaluation. Founder and principal contributor: @Coder-Yu @xiaxin1998
Supported by: @AIhongzhi (A/Prof. Hongzhi Yin, UQ)

To learn more about the Self Rec framework, please visit https://github.com/Coder-Yu/SELFRec/.

Architecture

DSVC

Requirements

numba==0.53.1
numpy==1.20.3
scipy==1.6.2
torch>=1.7.0

Usage

  1. Configure the xx.conf file in the directory named conf. (xx is the name of the model you want to run)
  2. Run main.py and choose the model you want to run.

Implemented Models

Related Datasets

ModelPaperTypeCode
DSVCYang et al. Dual Social View Enhanced Contrastive Learning for Social Recommendation, TCSS'24. Graph + CL PyTorch
DatasetsYelp2018Douban-bookFilmTrust
# User$45,919$$13,025$$1,509$
# Item$45,538$$22,348$$2,072$
# Interaction$1,183,610$$598,420$$35,497$
# Relation$709,459$$169,150$$1,853$
U-I Density$5.66\times10^{-4}$$2.06\times10^{-3}$$1.14\times10^{-2}$
U-U Density$8.01\times10^{-4}$$1.04\times10^{-3}$$1.92\times10^{-3}$

Reference

If you find this repo helpful to your research, please cite our paper.

@article{yang2024dual,
title={Dual Social View Enhanced Contrastive Learning for Social Recommendation},
author={Yang, Shixiao and Qin, Zhida and Du, Enjun and Zhou, Pengzhan and Huang, Tianyu},
journal={IEEE Transactions on Computational Social Systems},
year={2024},
publisher={IEEE}
}

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code for Dual Social View Enhanced Contrastive Learning for Social Recommendation

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GitHub - EnjunDu/DSVC: code for Dual Social View Enhanced Contrastive Learning for Social Recommendation · GitHub
Skip to content
BranchesTags
Repository files navigation
Framework adopted
We sincerely thank for the robust support provided by the SELFRec framework for this project.
SELFRec is a Python framework for self-supervised recommendation (SSR) which integrates commonly used datasets and metrics, and implements many state-of-the-art SSR models. SELFRec has a lightweight architecture and provides user-friendly interfaces. It can facilitate model implementation and evaluation.
Founder and principal contributor: @Coder-Yu @xiaxin1998
Supported by: @AIhongzhi (A/Prof. Hongzhi Yin, UQ)
To learn more about the Self Rec framework, please visit https://github.com/Coder-Yu/SELFRec/.
Architecture
DSVC
Requirements
numba==0.53.1
numpy==1.20.3
scipy==1.6.2
torch>=1.7.0

Usage
  1. Configure the xx.conf file in the directory named conf. (xx is the name of the model you want to run)
  2. Run main.py and choose the model you want to run.
Implemented Models
Related Datasets
ModelPaperTypeCode
DSVCYang et al. Dual Social View Enhanced Contrastive Learning for Social Recommendation, TCSS'24.
Graph + CL PyTorch 
DatasetsYelp2018Douban-bookFilmTrust
# User$45,919$$13,025$$1,509$
# Item$45,538$$22,348$$2,072$
# Interaction$1,183,610$$598,420$$35,497$
# Relation$709,459$$169,150$$1,853$
U-I Density$5.66\times10^{-4}$$2.06\times10^{-3}$$1.14\times10^{-2}$
U-U Density$8.01\times10^{-4}$$1.04\times10^{-3}$$1.92\times10^{-3}$
Reference
If you find this repo helpful to your research, please cite our paper.
@article{yang2024dual,
title={Dual Social View Enhanced Contrastive Learning for Social Recommendation},
author={Yang, Shixiao and Qin, Zhida and Du, Enjun and Zhou, Pengzhan and Huang, Tianyu},
journal={IEEE Transactions on Computational Social Systems},
year={2024},
publisher={IEEE}
}

About
code for Dual Social View Enhanced Contrastive Learning for Social Recommendation
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7 stars
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GitHub - EnjunDu/DSVC: code for Dual Social View Enhanced Contrastive Learning for Social Recommendation · GitHub
Skip to content
BranchesTags
Repository files navigation
Framework adopted
We sincerely thank for the robust support provided by the SELFRec framework for this project.
SELFRec is a Python framework for self-supervised recommendation (SSR) which integrates commonly used datasets and metrics, and implements many state-of-the-art SSR models. SELFRec has a lightweight architecture and provides user-friendly interfaces. It can facilitate model implementation and evaluation.
Founder and principal contributor: @Coder-Yu @xiaxin1998
Supported by: @AIhongzhi (A/Prof. Hongzhi Yin, UQ)
To learn more about the Self Rec framework, please visit https://github.com/Coder-Yu/SELFRec/.
Architecture
DSVC
Requirements
numba==0.53.1
numpy==1.20.3
scipy==1.6.2
torch>=1.7.0

Usage
  1. Configure the xx.conf file in the directory named conf. (xx is the name of the model you want to run)
  2. Run main.py and choose the model you want to run.
Implemented Models
Related Datasets
ModelPaperTypeCode
DSVCYang et al. Dual Social View Enhanced Contrastive Learning for Social Recommendation, TCSS'24.
Graph + CL PyTorch 
DatasetsYelp2018Douban-bookFilmTrust
# User$45,919$$13,025$$1,509$
# Item$45,538$$22,348$$2,072$
# Interaction$1,183,610$$598,420$$35,497$
# Relation$709,459$$169,150$$1,853$
U-I Density$5.66\times10^{-4}$$2.06\times10^{-3}$$1.14\times10^{-2}$
U-U Density$8.01\times10^{-4}$$1.04\times10^{-3}$$1.92\times10^{-3}$
Reference
If you find this repo helpful to your research, please cite our paper.
@article{yang2024dual,
title={Dual Social View Enhanced Contrastive Learning for Social Recommendation},
author={Yang, Shixiao and Qin, Zhida and Du, Enjun and Zhou, Pengzhan and Huang, Tianyu},
journal={IEEE Transactions on Computational Social Systems},
year={2024},
publisher={IEEE}
}

About
code for Dual Social View Enhanced Contrastive Learning for Social Recommendation
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7 stars
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1 watching
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, 'i');
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - EnjunDu/DSVC: code for Dual Social View Enhanced Contrastive Learning for Social Recommendation · GitHub
Skip to content
BranchesTags
Repository files navigation
Framework adopted
We sincerely thank for the robust support provided by the SELFRec framework for this project.
SELFRec is a Python framework for self-supervised recommendation (SSR) which integrates commonly used datasets and metrics, and implements many state-of-the-art SSR models. SELFRec has a lightweight architecture and provides user-friendly interfaces. It can facilitate model implementation and evaluation.
Founder and principal contributor: @Coder-Yu @xiaxin1998
Supported by: @AIhongzhi (A/Prof. Hongzhi Yin, UQ)
To learn more about the Self Rec framework, please visit https://github.com/Coder-Yu/SELFRec/.
Architecture
DSVC
Requirements
numba==0.53.1
numpy==1.20.3
scipy==1.6.2
torch>=1.7.0

Usage
  1. Configure the xx.conf file in the directory named conf. (xx is the name of the model you want to run)
  2. Run main.py and choose the model you want to run.
Implemented Models
Related Datasets
ModelPaperTypeCode
DSVCYang et al. Dual Social View Enhanced Contrastive Learning for Social Recommendation, TCSS'24.
Graph + CL PyTorch 
DatasetsYelp2018Douban-bookFilmTrust
# User$45,919$$13,025$$1,509$
# Item$45,538$$22,348$$2,072$
# Interaction$1,183,610$$598,420$$35,497$
# Relation$709,459$$169,150$$1,853$
U-I Density$5.66\times10^{-4}$$2.06\times10^{-3}$$1.14\times10^{-2}$
U-U Density$8.01\times10^{-4}$$1.04\times10^{-3}$$1.92\times10^{-3}$
Reference
If you find this repo helpful to your research, please cite our paper.
@article{yang2024dual,
title={Dual Social View Enhanced Contrastive Learning for Social Recommendation},
author={Yang, Shixiao and Qin, Zhida and Du, Enjun and Zhou, Pengzhan and Huang, Tianyu},
journal={IEEE Transactions on Computational Social Systems},
year={2024},
publisher={IEEE}
}

About
code for Dual Social View Enhanced Contrastive Learning for Social Recommendation
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7 stars
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1 watching
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, 'i');
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try {
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var __re = new RegExp('^' + "youtube\\.com" + '
GitHub - EnjunDu/DSVC: code for Dual Social View Enhanced Contrastive Learning for Social Recommendation · GitHub
Skip to content
BranchesTags
Repository files navigation
Framework adopted
We sincerely thank for the robust support provided by the SELFRec framework for this project.
SELFRec is a Python framework for self-supervised recommendation (SSR) which integrates commonly used datasets and metrics, and implements many state-of-the-art SSR models. SELFRec has a lightweight architecture and provides user-friendly interfaces. It can facilitate model implementation and evaluation.
Founder and principal contributor: @Coder-Yu @xiaxin1998
Supported by: @AIhongzhi (A/Prof. Hongzhi Yin, UQ)
To learn more about the Self Rec framework, please visit https://github.com/Coder-Yu/SELFRec/.
Architecture
DSVC
Requirements
numba==0.53.1
numpy==1.20.3
scipy==1.6.2
torch>=1.7.0

Usage
  1. Configure the xx.conf file in the directory named conf. (xx is the name of the model you want to run)
  2. Run main.py and choose the model you want to run.
Implemented Models
Related Datasets
ModelPaperTypeCode
DSVCYang et al. Dual Social View Enhanced Contrastive Learning for Social Recommendation, TCSS'24.
Graph + CL PyTorch 
DatasetsYelp2018Douban-bookFilmTrust
# User$45,919$$13,025$$1,509$
# Item$45,538$$22,348$$2,072$
# Interaction$1,183,610$$598,420$$35,497$
# Relation$709,459$$169,150$$1,853$
U-I Density$5.66\times10^{-4}$$2.06\times10^{-3}$$1.14\times10^{-2}$
U-U Density$8.01\times10^{-4}$$1.04\times10^{-3}$$1.92\times10^{-3}$
Reference
If you find this repo helpful to your research, please cite our paper.
@article{yang2024dual,
title={Dual Social View Enhanced Contrastive Learning for Social Recommendation},
author={Yang, Shixiao and Qin, Zhida and Du, Enjun and Zhou, Pengzhan and Huang, Tianyu},
journal={IEEE Transactions on Computational Social Systems},
year={2024},
publisher={IEEE}
}

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code for Dual Social View Enhanced Contrastive Learning for Social Recommendation
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, 'i');
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - EnjunDu/DSVC: code for Dual Social View Enhanced Contrastive Learning for Social Recommendation · GitHub
Skip to content
BranchesTags
Repository files navigation
Framework adopted
We sincerely thank for the robust support provided by the SELFRec framework for this project.
SELFRec is a Python framework for self-supervised recommendation (SSR) which integrates commonly used datasets and metrics, and implements many state-of-the-art SSR models. SELFRec has a lightweight architecture and provides user-friendly interfaces. It can facilitate model implementation and evaluation.
Founder and principal contributor: @Coder-Yu @xiaxin1998
Supported by: @AIhongzhi (A/Prof. Hongzhi Yin, UQ)
To learn more about the Self Rec framework, please visit https://github.com/Coder-Yu/SELFRec/.
Architecture
DSVC
Requirements
numba==0.53.1
numpy==1.20.3
scipy==1.6.2
torch>=1.7.0

Usage
  1. Configure the xx.conf file in the directory named conf. (xx is the name of the model you want to run)
  2. Run main.py and choose the model you want to run.
Implemented Models
Related Datasets
ModelPaperTypeCode
DSVCYang et al. Dual Social View Enhanced Contrastive Learning for Social Recommendation, TCSS'24.
Graph + CL PyTorch 
DatasetsYelp2018Douban-bookFilmTrust
# User$45,919$$13,025$$1,509$
# Item$45,538$$22,348$$2,072$
# Interaction$1,183,610$$598,420$$35,497$
# Relation$709,459$$169,150$$1,853$
U-I Density$5.66\times10^{-4}$$2.06\times10^{-3}$$1.14\times10^{-2}$
U-U Density$8.01\times10^{-4}$$1.04\times10^{-3}$$1.92\times10^{-3}$
Reference
If you find this repo helpful to your research, please cite our paper.
@article{yang2024dual,
title={Dual Social View Enhanced Contrastive Learning for Social Recommendation},
author={Yang, Shixiao and Qin, Zhida and Du, Enjun and Zhou, Pengzhan and Huang, Tianyu},
journal={IEEE Transactions on Computational Social Systems},
year={2024},
publisher={IEEE}
}

About
code for Dual Social View Enhanced Contrastive Learning for Social Recommendation
Resources
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Stars
7 stars
Watchers
1 watching
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GitHub - EnjunDu/DSVC: code for Dual Social View Enhanced Contrastive Learning for Social Recommendation · GitHub
Skip to content
BranchesTags
Repository files navigation
Framework adopted
We sincerely thank for the robust support provided by the SELFRec framework for this project.
SELFRec is a Python framework for self-supervised recommendation (SSR) which integrates commonly used datasets and metrics, and implements many state-of-the-art SSR models. SELFRec has a lightweight architecture and provides user-friendly interfaces. It can facilitate model implementation and evaluation.
Founder and principal contributor: @Coder-Yu @xiaxin1998
Supported by: @AIhongzhi (A/Prof. Hongzhi Yin, UQ)
To learn more about the Self Rec framework, please visit https://github.com/Coder-Yu/SELFRec/.
Architecture
DSVC
Requirements
numba==0.53.1
numpy==1.20.3
scipy==1.6.2
torch>=1.7.0

Usage
  1. Configure the xx.conf file in the directory named conf. (xx is the name of the model you want to run)
  2. Run main.py and choose the model you want to run.
Implemented Models
Related Datasets
ModelPaperTypeCode
DSVCYang et al. Dual Social View Enhanced Contrastive Learning for Social Recommendation, TCSS'24.
Graph + CL PyTorch 
DatasetsYelp2018Douban-bookFilmTrust
# User$45,919$$13,025$$1,509$
# Item$45,538$$22,348$$2,072$
# Interaction$1,183,610$$598,420$$35,497$
# Relation$709,459$$169,150$$1,853$
U-I Density$5.66\times10^{-4}$$2.06\times10^{-3}$$1.14\times10^{-2}$
U-U Density$8.01\times10^{-4}$$1.04\times10^{-3}$$1.92\times10^{-3}$
Reference
If you find this repo helpful to your research, please cite our paper.
@article{yang2024dual,
title={Dual Social View Enhanced Contrastive Learning for Social Recommendation},
author={Yang, Shixiao and Qin, Zhida and Du, Enjun and Zhou, Pengzhan and Huang, Tianyu},
journal={IEEE Transactions on Computational Social Systems},
year={2024},
publisher={IEEE}
}

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