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@Article{MaiaOlivQuilMaca:2017:CoDeCo,
               author = "Maia, Daniel Marcos Nogueira and Oliveira, Jo{\~a}o Eliakin Mota 
                         de and Quiles, Marcos G. and Macau, Elbert Einstein Nehrer",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade Federal 
                         de S{\~a}o Paulo (UNIFESP)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Community detection in complex networks via adapted Kuramoto 
                         dynamics",
              journal = "Communications in Nonlinear Science and Numerical Simulation",
                 year = "2017",
               volume = "53",
                pages = "130--141",
                month = "Dec.",
             keywords = "Community detection, Kuramoto model.",
             abstract = "Based on the Kuramoto model, a new network model, namely, the 
                         generalized Kuramoto model with Fourier term, is introduced for 
                         studying community detection in complex networks. In particular, 
                         the Fourier term provides a natural phase locking of the 
                         trajectories into a pre-defined number of clusters. A mathematical 
                         approach is used to study the behavior of the solutions and its 
                         properties. Conditions for properly choosing the coupling 
                         parameters so that phase locking takes place are presented and a 
                         quality function called clustering density is introduced to 
                         measure the effectiveness of the communities identification. 
                         Illustrations with real and synthetic networks with community 
                         structure are presented.",
                  doi = "10.1016/j.cnsns.2017.05.002",
                  url = "http://dx.doi.org/10.1016/j.cnsns.2017.05.002",
                 issn = "1007-5704",
             language = "en",
           targetfile = "maia_community.pdf",
        urlaccessdate = "23 nov. 2020"
}


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