DPGNN

This is the official PyTorch implementation for the paper:

Modeling Two-Way Selection Preference for Person-Job Fit. RecSys 2022

Overview

We propose a dual-perspective graph representation learning approach to model directed interactions between candidates and jobs for person-job fit, named Dual-Perspective Graph Neural Network (DPGNN).

Adaptation for v5-sections Dataset

This clone has been adapted to work with the WorkfitAI v5-sections dataset format. The original code is unchanged - only a data conversion script has been added.

Quick Start with v5-sections

# Step 1: Install dependencies
pip install -r requirements.txt

# Step 2: Convert v5-sections CSV to DPGNN format
python convert_dataset.py --train_csv train.csv --test_csv test.csv

# Step 3: Train the model
python main.py

What the converter does:

• Converts train.csv and test.csv to DPGNN's expected format
• Creates unique geek (resume) and job tokens
• Generates BERT embeddings using bert-base-uncased
• Creates train/valid/test splits in the required format

Requirements

torch>=1.10.0
torch_geometric>=2.0.2
transformers>=4.20.0

Install all requirements:

pip install -r requirements.txt

Dataset

dataset_path in prop/overall.yaml should contain the following files:

dataset_path/
├── data.{train/valid_g/valid_j/test_g/test_j/user_add/job_add}
├── {geek/job}.bert.npy
└── {geek/job}.token

Train

python main.py

Acknowledgement

The implementation is based on the open-source recommendation library RecBole and RecBole-PJF.

Please consider citing the following papers as the references if you use our codes.

@inproceedings{yang2022modeling,
  author = {Chen Yang and Yupeng Hou and Yang Song and Tao Zhang and Ji-Rong Wen and Wayne Xin Zhao},
  title = {Modeling Two-Way Selection Preference for Person-Job Fit},
  booktitle = {{RecSys}},
  year = {2022}
}

@inproceedings{zhao2021recbole,
  title={Recbole: Towards a unified, comprehensive and efficient framework for recommendation algorithms},
  author={Wayne Xin Zhao and Shanlei Mu and Yupeng Hou and Zihan Lin and Kaiyuan Li and Yushuo Chen and Yujie Lu and Hui Wang and Changxin Tian and Xingyu Pan and Yingqian Min and Zhichao Feng and Xinyan Fan and Xu Chen and Pengfei Wang and Wendi Ji and Yaliang Li and Xiaoling Wang and Ji-Rong Wen},
  booktitle={{CIKM}},
  year={2021}
}

@article{zhao2022recbole,
  title={RecBole 2.0: Towards a More Up-to-Date Recommendation Library},
  author={Zhao, Wayne Xin and Hou, Yupeng and Pan, Xingyu and Yang, Chen and Zhang, Zeyu and Lin, Zihan and Zhang, Jingsen and Bian, Shuqing and Tang, Jiakai and Sun, Wenqi and others},
  journal={arXiv preprint arXiv:2206.07351},
  year={2022}
}