Multi-View Collaborative Network Embedding https://arxiv.org/abs/2005.08189. (https://dl.acm.org/doi/fullHtml/10.1145/3441450)
Embedding learning algorithm with two versions: attention (MANE+, semi-supervised version) and without attention (MANE, unsupervised version) on a multi-view / multi-network dataset.
Three different datasets /tasks are available:
- Link prediction: Binary class
- Link prediction: Multi-class, i.e., edges have labels -- relationship mining
- Node classification
Example datasets and input formats are provided.
Usage:
- args_parser file of a chosen task should be modified for parameter settings or other choices before running the code.
- main file of a chosen task should be run. (e.g., python main_Node_Classification_MANE.py)
Experiments performed on: scikit-learn 0.19.1 numpy 1.15.4 scipy 1.2.0 torch 0.4.1 Python 3.5
Compatible with both cuda and cpu devices, depending on the user choice through arg_parser file. Also compatible with python2 and python3.