Relations Between Adjacency and Modularity Graph Partitioning
| Title: | Relations Between Adjacency and Modularity Graph Partitioning |
|---|---|
| Authors: | Jiang, Hansi, Meyer, Carl |
| Publication Year: | 2015 |
| Collection: | Statistics |
| Subject Terms: | Statistics - Machine Learning, 05C50, 15A18, 62H30, 90C59 |
| More Details: | This paper develops the exact linear relationship between the leading eigenvector of the unnormalized modularity matrix and the eigenvectors of the adjacency matrix. We propose a method for approximating the leading eigenvector of the modularity matrix, and we derive the error of the approximation. There is also a complete proof of the equivalence between normalized adjacency clustering and normalized modularity clustering. Numerical experiments show that normalized adjacency clustering can be as twice efficient as normalized modularity clustering. Comment: 12 pages |
| Document Type: | Working Paper |
| DOI: | 10.1007/978-3-031-33377-4_15 |
| Access URL: | http://arxiv.org/abs/1505.03481 |
| Accession Number: | edsarx.1505.03481 |
| Database: | arXiv |
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