yueliu1999/HSAN
[AAAI 2023] An official source code for paper Hard Sample Aware Network for Contrastive Deep Graph Clustering.
This project helps researchers and data scientists analyze complex network data to identify underlying groups or clusters. You input raw graph data, which includes information about connections and attributes of individual elements, and it outputs a clearer understanding of how these elements naturally group together based on both their characteristics and their relationships. This is ideal for those working with linked data, like social networks, biological pathways, or citation networks.
214 stars. No commits in the last 6 months.
Use this if you need to discover meaningful groupings within your graph-structured data where traditional clustering methods struggle with nuanced relationships.
Not ideal if your data is not structured as a graph or if you require human-interpretable rules for clustering decisions.
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Python
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Last pushed
Dec 20, 2022
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