Paper Info
Title
Comparison of Local and Global Ranking in Networks.
Abstract
Many real world data and processes have a network structure and can usefully be represented as graphs. Network analysis focuses on the relations among the nodes exploring the properties of each network. Latest trend in analyzing networks is to focus on local methods and parallelization. We introduce a method to find the ranking of the nodes. The approach extracts dependency relations among the network's nodes. Key technical parameter of the approach is locality. Since only the surrounding of examined nodes is used in computations, there is no need to analyze the entire network. We compare this proposed local ranking to the global ranking of PageRank. We present experiment using large-scale artificial and real world networks. The results of experiment show high effectiveness due to the locality of our approach and also high quality of node ranking comparable to PageRank.
Year
DOI
Venue
2014
10.1007/978-3-319-08156-4_35
PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INNOVATIONS IN BIO-INSPIRED COMPUTING AND APPLICATIONS (IBICA 2014)
Keywords
DocType
Volume
complex networks,graphs,node weighting,dependency,ranking
Conference
303
ISSN
Citations 
PageRank 
2194-5357
0
0.34
References 
Authors
8
5
Name
Order
Citations
PageRank
Sarka Zehnalova184.83
Milos Kudelka211623.81
Zdenek Horak38712.96
Krömer Pavel433059.99
Václav Snasel51261210.53