Open AccessOverlapping community detection in networks based on link partitioning and partitioning around medoids
Author(s) -
Alexander Ponomarenko,
Leonidas Pitsoulis,
Marat Shamshetdinov
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0255717
Subject(s) - medoid , graph partition , computer science , disjoint sets , graph , heuristic , cluster analysis , link (geometry) , set (abstract data type) , algorithm , theoretical computer science , combinatorics , mathematics , artificial intelligence , computer network , programming language
In this paper, we present a new method for detecting overlapping communities in networks with a predefined number of clusters called LPAM (Link Partitioning Around Medoids). The overlapping communities in the graph are obtained by detecting the disjoint communities in the associated line graph employing link partitioning and partitioning around medoids which are done through the use of a distance function defined on the set of nodes. We consider both the commute distance and amplified commute distance as distance functions. The performance of the LPAM method is evaluated with computational experiments on real life instances, as well as synthetic network benchmarks. For small and medium-size networks, the exact solution was found, while for large networks we found solutions with a heuristic version of the LPAM method.