On the degeneracy of the Randić entropy and related graph measures

Matthias Dehmer; Zengqiang Chen; Abbe Mowshowitz; Herbert Jodlbauer; F. Emmert-Streib; Yongtang Shi; Shailesh Tripathi; Chengyi Xia

doi:10.1016/j.ins.2018.11.011

On the degeneracy of the Randić entropy and related graph measures

Matthias Dehmer^*
, Zengqiang Chen
, Abbe Mowshowitz
, Herbert Jodlbauer
, F. Emmert-Streib
, Yongtang Shi
, Shailesh Tripathi
, Chengyi Xia

^*Corresponding author for this work

Upper Austria University of Applied Sciences
Nankai University
Private University for Health Sciences, Medical Informatics and Technology
City University of New York
Tampere University
Institute of Biosciences and Medical Technology
Tianjin University of Technology

Research output: Contribution to journal › Article › peer-review

Abstract

Numerous quantitative graph measures have been defined and applied in various disciplines. Such measures may be differentiated according to whether they are information-theoretic or non-information-theoretic. In this paper, we examine an important property of Randić entropy, an information-theoretic measure, and examine some related graph measures based on random roots. In particular, we investigate the degeneracy of these structural graph measures and discuss numerical results. Finally, we draw some conclusions about the measures’ applicability to deterministic and non-deterministic networks.

Original language	English
Pages (from-to)	680-687
Number of pages	8
Journal	Information Sciences
Volume	501
DOIs	https://doi.org/10.1016/j.ins.2018.11.011
Publication status	Published - Oct 2019
Externally published	Yes

Keywords

Data science
Graphs
Networks
Quantitative graph theory
Structural graph measures
Structural network analysis

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10.1016/j.ins.2018.11.011

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title = "On the degeneracy of the Randi{\'c} entropy and related graph measures",

abstract = "Numerous quantitative graph measures have been defined and applied in various disciplines. Such measures may be differentiated according to whether they are information-theoretic or non-information-theoretic. In this paper, we examine an important property of Randi{\'c} entropy, an information-theoretic measure, and examine some related graph measures based on random roots. In particular, we investigate the degeneracy of these structural graph measures and discuss numerical results. Finally, we draw some conclusions about the measures{\textquoteright} applicability to deterministic and non-deterministic networks.",

keywords = "Data science, Graphs, Networks, Quantitative graph theory, Structural graph measures, Structural network analysis",

author = "Matthias Dehmer and Zengqiang Chen and Abbe Mowshowitz and Herbert Jodlbauer and F. Emmert-Streib and Yongtang Shi and Shailesh Tripathi and Chengyi Xia",

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year = "2019",

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doi = "10.1016/j.ins.2018.11.011",

language = "English",

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AU - Dehmer, Matthias

AU - Chen, Zengqiang

AU - Mowshowitz, Abbe

AU - Jodlbauer, Herbert

AU - Emmert-Streib, F.

AU - Shi, Yongtang

AU - Tripathi, Shailesh

AU - Xia, Chengyi

PY - 2019/10

Y1 - 2019/10

N2 - Numerous quantitative graph measures have been defined and applied in various disciplines. Such measures may be differentiated according to whether they are information-theoretic or non-information-theoretic. In this paper, we examine an important property of Randić entropy, an information-theoretic measure, and examine some related graph measures based on random roots. In particular, we investigate the degeneracy of these structural graph measures and discuss numerical results. Finally, we draw some conclusions about the measures’ applicability to deterministic and non-deterministic networks.

AB - Numerous quantitative graph measures have been defined and applied in various disciplines. Such measures may be differentiated according to whether they are information-theoretic or non-information-theoretic. In this paper, we examine an important property of Randić entropy, an information-theoretic measure, and examine some related graph measures based on random roots. In particular, we investigate the degeneracy of these structural graph measures and discuss numerical results. Finally, we draw some conclusions about the measures’ applicability to deterministic and non-deterministic networks.

KW - Data science

KW - Graphs

KW - Networks

KW - Quantitative graph theory

KW - Structural graph measures

KW - Structural network analysis

UR - https://www.scopus.com/pages/publications/85057760552

U2 - 10.1016/j.ins.2018.11.011

DO - 10.1016/j.ins.2018.11.011

M3 - Article

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SN - 0020-0255

VL - 501

SP - 680

EP - 687

JO - Information Sciences

JF - Information Sciences

ER -

On the degeneracy of the Randić entropy and related graph measures

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Keywords

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