9 papers
On the Optimization of Methods for Establishing Well-Connected Communities
Mohammad Dindoost, Oliver Alvarado Rodriguez, Bartosz Bryg +4
Community detection plays a central role in uncovering meso scale structures in networks. However, existing methods often suffer from disconnected or weakly connected clusters, und…
Dense Subgraph Clustering and a New Cluster Ensemble Method
The-Anh Vu-Le, João Alfredo Cardoso Lamy, Tomás Alessi +5
We propose DSC-Flow-Iter, a new community detection algorithm that is based on iterative extraction of dense subgraphs. Although DSC-Flow-Iter leaves many nodes unclustered, it is…
Using Stochastic Block Models for Community Detection: The issue of edge-connectivity
The-Anh Vu-Le, Minhyuk Park, Ian Chen +2
A relevant, sometimes overlooked, quality criterion for communities in graphs is that they should be well-connected in addition to being edge-dense. Prior work has shown that leadi…
An Agent-based Model of Citation Behavior
George Chacko, Minhyuk Park, Vikram Ramavarapu +3
Whether citations can be objectively and reliably used to measure productivity and scientific quality of articles and researchers can, and should, be vigorously questioned. However…
FastEnsemble: scalable ensemble clustering on large networks
Yasamin Tabatabaee, Eleanor Wedell, Minhyuk Park +1
Many community detection algorithms are inherently stochastic, leading to variations in their output depending on input parameters and random seeds. This variability makes the resu…
Improved Community Detection using Stochastic Block Models
Minhyuk Park, Daniel Wang Feng, Siya Digra +4
Identifying edge-dense communities that are also well-connected is an important aspect of understanding community structure. Prior work has shown that community detection methods c…