yueliu1999/DCRN
[AAAI 2022] An official source code for paper Deep Graph Clustering via Dual Correlation Reduction.
This project helps researchers and data scientists analyze complex interconnected data, like social networks or biological pathways, to automatically group similar items together. You input a graph dataset (nodes and connections), and it outputs clear clusters of related nodes, revealing hidden structures and relationships. It's designed for anyone working with network-based data who needs to identify natural groupings without manual inspection.
201 stars. No commits in the last 6 months.
Use this if you need to find inherent groupings within complex networked data, such as identifying communities in social graphs, categorizing research papers based on citation networks, or segmenting customers by their interaction patterns.
Not ideal if your data isn't structured as a graph, or if you need to classify items into predefined categories rather than discovering new ones.
Stars
201
Forks
28
Language
Python
License
MIT
Category
Last pushed
May 23, 2023
Commits (30d)
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