Paper Info
Title
Structural Graph Indexing for Mining Complex Networks
Abstract
Systems such as proteins, chemical compounds, and the Internet are being modeled as complex networks to identify local and global characteristics of the system. In many instances, these graphs are very large in size presenting challenges in their analysis. Hence, graph indexing techniques are developed to enhance various graph mining algorithms. In this paper, we propose a new Structural Graph Indexing (SGI) technique that does not limit the number of nodes in indexing to provide an alternative tool for graph mining algorithms. As indexing feature, we use common graph structures, namely, star, complete bipartite, triangle and clique, that frequently appear in protein, chemical compound, and Internet graphs. Note that, SGI lists all substructures matching structure formulations and other graph structures can be identified and added to the SGI.
Year
DOI
Venue
2010
10.1109/ICDCSW.2010.42
ICDCS Workshops
Keywords
Field
DocType
alternative tool,graph indexing technique,graph structure,complete bipartite,internet graph,chemical compound,structural graph indexing,indexing feature,various graph mining algorithm,graph mining algorithm,mining complex networks,common graph structure,indexing,topology,data mining,internet topology,indexation,internet,complex networks,graph theory,complex network
Graph theory,Data mining,Graph property,Computer science,Bipartite graph,Theoretical computer science,Null graph,Clique-width,Graph (abstract data type),Voltage graph,Complement graph
Conference
Citations 
PageRank 
References 
4
0.38
8
Authors
2
Name
Order
Citations
PageRank
Hakan Kardes1243.52
Mehmet Hadi Günes214916.19