Title :
Lossy Compression of Dynamic, Weighted Graphs
Author :
Wilko Henecka;Matthew Roughan
Author_Institution :
Sch. of Math. Sci., Univ. of Adelaide, Adelaide, SA, Australia
Abstract :
A graph is used to represent data in which the relationships between the objects in the data are at least as important as the objects themselves. Large graph datasets are becoming more common as networks such as the Internet grow, and our ability to measure these graphs improves. This necessitates methods to compress these datasets. In this paper we present a method aimed at lossy compression of large, dynamic, weighted graphs.
Keywords :
"Approximation methods","Approximation algorithms","Weight measurement","Heuristic algorithms","Social network services","Noise"
Conference_Titel :
Future Internet of Things and Cloud (FiCloud), 2015 3rd International Conference on
DOI :
10.1109/FiCloud.2015.64
