kshitijbhandari/Unsupervised-Clustering-of-Actor-Movie-Bipartite-Graphs-Using-Random-Walk-Embeddings
Grouped 3,411 actors into 3 communities and 1,292 movies into 50 clusters using heterogeneous random walks and Word2Vec embeddings on a bipartite actor-movie network. Designed custom graph-aware metrics for optimal cluster selection and visualized results with t-SNE.
Stars
—
Forks
—
Language
Jupyter Notebook
License
—
Category
Last pushed
Mar 22, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/kshitijbhandari/Unsupervised-Clustering-of-Actor-Movie-Bipartite-Graphs-Using-Random-Walk-Embeddings"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
pyg-team/pytorch_geometric
Graph Neural Network Library for PyTorch
a-r-j/graphein
Protein Graph Library
snap-stanford/ogb
Benchmark datasets, data loaders, and evaluators for graph machine learning
graspologic-org/graspologic
Python package for graph statistics
tigergraph/pyTigerGraph
Python package for utilizing TigerGraph Databases