Graph Partitioning by Correspondence Analysis and Taxicab Correspondence Analysis

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. Copyright Springer Science+Business Media New York 2013

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Year of publication:	2013
Authors:	Choulakian, Vartan ; Tibeiro, Jules
Published in:	Journal of Classification. - Springer. - Vol. 30.2013, 3, p. 397-427
Publisher:	Springer
Subject:	Adjacency matrix \| Incidence matrix \| Network analysis \| Graph partitioning \| Graph Laplacian matrix \| Correspondence analysis \| Taxicab correspondence analysis \| NCut \| RCut \| MCut \| Matrix norm \| Centroid method

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

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