Probabilistic inequalities for evaluating structural network measures

Veronika Kraus; Matthias Dehmer; Frank Emmert-Streib

doi:10.1016/j.ins.2014.07.018

Probabilistic inequalities for evaluating structural network measures

Veronika Kraus
, Matthias Dehmer^*
, Frank Emmert-Streib

^*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Artikkeli › Tieteellinen › vertaisarvioitu

27 Sitaatiot (Scopus)

Abstrakti

Proving interrelations between structural graph measures analytically has been intricate. Generally, relations between structural graph measures describe the interplay between measures which turned out to be useful for better understanding the properties of such quantities. The results which have been achieved so far are restricted to simple measures or special graph classes such as trees. In this paper, we introduce a probabilistic approach for establishing inequalities between quantitative network measures on random networks. Those inequalities between different graph measures lead to a deeper understanding of the mathematical apparatus and, in particular, to a discussion of quality aspects of structural graph measures, which is a major contribution of this paper. (C) 2014 Elsevier Inc. All rights reserved.

Alkuperäiskieli	Englanti
Sivut	220-245
Sivumäärä	26
Julkaisu	Information Sciences
Vuosikerta	288
DOI - pysyväislinkit	https://doi.org/10.1016/j.ins.2014.07.018
Tila	Julkaistu - 20 jouluk. 2014
OKM-julkaisutyyppi	A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Rahoitus

Matthias Dehmer and Veronika Kraus thank the Austrian Science Funds for supporting this work (project P26142 and P22029). Matthias Dehmer also gratefully acknowledges financial support from the German Federal Ministry of Education and Research (BMBF) (project RiKoV, Grant No. 13N12304).

Pääsy asiakirjaan

10.1016/j.ins.2014.07.018

Siteeraa tätä

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abstract = "Proving interrelations between structural graph measures analytically has been intricate. Generally, relations between structural graph measures describe the interplay between measures which turned out to be useful for better understanding the properties of such quantities. The results which have been achieved so far are restricted to simple measures or special graph classes such as trees. In this paper, we introduce a probabilistic approach for establishing inequalities between quantitative network measures on random networks. Those inequalities between different graph measures lead to a deeper understanding of the mathematical apparatus and, in particular, to a discussion of quality aspects of structural graph measures, which is a major contribution of this paper. (C) 2014 Elsevier Inc. All rights reserved.",

keywords = "Quantitative graph theory, Information inequality, Statistics, Random network models, INFORMATION-THEORY, COMPLEX NETWORKS, TOPOLOGICAL INDEXES, ENTROPY MEASURES, GRAPH ENTROPIES, DISCRIMINATION, CONNECTIVITY, BOUNDS, QUACN",

author = "Veronika Kraus and Matthias Dehmer and Frank Emmert-Streib",

year = "2014",

month = dec,

day = "20",

doi = "10.1016/j.ins.2014.07.018",

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TY - JOUR

T1 - Probabilistic inequalities for evaluating structural network measures

AU - Kraus, Veronika

AU - Dehmer, Matthias

AU - Emmert-Streib, Frank

PY - 2014/12/20

Y1 - 2014/12/20

N2 - Proving interrelations between structural graph measures analytically has been intricate. Generally, relations between structural graph measures describe the interplay between measures which turned out to be useful for better understanding the properties of such quantities. The results which have been achieved so far are restricted to simple measures or special graph classes such as trees. In this paper, we introduce a probabilistic approach for establishing inequalities between quantitative network measures on random networks. Those inequalities between different graph measures lead to a deeper understanding of the mathematical apparatus and, in particular, to a discussion of quality aspects of structural graph measures, which is a major contribution of this paper. (C) 2014 Elsevier Inc. All rights reserved.

AB - Proving interrelations between structural graph measures analytically has been intricate. Generally, relations between structural graph measures describe the interplay between measures which turned out to be useful for better understanding the properties of such quantities. The results which have been achieved so far are restricted to simple measures or special graph classes such as trees. In this paper, we introduce a probabilistic approach for establishing inequalities between quantitative network measures on random networks. Those inequalities between different graph measures lead to a deeper understanding of the mathematical apparatus and, in particular, to a discussion of quality aspects of structural graph measures, which is a major contribution of this paper. (C) 2014 Elsevier Inc. All rights reserved.

KW - Quantitative graph theory

KW - Information inequality

KW - Statistics

KW - Random network models

KW - INFORMATION-THEORY

KW - COMPLEX NETWORKS

KW - TOPOLOGICAL INDEXES

KW - ENTROPY MEASURES

KW - GRAPH ENTROPIES

KW - DISCRIMINATION

KW - CONNECTIVITY

KW - BOUNDS

KW - QUACN

U2 - 10.1016/j.ins.2014.07.018

DO - 10.1016/j.ins.2014.07.018

M3 - Article

SN - 0020-0255

VL - 288

SP - 220

EP - 245

JO - Information Sciences

JF - Information Sciences

ER -

Probabilistic inequalities for evaluating structural network measures

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Rahoitus

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