Reference : A Degenerate Agglomerative Hierarchical Clustering Algorithm for Community Detection
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/38403
A Degenerate Agglomerative Hierarchical Clustering Algorithm for Community Detection
English
Fiscarelli, Antonio Maria mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Beliakov, Aleksandr mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > >]
Konchenko, Stanislav mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Bouvry, Pascal mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
2018
Intelligent Information and Database Systems
Nguyen, Ngoc Thanh
Hoang, Duong Hung
Hong, Tzung-Pei
Pham, Hoang
TrawiƄski, Bogdan
Springer
234-242
Yes
International
978-3-319-75416-1
Cham
Switzerland
10th Asian Conference on Intelligent Information and Database Systems
from 19-03-2018 to 21-03-2018
Dong Hoi City
Vietnam
[en] Community detection ; Graph clustering ; Graph theory
[en] Community detection consists of grouping related vertices that usually show high intra-cluster connectivity and low inter-cluster connectivity. This is an important feature that many networks exhibit and detecting such communities can be challenging, especially when they are densely connected. The method we propose is a degenerate agglomerative hierarchical clustering algorithm (DAHCA) that aims at finding a community structure in networks. We tested this method using common classes of graph benchmarks and compared it to some state-of-the-art community detection algorithms.
Luxembourg Centre for Contemporary and Digital History (C2DH) > Digital History & Historiography (DHI) ; Luxembourg Centre for Contemporary and Digital History (C2DH) > Doctoral Training Unit (DTU)
Fonds National de la Recherche - FnR
Researchers ; Professionals
http://hdl.handle.net/10993/38403
https://doi.org/10.1007/978-3-319-75417-8_22
FnR ; FNR10929115 > Andreas Fickers > DHH > Digital History and Hermeneutics > 01/03/2017 > 31/08/2023 > 2016

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