"Self-supervised Learning for Multimedia" (SLMRec) aims capture multi-modal patterns in the data itself, we go beyond the supervised learning paradigm, and incorporate the idea of self-supervised learning (SSL) into multimedia recommendation.
Authors: Zhulin Tao, Xiaohao Liu, Yewei Xia, Xiang Wang, Lifang Yang, Xianglin Huang, Tat-Seng Chua
The code has been tested running under Python 3.6.5. The required packages are as follows:
- torch==1.7.0
- numpy==1.16.1
- torch_geometric==1.6.1
We provide three processed datasets: Kwai, Tiktok, and Movielnes.
- You can find the full version of recommendation datasets via Kwai, Tiktok, and Movielens. Since the copyright of datasets, we cannot release them directly.
The hyper-parameters used to train the models are set as default in the conf/SLMRec.properties. Feel free to change them if needed.
python3 main.py --recommender="SLMRec" --data.input.dataset=tiktok@ARTICLE{SLMRec,
author={Tao, Zhulin and
Liu, Xiaohao and
Xia, Yewei and
Wang, Xiang and
Yang, Lifang and
Huang, Xianglin and
Chua, Tat-Seng},
journal={IEEE Transactions on Multimedia},
title={Self-supervised Learning for Multimedia Recommendation},
year={2022},
doi={10.1109/TMM.2022.3187556}
}
Copyright (C) Communication University of China
This program is licensed under the GNU General Public License 3.0 (https://www.gnu.org/licenses/gpl-3.0.html). Any derivative work obtained under this license must be licensed under the GNU General Public License as published by the Free Software Foundation, either Version 3 of the License, or (at your option) any later version, if this derivative work is distributed to a third party.
The copyright for the program is owned by Communication University of China. For commercial projects that require the ability to distribute the code of this program as part of a program that cannot be distributed under the GNU General Public License, please contact [email protected] to purchase a commercial license.