A Note on Spectral Clustering and SVD of Graph Data
arXiv:1809.11029v11 citations
Originality Synthesis-oriented
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This is an incremental theoretical note that clarifies relationships between existing methods for researchers in graph analysis.
The paper explores the connections between spectral clustering and Singular Value Decomposition (SVD) for graph data analysis using linear algebra, without presenting new experimental results or numerical improvements.
Spectral clustering and Singular Value Decomposition (SVD) are both widely used technique for analyzing graph data. In this note, I will present their connections using simple linear algebra, aiming to provide some in-depth understanding for future research.