Skip to content

Code of paper: DeepPick: A Deep Learning Approach to Unveil Outstanding Users With Public Attainable Features

License

Notifications You must be signed in to change notification settings

wandli/DeepPick

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

TKDE23DeepPick

This is the official code for TKDE Paper:

"DeepPick: A Deep Learning Approach to Unveil Outstanding Users With Public Attainable Features."

Cite

If you take advantage of DeepPick in your research, please cite the following in your manuscript:

@ARTICLE{9462439,
  author={Li, Wanda and Xu, Zhiwei and Sun, Yi and Gong, Qingyuan and Chen, Yang and Ding, Aaron Yi and Wang, Xin and Hui, Pan},
  journal={IEEE Transactions on Knowledge and Data Engineering}, 
  title={DeepPick: A Deep Learning Approach to Unveil Outstanding Users With Public Attainable Features}, 
  year={2023},
  volume={35},
  number={1},
  pages={291-306},
  doi={10.1109/TKDE.2021.3091503}}

Dataset

You can download a sample dataset from this Dropbox link and run main.py to reproduce the results.

About

Code of paper: DeepPick: A Deep Learning Approach to Unveil Outstanding Users With Public Attainable Features

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages