Graph Partitioning by Correspondence Analysis and Taxicab Correspondence Analysis

被引：11

作者：

Choulakian, Vartan ^{[1
]}

de Tibeiro, Jules ^{[2
]}

机构：

[1] Univ Moncton, Moncton, NB E1A 3E9, Canada

[2] Univ Moncton, Shippegan, NB, Canada

来源：

JOURNAL OF CLASSIFICATION | 2013年 / 30卷 / 03期

关键词：

Adjacency matrix; Incidence matrix; Network analysis; Graph partitioning; Graph Laplacian matrix; Correspondence analysis; Taxicab correspondence analysis; NCut; RCut; MCut; Matrix norm; Centroid method;

D O I：

10.1007/s00357-013-9145-4

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

We consider correspondence analysis (CA) and taxicab correspondence analysis (TCA) of relational datasets that can mathematically be described as weighted loopless graphs. Such data appear in particular in network analysis. We present CA and TCA as relaxation methods for the graph partitioning problem. Examples of real datasets are provided.

引用

页码：397 / 427

页数：31

共 40 条

[1] Approximating the cut-norm via Grothendieck's inequality [J].