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This is our Tensorflow implementation for "Social Collaborative Mutual Learning for Item Recommendation" (SCML) TKDD 2020.

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Tianyu Zhu
Mar 23, 2022
20bc4c8 · Mar 23, 2022

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Social Collaborative Mutual Learning

This is our Tensorflow implementation for the paper:

Tianyu Zhu, Guannan Liu, and Guoqing Chen. "Social Collaborative Mutual Learning for Item Recommendation." ACM Transactions on Knowledge Discovery from Data (TKDD) 14.4 (2020): 1-19.

Introduction

Social Collaborative Mutual Learning (SCML) is a social recommendation framework that combines the item-based CF model with the social CF model by two mutual regularization strategies.

Citation

@article{zhu2020social,
  title = {Social Collaborative Mutual Learning for Item Recommendation},
  author = {Tianyu Zhu and Guannan Liu and Guoqing Chen},
  journal = {ACM Transactions on Knowledge Discovery from Data (TKDD)},
  volume = {14},
  number = {4},
  pages = {1--19},
  year = {2020},
  publisher = {ACM New York, NY, USA}
}

Environment Requirement

The code has been tested running under Python 3.6. The required packages are as follows:

  • tensorflow == 1.5.0
  • numpy == 1.14.2
  • scipy == 1.1.0

Dataset

Example to Run the Codes

  • Ciao dataset
python main.py --dataset=Ciao

About

This is our Tensorflow implementation for "Social Collaborative Mutual Learning for Item Recommendation" (SCML) TKDD 2020.

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