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Network Entropies Based on Independent Sets and Matchings

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  • Cao, Shujuan
  • Dehmer, Matthias
  • Kang, Zhe

Abstract

Entropy-based measures have been used to characterize the structure of complex networks. Various graph entropies based on different graph parameters have been proposed and studied. So, it has been intricate to decide which measure is the right one for solving a particular problem. In this paper, we introduce graph entropy measures based on independent sets and matchings of graphs. The values of entropies of some special graphs are calculated and we draw several conclusions regrading the usability of the measures. Based on our findings, we conclude that it should be demanding studying extremal values of the novel entropies.

Suggested Citation

  • Cao, Shujuan & Dehmer, Matthias & Kang, Zhe, 2017. "Network Entropies Based on Independent Sets and Matchings," Applied Mathematics and Computation, Elsevier, vol. 307(C), pages 265-270.
    • Handle: RePEc:eee:apmaco:v:307:y:2017:i:c:p:265-270
    DOI: 10.1016/j.amc.2017.02.021
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    References listed on IDEAS

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    1. Cao, Shujuan & Dehmer, Matthias, 2015. "Degree-based entropies of networks revisited," Applied Mathematics and Computation, Elsevier, vol. 261(C), pages 141-147.
    2. Shi, Yongtang, 2015. "Note on two generalizations of the Randić index," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 1019-1025.
    3. Chen, Zengqiang & Dehmer, Matthias & Shi, Yongtang, 2015. "Bounds for degree-based network entropies," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 983-993.
    4. Yu, Guihai & Liu, Xin & Qu, Hui, 2017. "Singularity of Hermitian (quasi-)Laplacian matrix of mixed graphs," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 287-292.
    5. Lang, Rongling & Li, Tao & Mo, Desen & Shi, Yongtang, 2016. "A novel method for analyzing inverse problem of topological indices of graphs using competitive agglomeration," Applied Mathematics and Computation, Elsevier, vol. 291(C), pages 115-121.
    6. Matthias Dehmer & Abbe Mowshowitz & Yongtang Shi, 2014. "Structural Differentiation of Graphs Using Hosoya-Based Indices," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-4, July.
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    Cited by:

    1. Lei, Hui & Li, Tao & Ma, Yuede & Wang, Hua, 2018. "Analyzing lattice networks through substructures," Applied Mathematics and Computation, Elsevier, vol. 329(C), pages 297-314.
    2. Wan, Pengfei & Tu, Jianhua & Zhang, Shenggui & Li, Binlong, 2018. "Computing the numbers of independent sets and matchings of all sizes for graphs with bounded treewidth," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 42-47.
    3. Lan, Yongxin & Li, Tao & Ma, Yuede & Shi, Yongtang & Wang, Hua, 2018. "Vertex-based and edge-based centroids of graphs," Applied Mathematics and Computation, Elsevier, vol. 331(C), pages 445-456.
    4. Mikołaj Morzy & Tomasz Kajdanowicz & Przemysław Kazienko, 2017. "On Measuring the Complexity of Networks: Kolmogorov Complexity versus Entropy," Complexity, Hindawi, vol. 2017, pages 1-12, November.
    5. Yu, Guihai & Qu, Hui, 2018. "The coefficients of the immanantal polynomial," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 38-44.
    6. Ma, Yuede & Cao, Shujuan & Shi, Yongtang & Dehmer, Matthias & Xia, Chengyi, 2019. "Nordhaus–Gaddum type results for graph irregularities," Applied Mathematics and Computation, Elsevier, vol. 343(C), pages 268-272.
    7. Wan, Pengfei & Tu, Jianhua & Dehmer, Matthias & Zhang, Shenggui & Emmert-Streib, Frank, 2019. "Graph entropy based on the number of spanning forests of c-cyclic graphs," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
    8. Ghorbani, Modjtaba & Dehmer, Matthias & Rajabi-Parsa, Mina & Emmert-Streib, Frank & Mowshowitz, Abbe, 2019. "Hosoya entropy of fullerene graphs," Applied Mathematics and Computation, Elsevier, vol. 352(C), pages 88-98.
    9. Lan, Yongxin & Li, Tao & Wang, Hua & Xia, Chengyi, 2019. "A note on extremal trees with degree conditions," Applied Mathematics and Computation, Elsevier, vol. 341(C), pages 70-79.
    10. Wang, Juan & Li, Chao & Xia, Chengyi, 2018. "Improved centrality indicators to characterize the nodal spreading capability in complex networks," Applied Mathematics and Computation, Elsevier, vol. 334(C), pages 388-400.

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