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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Vartan Choulakian is supported by a grant from the Natural Science and Research Council of Canada.
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Choulakian, V., de Tibeiro, J. Graph Partitioning by Correspondence Analysis and Taxicab Correspondence Analysis. J Classif 30, 397–427 (2013). https://doi.org/10.1007/s00357-013-9145-4
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DOI: https://doi.org/10.1007/s00357-013-9145-4