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.

Graph partitioning by Correspondence Analysis and Taxicab Correspondence Analysis

BALBI, SIMONA
2014

Abstract

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11588/599482
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