# HGSL

**Repository Path**: xiao-song-sinx/HGSL

## Basic Information

- **Project Name**: HGSL
- **Description**: 图神经网络的异质图结构学习
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-11-13
- **Last Updated**: 2021-11-13

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# HGSL
Source code of AAAI submission "Heterogeneous Graph Structure Learning for Graph Neural Networks"
# Requirements
## Python Packages
- Python >= 3.6.8
- Pytorch >= 1.3.0
## GPU Memmory Requirements
- ACM >= 8G
- DBLP >=5G
- Yelp >=3G 
# Usage
Take DBLP dataset as an example:
python train.py --dataset='dblp' 

# FAQ
## Code of preprocessing data?
The data is originally preprocessed by GTN project (https://github.com/seongjunyun/Graph_Transformer_Networks). 

## How to generate semantic embeddings?
The semantic embeddings, i.e. $\mathcal{Z}$ in the paper, are generated by metapath2vec algorithm. Users may refer to https://github.com/dmlc/dgl/tree/master/examples/pytorch/metapath2vec for an implementation.