3 citations · 5 across the 7 of their papers we have counts for
10 papers
Improved Methods for k-core Community Search
Ian Chen, Haotian Yi, Arun Sharma +2
Community search based on user-specified query nodes is complementary to community finding or graph clustering. Prior work in community search is divided into optimizing for extern…
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…
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…
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…