2019/07/19 by Alexander Ponomarenko, Ponomarenko, Alexander, Leonidas Pitsoulis +3 · 1 citation
Computer Science · Physics and Astronomy · #Caching and Content Delivery #Complex Network Analysis Techniques #Discrete Mathematics (cs.DM) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Network Traffic and Congestion Control #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1907.08731
openalex publication_date 2019/07/19 · openalex created_date 2022/07/28 · openalex updated_date 2026/07/28
In this paper, we present a new method for detecting overlapping communities\nin networks with a predefined number of clusters called LPAM (Link Partitioning\nAround Medoids). The overlapping communities in the graph are obtained by\ndetecting the disjoint communities in the associated line graph employing link\npartitioning and partitioning around medoids which are done through the use of\na distance function defined on the set of nodes. We consider both the commute\ndistance and amplified commute distance as distance functions. The performance\nof the LPAM method is evaluated with computational experiments on real life\ninstances, as well as synthetic network benchmarks. For small and medium-size\nnetworks, the exact solution was found, while for large networks we found\nsolutions with a heuristic version of the LPAM method.\n