weighted-metapath2vec 0.1.3

A weighted alternative to metapath2vec for heterogenous graph embedding

Weighted-Metapath2Vec

Weighted-Metapath2Vec is a Python package to embed heterogeneous graphs. The algorithm uses a weighted alternative to Metapath2vec to compute the embeddings. The embeddings can be used for downstream machine learning.

Installation

pip install weighted-metapath2vec

Usage

from weighted_metapath2vec import WeightedMetapath2VecModel

...  # Load a networkx graph as G

metapaths = [
    ['Article', 'Author', 'Article'],
    ['Author', 'Article', 'Author']
]

model = WeightedMetapath2VecModel(G,
                                  metapaths,
                                  walk_length=3,
                                  n_walks_per_node=20,
                                  embedding_dim=128)

node_embeddings = model.fit_transform()

...  # downstream task

Contributing

Use GitHub to fork and submit pull requests.

License

MIT License. See the LICENSE file.