6 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…
EC-SBM Synthetic Network Generator
The-Anh Vu-Le, Lahari Anne, George Chacko +1
Generating high-quality synthetic networks with realistic community structure is vital to effectively evaluate community detection algorithms. In this study, we propose a new synth…
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…