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The implementation for the work "LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting".

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LabelCraft

arXiv

This is the pytorch implementation of our paper at WSDM 2024:

LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting

Yimeng Bai, Yang Zhang, Jing Lu, Jianxin Chang, Xiaoxue Zang, Yanan Niu, Yang Song, Fuli Feng.

Usage

Data

The experimental datasets Kuaishou and WeChat are available for download via the links provided in the files located at /data/kuaishou/download.txt and /data/wechat/download.txt.

Training & Evaluation

python main.py

Citation

@inproceedings{LabelCraft,
author = {Bai, Yimeng and Zhang, Yang and Lu, Jing and Chang, Jianxin and Zang, Xiaoxue and Niu, Yanan and Song, Yang and Feng, Fuli},
title = {LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting},
year = {2024},
isbn = {9798400703713},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3616855.3635816},
doi = {10.1145/3616855.3635816},
booktitle = {Proceedings of the 17th ACM International Conference on Web Search and Data Mining},
pages = {28–37},
numpages = {10},
keywords = {label generation, short video recommendation},
location = {Merida, Mexico},
series = {WSDM '24}
}

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The implementation for the work "LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting".

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