Paper Info
Title
Social based layouts for the increase of locality in graph operations
Abstract
Graphs provide a natural data representation for analyzing the relationships among entities in many application areas. Since the analysis algorithms perform memory intensive operations, it is important that the graph layout is adapted to take advantage of the memory hierarchy. Here, we propose layout strategies based on community detection to improve the in-memory data locality of generic graph algorithms. We conclude that the detection of communities in a graph provides a layout strategy that improves the performance of graph algorithms consistently over other state of the art strategies.
Year
DOI
Venue
2011
10.1007/978-3-642-20149-3_40
Lecture Notes in Computer Science
Keywords
Field
DocType
layout strategy,analysis algorithm,memory intensive operation,in-memory data locality,graph operation,graph layout,generic graph algorithm,community detection,application area,memory hierarchy,natural data representation,performance,data representation
Graph operations,Data mining,Locality,Graph database,Memory hierarchy,External Data Representation,Computer science,Theoretical computer science,Graph rewriting,Graph (abstract data type),Graph Layout
Conference
Volume
ISSN
Citations 
6587
0302-9743
6
PageRank 
References 
Authors
0.57
27
3
Name
Order
Citations
PageRank
Arnau Prat-Pérez122713.44
David Dominguez-Sal218916.35
Josep-Lluis Larriba-Pey3513.37