Cayley graphs as classifiers for data mining: the influence of asymmetries

Title: Cayley graphs as classifiers for data mining: the influence of asymmetries
Creator: Kelarev, Andrei; Ryan, Joe; Yearwood, John
Relation: Discrete Mathematics Vol. 309, Issue 17, p. 5360-5369
Publisher Link: http://dx.doi.org/10.1016/j.disc.2008.11.030
Publisher: Elsevier
Resource Type: journal article
Date: 2009
Description: The endomorphism monoids of graphs have been actively investigated. They are convenient tools expressing asymmetries of the graphs. One of the most important classes of graphs considered in this framework is that of Cayley graphs. Our paper proposes a new method of using Cayley graphs for classification of data. We give a survey of recent results devoted to the Cayley graphs also involving their endomorphism monoids.
Subject: Cayley graphs; endomorphism monoids; classification
Identifier: http://hdl.handle.net/1959.13/809128
Identifier: uon:7822
Identifier: ISSN:0012-365X
Language: eng
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