percltv's Introduction

perCLTV

This repo is the TF2.0 implementation of perCLTV: A General System for Personalized Customer Lifetime Value Prediction in Online Games [PDF].

Folders

data/: data of perCLTV (randomly generated sample data to show the data format, not the real data).
- sample_data_individual_behavior.csv: the sample for individual behavior sequential data.
- sample_data_social_behavior.csv: the sample for social behavior graph data.
- sample_data_label.csv: the sample data for label, where label1 is churn label (binary classification) and label2 is payment label (regression).
src/: implementations of MSDMT.
- model.py: the code for model.
main.py: the code for pipeline.

Requirements

The code has been tested running under Python 3.8.16, with the following packages installed (along with their dependencies):

tensorflow == 2.12.0
spektral == 1.2.0
attention == 5.0.0
numpy == 1.23.5
pandas == 2.0.0
scikit-learn == 1.2.2

Running

$ python main.py

Cite

Please cite our paper if you use this code in your own work:

@article{zhao2023percltv,
  title={perCLTV: A general system for personalized customer lifetime value prediction in online games},
  author={Zhao, Shiwei and Wu, Runze and Tao, Jianrong and Qu, Manhu and Zhao, Minghao and Fan, Changjie and Zhao, Hongke},
  journal={ACM Transactions on Information Systems},
  volume={41},
  number={1},
  pages={1--29},
  year={2023},
  publisher={ACM New York, NY}
}

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