Skip to content
/ MMDNE Public

Source code for CIKM 2019 paper "Temporal Network Embedding with Micro- and Macro-dynamics"

Notifications You must be signed in to change notification settings

rootlu/MMDNE

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

21 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

MMDNE

Source code for CIKM 2019 paper "Temporal Network Embedding with Micro- and Macro-dynamics".

Requirements

  • Python 2.7
  • numpy
  • scipy
  • PyTorch (0.3.0)
  • My machine with two GPUs (NVIDIA GTX-1080 *2) and two CPUs (Intel Xeon E5-2690 * 2)

Description

The datasets are also available at Google Drive.

MMDNE/
├── code
│   ├── DataHelper.py: load and process data for MMDNE
│   ├── Evaluation.py: evaluate the performance of MMDNE (e.g., classification)
│   └── MMDNE.py: model architecture and training
├── data
│   └── dblp
│       ├── dblp.txt: each line is a temporal edge with the format (node1 \t node2 \t timestamp)
│       ├── node2label.txt: node label data with the format (node_name, label)
│   └── Tmall
│       ├── tmall.txt: each line is a temporal edge with the format (node1 \t node2 \t timestamp)
│       ├── node2label.txt: node label data with the format (node_name, label)
│   └── Eucore: will be available soon!
└── res
│    └── dblp
│        └──
├── README.md

Usage:

python MMDNE.py

Reference

@inproceedings{Yuanfu2019MMDNE,
  title={Temporal Network Embedding with Micro- and Macro-dynamics},
  author={Yuanfu Lu, Xiao Wang, Chuan Shi, Philip S. Yu, Yanfang Ye.}
  booktitle={Proceedings of CIKM},
  year={2019}
}

About

Source code for CIKM 2019 paper "Temporal Network Embedding with Micro- and Macro-dynamics"

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Languages