A review of relational machine learning for knowledge graphs
Relational machine learning studies methods for the statistical analysis of relational, or
graph-structured, data. In this paper, we provide a review of how such statistical models can …
graph-structured, data. In this paper, we provide a review of how such statistical models can …
A brief history of statistical models for network analysis and open challenges
SE Fienberg - Journal of Computational and Graphical Statistics, 2012 - Taylor & Francis
Networks are ubiquitous in science. They have also become a focal point for discussion in
everyday life. Formal statistical models for the analysis of network data have emerged as a …
everyday life. Formal statistical models for the analysis of network data have emerged as a …
Stochastic blockmodels and community structure in networks
B Karrer, MEJ Newman - Physical Review E—Statistical, Nonlinear, and Soft …, 2011 - APS
Stochastic blockmodels have been proposed as a tool for detecting community structure in
networks as well as for generating synthetic networks for use as benchmarks. Most …
networks as well as for generating synthetic networks for use as benchmarks. Most …
Hierarchical block structures and high-resolution model selection in large networks
TP Peixoto - Physical Review X, 2014 - APS
Discovering and characterizing the large-scale topological features in empirical networks
are crucial steps in understanding how complex systems function. However, most existing …
are crucial steps in understanding how complex systems function. However, most existing …
Estimation and prediction for stochastic blockstructures
K Nowicki, TAB Snijders - Journal of the American statistical …, 2001 - Taylor & Francis
A statistical approach to a posteriori blockmodeling for digraphs and valued digraphs is
proposed. The probability model assumes that the vertices of the digraph are partitioned into …
proposed. The probability model assumes that the vertices of the digraph are partitioned into …
[图书][B] Network analysis: methodological foundations
U Brandes - 2005 - books.google.com
'Network'is a heavily overloaded term, so that 'network analysis' means different things to
different people. Specific forms of network analysis are used in the study of diverse …
different people. Specific forms of network analysis are used in the study of diverse …
Estimation and prediction for stochastic blockmodels for graphs with latent block structure
TAB Snijders, K Nowicki - Journal of classification, 1997 - Springer
a posteriori blockmodeling for graphs is proposed. The model assumes that the vertices of
the graph are partitioned into two unknown blocks and that the probability of an edge …
the graph are partitioned into two unknown blocks and that the probability of an edge …
[图书][B] An introduction to exponential random graph modeling
JK Harris - 2013 - books.google.com
This volume introduces the basic concepts of Exponential Random Graph Modeling
(ERGM), gives examples of why it is used, and shows the reader how to conduct basic …
(ERGM), gives examples of why it is used, and shows the reader how to conduct basic …
Role discovery in networks
Roles represent node-level connectivity patterns such as star-center, star-edge nodes, near-
cliques or nodes that act as bridges to different regions of the graph. Intuitively, two nodes …
cliques or nodes that act as bridges to different regions of the graph. Intuitively, two nodes …
The many facets of community detection in complex networks
Community detection, the decomposition of a graph into essential building blocks, has been
a core research topic in network science over the past years. Since a precise notion of what …
a core research topic in network science over the past years. Since a precise notion of what …