Local volume dimension: A novel approach for important nodes identification in complex networks

How to identify important nodes in complex networks? It is still an open problem. Many methods have been proposed to tackle this problem. The main contribution of this paper is to propose a method ...

[1]  Kang Hao Cheong,et al.  A time-based switching scheme for nomadic-colonial alternation under noisy conditions , 2017, Commun. Nonlinear Sci. Numer. Simul..

[2]  Qi Wang,et al.  Extracting the Globally and Locally Adaptive Backbone of Complex Networks , 2014, PloS one.

[3]  Kang Hao Cheong,et al.  Periodic habitat destruction and migration can paradoxically enable sustainable territorial expansion , 2019, Nonlinear Dynamics.

[4]  Daijun Wei,et al.  A generalized volume dimension of complex networks , 2014 .

[5]  Lada A. Adamic,et al.  The political blogosphere and the 2004 U.S. election: divided they blog , 2005, LinkKDD '05.

[6]  Herbert W. Hethcote,et al.  The Mathematics of Infectious Diseases , 2000, SIAM Rev..

[7]  Jie Cao,et al.  Dynamic Cluster Formation Game for Attributed Graph Clustering , 2019, IEEE Transactions on Cybernetics.

[8]  Qi Liu,et al.  Identifying influential nodes based on local dimension , 2014 .

[9]  Yong Deng,et al.  Vital Spreaders Identification in Complex Networks with Multi-Local Dimension , 2019, Knowl. Based Syst..

[10]  Zhen Jin,et al.  Spatial dynamics of an epidemic model with nonlocal infection , 2020, Appl. Math. Comput..

[11]  Eric Rosenberg.  Generalized Hausdorff dimensions of a complex network , 2018, Physica A: Statistical Mechanics and its Applications.

[12]  Weiren Shi,et al.  Evaluating the importance of nodes in complex networks , 2016 .

[13]  Chen Dong,et al.  Ranking the spreading influence of nodes in complex networks based on mixing degree centrality and local structure , 2019, International Journal of Modern Physics B.

[14]  Michalis Vazirgiannis,et al.  Locating influential nodes in complex networks , 2016, Scientific Reports.

[15]  K. H. Cheong,et al.  Cross-issue solidarity and truth convergence in opinion dynamics , 2017, Journal of Physics A: Mathematical and Theoretical.

[16]  M. Newman,et al.  Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  Kang Hao Cheong,et al.  Parrondo’s paradox from classical to quantum: A review , 2020 .

[18]  Benedict Mondal,et al.  Exponential structure of income inequality: evidence from 67 countries , 2016 .

[19]  Kang Hao Cheong,et al.  Parrondo’s paradox and complementary Parrondo processes , 2013 .

[20]  Qi Zhang,et al.  Identifying influential nodes in complex networks based on the inverse-square law , 2018, Physica A: Statistical Mechanics and its Applications.

[21]  J. Bory‐Reyes,et al.  A box-covering Tsallis information dimension and non-extensive property of complex networks , 2020 .

[22]  Qian Wang,et al.  Classifying superheavy elements by machine learning , 2019, Physical Review A.

[23]  Hua Dong,et al.  Spectrally negative Lévy risk model under Erlangized barrier strategy , 2019, J. Comput. Appl. Math..

[24]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .

[25]  Yicheng Zhang,et al.  Identifying influential nodes in complex networks , 2012 .

[26]  Yong Deng,et al.  The vulnerability of communities in complex network: An entropy approach , 2019, Reliab. Eng. Syst. Saf..

[27]  Phillip Bonacich,et al.  Eigenvector-like measures of centrality for asymmetric relations , 2001, Soc. Networks.

[28]  Jürgen Kurths,et al.  Effects of network robustness on explosive synchronization. , 2019, Physical review. E.

[29]  Pablo M. Gleiser,et al.  Community Structure in Jazz , 2003, Adv. Complex Syst..

[30]  Yang Liu,et al.  Framework of Evolutionary Algorithm for Investigation of Influential Nodes in Complex Networks , 2019, IEEE Transactions on Evolutionary Computation.

[31]  Yong Deng,et al.  Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks , 2016, PloS one.

[32]  Tao Zhou,et al.  The H-index of a network node and its relation to degree and coreness , 2016, Nature Communications.

[33]  Mark E. J. Newman.  A measure of betweenness centrality based on random walks , 2005, Soc. Networks.

[34]  Chin-Teng Lin,et al.  A Fuzzy Interval Time-Series Energy and Financial Forecasting Model Using Network-Based Multiple Time-Frequency Spaces and the Induced-Ordered Weighted Averaging Aggregation Operation , 2020, IEEE Transactions on Fuzzy Systems.

[35]  Yong Deng,et al.  Alternatives selection for produced water management: A network-based methodology , 2020, Eng. Appl. Artif. Intell..

[36]  Tong Li,et al.  Self-organized interdependence among populations promotes cooperation by means of coevolution. , 2019, Chaos.

[37]  Lidia A. Braunstein,et al.  Containing misinformation spreading in temporal social networks , 2019, Chaos.

[38]  Lev Muchnik,et al.  Identifying influential spreaders in complex networks , 2010, 1001.5285.

[39]  P. Jena,et al.  Penta-BCN: A New Ternary Pentagonal Monolayer with Intrinsic Piezoelectricity. , 2020, The journal of physical chemistry letters.

[40]  Yong Deng,et al.  Network-based evidential three-way theoretic model for large-scale group decision analysis , 2021, Inf. Sci..

[41]  Pengli Lu,et al.  A mixed clustering coefficient centrality for identifying essential proteins , 2020, 2003.05057.

[42]  Ye Ye,et al.  Passive network evolution promotes group welfare in complex networks , 2019, Chaos, Solitons & Fractals.

[43]  A. Karci,et al.  Comparisons of Karcı and Shannon entropies and their effects on centrality of social networks , 2019, Physica A: Statistical Mechanics and its Applications.

[44]  Kang Hao Cheong,et al.  Occurrence of complementary processes in Parrondo’s paradox , 2014 .

[45]  Mahdi Jalili,et al.  Identification of influential users in social network using gray wolf optimization algorithm , 2020, Expert Syst. Appl..

[46]  Kang Hao Cheong,et al.  Construction of novel stochastic matrices for analysis of Parrondo’s paradox , 2013 .

[47]  Yong Deng,et al.  An Efficient Network Method for Time Series Forecasting Based on the DC Algorithm and Visibility Relation , 2020, IEEE Access.

[48]  Kang Hao Cheong,et al.  Multicellular survival as a consequence of Parrondo’s paradox , 2018, Proceedings of the National Academy of Sciences.

[49]  R. Tao,et al.  Electrorheology leads to healthier and tastier chocolate , 2016, Proceedings of the National Academy of Sciences.

[50]  G. Pazour,et al.  Ror2 signaling regulates Golgi structure and transport through IFT20 for tumor invasiveness , 2017, Scientific Reports.

[51]  Xuelong Li,et al.  The effect of multigame on cooperation in spatial network , 2019, Appl. Math. Comput..

[52]  Lucas Lacasa,et al.  Visibility Graphs for Image Processing , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[53]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[54]  M. Newman.  Analysis of weighted networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[55]  Kang Hao Cheong,et al.  Multi-level information fusion to alleviate network congestion , 2020, Inf. Fusion.

[56]  Bin Ge,et al.  Identifying Node Importance in a Complex Network Based on Node Bridging Feature , 2018, Applied Sciences.

[57]  Joel Weijia Lai,et al.  Social dynamics and Parrondo’s paradox: a narrative review , 2020, Nonlinear Dynamics.

[58]  Wen Jiang,et al.  Evaluating Topological Vulnerability Based on Fuzzy Fractal Dimension , 2018, Int. J. Fuzzy Syst..

[59]  Yi-Cheng Zhang,et al.  Leaders in Social Networks, the Delicious Case , 2011, PloS one.

[60]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[61]  Albert-László Barabási,et al.  Network-based prediction of protein interactions , 2018, Nature Communications.

[62]  R. Tao,et al.  Electric field suppressed turbulence and reduced viscosity of asphaltene base crude oil sample , 2018 .

[63]  Zhen Wang,et al.  GMM: A generalized mechanics model for identifying the importance of nodes in complex networks , 2020, Knowl. Based Syst..

[64]  Wen Jiang,et al.  A Novel Z-Network Model Based on Bayesian Network and Z-Number , 2020, IEEE Transactions on Fuzzy Systems.

[65]  Yong Deng,et al.  Identifying influential nodes in complex networks from global perspective , 2020, Chaos, Solitons & Fractals.

[66]  Guanrong Chen,et al.  Behaviors of susceptible-infected epidemics on scale-free networks with identical infectivity. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[67]  Yong Deng,et al.  Identification of influencers in complex networks by local information dimension , 2019, Inf. Sci..

[68]  Yong Deng,et al.  Identifying influential nodes in complex networks: A node information dimension approach. , 2018, Chaos.