Modularity maximization to find community structure in complex networks
| dc.contributor.author | Saoud, Bilal | |
| dc.date.accessioned | 2024-03-12T18:10:04Z | |
| dc.date.available | 2024-03-12T18:10:04Z | |
| dc.date.issued | 2021-05-25 | |
| dc.description.abstract | Complex networks have in generally communities. These communities are very important. Network’s communities represent sets of nodes, which are very connected. In this research, we developed a new method to find the community structure in networks. Our method is based on flower pollination algorithm (FPA) witch is used in the splitting process. The splitting of networks in our method maximizes a function of quality called modularity. We provide a general framework for implementing our new method to find community structure in networks. We present the effectiveness of our method by comparison with some known methods on computer-generated and real-world networks. | |
| dc.identifier.isbn | 978-9931-9788-0-0 | |
| dc.identifier.uri | http://dspace.univ-oeb.dz:4000/handle/123456789/18727 | |
| dc.language.iso | en | |
| dc.publisher | University of Oum El Bouaghi | |
| dc.subject | Community detection; networks; flower pollination algorithm; normalized mutual information; modularity | |
| dc.title | Modularity maximization to find community structure in complex networks | |
| dc.type | Article |
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