Modularity maximization is the most popular technique for the detection of community structure in graphs. The resolution limit of the method is supposedly solvable with the introduction of modified versions of the measure, with tunable resolution parameters. We show that multiresolution modularity suffers from two opposite coexisting problems: the tendency to merge small subgraphs, which dominates when the resolution is low; the tendency to split large subgraphs, which dominates when the resolution is high. In benchmark networks with heterogeneous distributions of cluster sizes, the simultaneous elimination of both biases is not possible and multiresolution modularity is not capable to recover the planted community structure, not even when it is pronounced and easily detectable by other methods, for any value of the resolution parameter. This holds for other multiresolution techniques and it is likely to be a general problem of methods based on global optimization.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1103/PhysRevE.84.066122 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Segregation-to-integration transformation model of memory evolution.
Netw Neurosci
December 2024
Department of Cognition, Development and Education Psychology, University of Barcelona, Barcelona, Spain.
Memories are thought to use coding schemes that dynamically adjust their representational structure to maximize both persistence and efficiency. However, the nature of these coding scheme adjustments and their impact on the temporal evolution of memory after initial encoding is unclear. Here, we introduce the Segregation-to-Integration Transformation (SIT) model, a network formalization that offers a unified account of how the representational structure of a memory is transformed over time.
View Article and Find Full Text PDFThe Effect of Modular Degeneracy on Neuroimaging Data.
Brain Connect
December 2024
Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland, USA.
The concept of community structure, based on modularity, is widely used to address many systems-level queries. However, its algorithm, based on the maximization of the modularity index Q, suffers from degeneracy problem, which yields a set of different possible solutions. In this work, we explored the degeneracy effect of modularity principle on resting-state functional magnetic resonance imaging (rsfMRI) data, when it is used to parcellate the cingulate cortex using data from the Human Connectome Project.
View Article and Find Full Text PDFReal world choices often involve balancing decisions that are optimized for the short-vs. long-term. Here, we reason that apparently sub-optimal single trial decisions in macaques may in fact reflect long-term, strategic planning.
View Article and Find Full Text PDFSelective Gas Adsorption in Permanently Microporous Coordination Cages with Exposed Metal Sites.
Inorg Chem
December 2024
Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States.
Porous coordination cages (PCCs), molecular analogs of metal-organic frameworks, offer modular platforms for studying the adsorption properties of small molecules, with coordinatively unsaturated metal centers playing a pivotal role in tuning these behaviors. In this work, we present the synthesis, activation, and detailed gas adsorption studies of second-row transition metal-based ML cuboctahedral cages, specifically Mo(bdc), Rh(bdc), and [Ru(bdc)]Cl. These materials represent rare examples of Mo-, Rh-, and Ru-based hybrid porous solids.
View Article and Find Full Text PDFLignin as a bioderived modular surfactant and intercalant for TiCT MXene stabilization and tunable functions.
Cell Rep Phys Sci
November 2024
Department of Applied Physics, Aalto University, FIN-02150 Espoo, Finland.
Controlled tailoring of atomically thin MXene interlayer spacings by surfactant/intercalants (e.g., polymers, ligands, small molecules) is important to maximize their potential for application.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!