Results 51 to 60 of about 1,651,191 (277)
A vertex-similarity clustering algorithm for community detection
Journal of Information and Telecommunication, 2020 Communities in networks are considered to be groups of vertices with higher probability of being connected to each other than to members of other groups.
Antonio Maria Fiscarelli +3 more
doaj +1 more source
A Memetic Algorithm for Community Detection in Signed Networks
IEEE Access, 2020 Community discovery (i.e. community detection) in signed networks is a division of nodes, such that the edges in the communities are positive and the edges between the communities are negative.
Shiwei Che, Wu Yang, Wei Wang
doaj +1 more source
Different approaches to community detection
, 2017 A precise definition of what constitutes a community in networks has remained elusive. Consequently, network scientists have compared community detection algorithms on benchmark networks with a particular form of community structure and classified them ...
Aicher C. +4 more
core +1 more source
Community Detection for Correlation Matrices [PDF]
Physical Review X, 2015 Final version, accepted for publication on ...
MacMahon, M., Garlaschelli, D.
openaire +5 more sources
Generating Ensembles of Gene Regulatory Networks to Assess Robustness of Disease Modules
Frontiers in Genetics, 2021 The use of biological networks such as protein–protein interaction and transcriptional regulatory networks is becoming an integral part of genomics research.
James T. Lim +4 more
doaj +1 more source
Community detection and graph partitioning
, 2013 Many methods have been proposed for community detection in networks. Some of the most promising are methods based on statistical inference, which rest on solid mathematical foundations and return excellent results in practice.
Newman, M. E. J.
core +1 more source
Statistical mechanics of community detection [PDF]
Physical Review E, 2006 Starting from a general \textit{ansatz}, we show how community detection can be interpreted as finding the ground state of an infinite range spin glass. Our approach applies to weighted and directed networks alike. It contains the \textit{at hoc} introduced quality function from \cite{ReichardtPRL} and the modularity $Q$ as defined by Newman and Girvan
Reichardt, Joerg, Bornholdt, Stefan
openaire +3 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Parents of children treated for acute lymphoblastic leukemia (ALL) often experience significant caregiver burden and disruption to their well‐being. While parent quality of life (QoL) during treatment is well characterized, little is known about outcomes during early survivorship.
Sara Dal Pra +3 more
wiley +1 more source
Adaptive Weights Community Detection
, 2022 Due to the technological progress of the last decades, Community Detection has become a major topic in machine learning. However, there is still a huge gap between practical and theoretical results, as theoretically optimal procedures often lack a feasible implementation and vice versa.
Besold, Franz, Spokoiny, Vladimir
openaire +4 more sources
Detecting communities using asymptotical surprise [PDF]
Physical Review E, 2015 Nodes in real-world networks are repeatedly observed to form dense clusters, often referred to as communities. Methods to detect these groups of nodes usually maximize an objective function, which implicitly contains the definition of a community. We here analyze a recently proposed measure called surprise, which assesses the quality of the partition ...
Traag, V.A., Aldecoa, R., Delvenne, J.C.
openaire +5 more sources