An a posteriori measure of network modularity
نویسندگان
چکیده
منابع مشابه
An a posteriori measure of network modularity
Measuring modularity is important to understand the structure of networks, and has an important number of real-world implications. However, several measures exists to assess the modularity, and give both different modularity values and different modules composition. In this article, I propose an a posteriori measure of modularity, which represents the ratio of interactions between members of th...
متن کاملLocal modularity measure for network clusterizations.
Many complex networks have an underlying modular structure, i.e., structural subunits (communities or clusters) characterized by highly interconnected nodes. The modularity has been introduced as a measure to assess the quality of clusterizations. has a global view, while in many real-world networks clusters are linked mainly locally among each other (local cluster connectivity). Here we introd...
متن کاملVulnerability Measure of a Network - a Survey
In this paper we discuss about tenacity and its properties in stability calculation. We indicate relationships between tenacity and connectivity, tenacity and binding number, tenacity and toughness. We also give good lower and upper bounds for tenacity. Since we are primarily interested in the case where disruption of the graph is caused by the removal of a vertex or vertices (and the resulting...
متن کاملAn Information-Theoretic Approach to Network Modularity
Exploiting recent developments in information theory, we propose, illustrate, and validate a principled information-theoretic algorithm for module discovery and resulting measure of network modularity. This measure is an order parameter (a dimensionless number between 0 and 1). Comparison is made to other approaches to module-discovery and to quantifying network modularity using Monte Carlo gen...
متن کاملClustering Categorical Data Using an Extended Modularity Measure
Newman and Girvan [12] recently proposed an objective function for graph clustering called the Modularity function which allows automatic selection of the number of clusters. Empirically, higher values of the Modularity function have been shown to correlate well with good graph clustering. In this paper we propose an extended Modularity measure for categorical data clustering; first, we establi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: F1000Research
سال: 2013
ISSN: 2046-1402
DOI: 10.12688/f1000research.2-130.v1