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Quantifying structural complexity of graphs: Information measures in mathematical chemistry

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Quantifying structural complexity of graphs : Information measures in mathematical chemistry. / Dehmer, Matthias; Emmert-Streib, Frank; Tsoy, Yury Robertovich; Varmuza, Kurt.

Quantum Frontiers of Atoms and Molecules. ed. / Mihai V. Putz. Nova Science Publishers, Inc., 2011. p. 479-497.

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Harvard

Dehmer, M, Emmert-Streib, F, Tsoy, YR & Varmuza, K 2011, Quantifying structural complexity of graphs: Information measures in mathematical chemistry. in MV Putz (ed.), Quantum Frontiers of Atoms and Molecules. Nova Science Publishers, Inc., pp. 479-497.

APA

Dehmer, M., Emmert-Streib, F., Tsoy, Y. R., & Varmuza, K. (2011). Quantifying structural complexity of graphs: Information measures in mathematical chemistry. In M. V. Putz (Ed.), Quantum Frontiers of Atoms and Molecules (pp. 479-497). Nova Science Publishers, Inc..

Vancouver

Dehmer M, Emmert-Streib F, Tsoy YR, Varmuza K. Quantifying structural complexity of graphs: Information measures in mathematical chemistry. In Putz MV, editor, Quantum Frontiers of Atoms and Molecules. Nova Science Publishers, Inc. 2011. p. 479-497

Author

Dehmer, Matthias ; Emmert-Streib, Frank ; Tsoy, Yury Robertovich ; Varmuza, Kurt. / Quantifying structural complexity of graphs : Information measures in mathematical chemistry. Quantum Frontiers of Atoms and Molecules. editor / Mihai V. Putz. Nova Science Publishers, Inc., 2011. pp. 479-497

Bibtex - Download

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title = "Quantifying structural complexity of graphs: Information measures in mathematical chemistry",
abstract = "In this chapter, we give a conceptional view about information measures for graphs which can be used to quantify their structural complexity. We focus on treating such measures in the context of mathematical chemistry but we want to mention that those are also applicable for arbitrary complex networks. Besides reviewing the most known information indices often used in chemical graph theory, we propose an information functional that is based on degree-degree associations in a graph. This leads us to a parametric graph entropy measure to quantify the structural information content of a graph. A brief numerical example shows how the measure can be calculated explicitly.",
author = "Matthias Dehmer and Frank Emmert-Streib and Tsoy, {Yury Robertovich} and Kurt Varmuza",
year = "2011",
language = "English",
isbn = "9781616681586",
pages = "479--497",
editor = "Putz, {Mihai V.}",
booktitle = "Quantum Frontiers of Atoms and Molecules",
publisher = "Nova Science Publishers, Inc.",

}

RIS (suitable for import to EndNote) - Download

TY - CHAP

T1 - Quantifying structural complexity of graphs

T2 - Information measures in mathematical chemistry

AU - Dehmer, Matthias

AU - Emmert-Streib, Frank

AU - Tsoy, Yury Robertovich

AU - Varmuza, Kurt

PY - 2011

Y1 - 2011

N2 - In this chapter, we give a conceptional view about information measures for graphs which can be used to quantify their structural complexity. We focus on treating such measures in the context of mathematical chemistry but we want to mention that those are also applicable for arbitrary complex networks. Besides reviewing the most known information indices often used in chemical graph theory, we propose an information functional that is based on degree-degree associations in a graph. This leads us to a parametric graph entropy measure to quantify the structural information content of a graph. A brief numerical example shows how the measure can be calculated explicitly.

AB - In this chapter, we give a conceptional view about information measures for graphs which can be used to quantify their structural complexity. We focus on treating such measures in the context of mathematical chemistry but we want to mention that those are also applicable for arbitrary complex networks. Besides reviewing the most known information indices often used in chemical graph theory, we propose an information functional that is based on degree-degree associations in a graph. This leads us to a parametric graph entropy measure to quantify the structural information content of a graph. A brief numerical example shows how the measure can be calculated explicitly.

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M3 - Chapter

SN - 9781616681586

SP - 479

EP - 497

BT - Quantum Frontiers of Atoms and Molecules

A2 - Putz, Mihai V.

PB - Nova Science Publishers, Inc.

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