phanein/deepwalk
Graph embedding library that learns vertex representations from random walks using a skip-gram model.
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DeepWalk learns low-dimensional representations for vertices in graphs by treating short random walks as sentences and applying the skip-gram algorithm (analogous to Word2Vec). The learned embeddings capture graph structure and can be used as features for downstream tasks like multi-label node classification. Input formats include adjacency lists, edge lists, and MATLAB sparse matrices.
Frequently asked
- What is phanein/deepwalk?
- Graph embedding library that learns vertex representations from random walks using a skip-gram model.
- Is deepwalk open source?
- Yes — phanein/deepwalk is an open-source project tracked on heatdrop.
- What language is deepwalk written in?
- phanein/deepwalk is primarily written in Python.
- How popular is deepwalk?
- phanein/deepwalk has 2.8k stars on GitHub.
- Where can I find deepwalk?
- phanein/deepwalk is on GitHub at https://github.com/phanein/deepwalk.