Quantitative Graph Theory: A new branch of graph theory and network science

Matthias Dehmer, Frank Emmert-Streib, Yongtang Shi

    Research output: Contribution to journalArticleScientificpeer-review

    17 Citations (Scopus)

    Abstract

    In this paper, we describe some highlights of the new branch QUANTITATIVE GRAPH THEORY and explain its significant different features compared to classical graph theory. The main goal of quantitative graph theory is the structural quantification of information contained in complex networks by employing a measurement approach based on numerical invariants and comparisons. Furthermore, the methods as well as the networks do not need to be deterministic but can be statistic. As such this complements the field of classical graph theory, which is descriptive and deterministic in nature. We provide examples of how quantitative graph theory can be used for novel applications in the context of the overarching concept network science.

    Original languageEnglish
    Pages (from-to)575-580
    Number of pages6
    JournalInformation Sciences
    Volume418-419
    DOIs
    Publication statusPublished - 1 Dec 2017
    Publication typeA1 Journal article-refereed

    Keywords

    • Data Science
    • Graphs
    • Networks
    • Quantitative Graph Theory
    • Statistics

    Publication forum classification

    • Publication forum level 1

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Theoretical Computer Science
    • Software
    • Computer Science Applications
    • Information Systems and Management
    • Artificial Intelligence

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