Information indices with high discriminative power for graphs.

In this paper, we evaluate the uniqueness of several information-theoretic measures for graphs based on so-called information functionals and compare the results with other information indices and non-information-theoretic measures such as the well-known Balaban J index. We show that, by employing a...

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Main Authors: Matthias Dehmer, Martin Grabner, Kurt Varmuza
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2012-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3290601?pdf=render
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author Matthias Dehmer
Martin Grabner
Kurt Varmuza
author_facet Matthias Dehmer
Martin Grabner
Kurt Varmuza
author_sort Matthias Dehmer
collection DOAJ
description In this paper, we evaluate the uniqueness of several information-theoretic measures for graphs based on so-called information functionals and compare the results with other information indices and non-information-theoretic measures such as the well-known Balaban J index. We show that, by employing an information functional based on degree-degree associations, the resulting information index outperforms the Balaban J index tremendously. These results have been obtained by using nearly 12 million exhaustively generated, non-isomorphic and unweighted graphs. Also, we obtain deeper insights on these and other topological descriptors when exploring their uniqueness by using exhaustively generated sets of alkane trees representing connected and acyclic graphs in which the degree of a vertex is at most four.
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spelling doaj.art-340cfe96cc05423dbe9e90ae8beeb8602022-12-21T17:57:06ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0172e3121410.1371/journal.pone.0031214Information indices with high discriminative power for graphs.Matthias DehmerMartin GrabnerKurt VarmuzaIn this paper, we evaluate the uniqueness of several information-theoretic measures for graphs based on so-called information functionals and compare the results with other information indices and non-information-theoretic measures such as the well-known Balaban J index. We show that, by employing an information functional based on degree-degree associations, the resulting information index outperforms the Balaban J index tremendously. These results have been obtained by using nearly 12 million exhaustively generated, non-isomorphic and unweighted graphs. Also, we obtain deeper insights on these and other topological descriptors when exploring their uniqueness by using exhaustively generated sets of alkane trees representing connected and acyclic graphs in which the degree of a vertex is at most four.http://europepmc.org/articles/PMC3290601?pdf=render
spellingShingle Matthias Dehmer
Martin Grabner
Kurt Varmuza
Information indices with high discriminative power for graphs.
PLoS ONE
title Information indices with high discriminative power for graphs.
title_full Information indices with high discriminative power for graphs.
title_fullStr Information indices with high discriminative power for graphs.
title_full_unstemmed Information indices with high discriminative power for graphs.
title_short Information indices with high discriminative power for graphs.
title_sort information indices with high discriminative power for graphs
url http://europepmc.org/articles/PMC3290601?pdf=render
work_keys_str_mv AT matthiasdehmer informationindiceswithhighdiscriminativepowerforgraphs
AT martingrabner informationindiceswithhighdiscriminativepowerforgraphs
AT kurtvarmuza informationindiceswithhighdiscriminativepowerforgraphs