18 citations · 23 across the 9 of their papers we have counts for
11 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…
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…
RECCS: Realistic Cluster Connectivity Simulator for Synthetic Network Generation
Lahari Anne, The-Anh Vu-Le, Minhyuk Park +2
The limited availability of useful ground-truth communities in real-world networks presents a challenge to evaluating and selecting a "best" community detection method for a given…
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…
Synthetic Networks That Preserve Edge Connectivity
Lahari Anne, The-Anh Vu-Le, Minhyuk Park +2
Since true communities within real-world networks are rarely known, synthetic networks with planted ground truths are valuable for evaluating the performance of community detection…
Improved Community Detection using Stochastic Block Models
Minhyuk Park, Daniel Wang Feng, Siya Digra +3
Community detection approaches resolve complex networks into smaller groups (communities) that are expected to be relatively edge-dense and well-connected. The stochastic block mod…
Well-Connected Communities in Real-World and Synthetic Networks
Minhyuk Park, Yasamin Tabatabaee, Vikram Ramavarapu +7
Integral to the problem of detecting communities through graph clustering is the expectation that they are "well connected". In this respect, we examine five different community de…
Center-Periphery Structure in Communities: Extracellular Vesicles
Eleanor Wedell, Minhyuk Park, Dmitriy Korobskiy +2
Clustering and community detection in networks are of broad interest and have been the subject of extensive research that spans several fields. We are interested in the relatively…