@Article{ChagasLoreSant:2022:HyHeOv,
               author = "Chagas, Guilherme Oliveira and Lorena, Luiz Antonio Nogueira and 
                         Santos, Rafael Duarte Coelho dos",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "A hybrid heuristic for overlapping community detection through the 
                         conductance minimization",
              journal = "Physica A: Statistical Mechanics and its Applications",
                 year = "2022",
               volume = "592",
                pages = "e126887",
                month = "Apr.",
             keywords = "Conductance minimization, Hybrid heuristic, Overlapping community 
                         detection.",
             abstract = "Community structures, which are sets of elements that share some 
                         relationship between themselves, can be found in several 
                         real-world networks. Many of these communities, also known as 
                         clusters, can share elements, i.e., they may overlap. Identifying 
                         such overlapping clusters is usually a harder task than finding 
                         non-overlapping ones and, therefore, it needs more sophisticated 
                         methods. In this work we proposed a hybrid heuristic for detecting 
                         overlapping clusters in networks. An overlapping clustering is 
                         generated through the solving of a mixed-integer linear program 
                         using, as input, a heterogeneous set of good-quality clusters. 
                         This set is produced by two state-of-the-art overlapping community 
                         detection algorithms. In addition, some local search methods for 
                         conductance minimization are used to improve the quality of the 
                         clustering generate by our hybrid heuristic. Test results in 
                         artificial and real-world graphs show that our approach is able to 
                         detect overlapping clusters with better overall conductance than 
                         methods in the state of the art.",
                  doi = "10.1016/j.physa.2022.126887",
                  url = "http://dx.doi.org/10.1016/j.physa.2022.126887",
                 issn = "0378-4371",
             language = "en",
           targetfile = "1-s2.0-S0378437122000231-2022.pdf",
        urlaccessdate = "14 jun. 2024"
}