A survey of continuous subgraph matching for dynamic graphs
With the rapid development of information technologies, multi-source heterogeneous data
has become an open problem, and the data is usually modeled as graphs since the graph …
has become an open problem, and the data is usually modeled as graphs since the graph …
Approximating betweenness centrality
Betweenness is a centrality measure based on shortest paths, widely used in complex
network analysis. It is computationally-expensive to exactly determine betweenness; …
network analysis. It is computationally-expensive to exactly determine betweenness; …
A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks
A Slepoy, AP Thompson, SJ Plimpton - The journal of chemical …, 2008 - pubs.aip.org
The time evolution of species concentrations in biochemical reaction networks is often
modeled using the stochastic simulation algorithm (SSA)[Gillespie, J. Phys. Chem. 81, 2340 …
modeled using the stochastic simulation algorithm (SSA)[Gillespie, J. Phys. Chem. 81, 2340 …
Privacy-preserving graph matching query supporting quick subgraph extraction
Graph matching, as one of the most fundamental problems in graph database, has a wide
range of applications. Due to the large scale of graph database and the hardness of graph …
range of applications. Due to the large scale of graph database and the hardness of graph …
Snap, small-world network analysis and partitioning: An open-source parallel graph framework for the exploration of large-scale networks
We present SNAP (Small-world Network Analysis and Partitioning), an open-source graph
framework for exploratory study and partitioning of large-scale networks. To illustrate the …
framework for exploratory study and partitioning of large-scale networks. To illustrate the …
Hadi: Mining radii of large graphs
Given large, multimillion-node graphs (eg, Facebook, Web-crawls, etc.), how do they evolve
over time? How are they connected? What are the central nodes and the outliers? In this …
over time? How are they connected? What are the central nodes and the outliers? In this …
[PDF][PDF] Crossing the mesoscale no-man's land via parallel kinetic Monte Carlo
S Plimpton, C Battaile, M Chandross… - Sandia Report …, 2009 - academia.edu
Abstract The kinetic Monte Carlo method and its variants are powerful tools for modeling
materials at the mesoscale, meaning at length and time scales in between the atomic and …
materials at the mesoscale, meaning at length and time scales in between the atomic and …
From QSAR models of drugs to complex networks: state-of-art review and introduction of new Markov-spectral moments indices
P Riera-Fernández, R Martin-Romalde… - Current Topics in …, 2012 - ingentaconnect.com
Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) models have been
largely used for different kind of problems in Medicinal Chemistry and other Biosciences as …
largely used for different kind of problems in Medicinal Chemistry and other Biosciences as …
Big graph mining: algorithms and discoveries
U Kang, C Faloutsos - ACM SIGKDD Explorations Newsletter, 2013 - dl.acm.org
How do we find patterns and anomalies in very large graphs with billions of nodes and
edges? How to mine such big graphs efficiently? Big graphs are everywhere, ranging from …
edges? How to mine such big graphs efficiently? Big graphs are everywhere, ranging from …