loading...
Exploring Local Community Structures in Large Networks
Hong Kong, China December 18-December 22
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WI.2006.722006 IEEE/WIC/ACM International Confe ...
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Feng Luo, Clemson University, USA
James Z. Wang, Clemson University, USA
Eric Promislow, ActiveState Software
In this paper, we extend the concept of degree from single vertex to sub-graph, and present a formal definition of module/community in a network based on this extension. A new locally optimized algorithm is designed to find the module for a given source vertex in a network. Our analysis shows that the complexity of this algorithm is O(K2d), where K is the number of vertices to be explored in the sub-graph and d is the average degree of the vertices in the sub-graph. Based on this algorithm, we implement a JAVA tool, MoNet, for exploring local community structures in large networks. Using this tool to analyze a co-purchase network from Amazon shows that there are local community structures in this network. Further analyses on these local community structures demonstrate that media items are much easier to form compact local modules than book items do, indicating that recommending digital media items to customers based on co-purchasing information in the online store will be more efficient than recommending books.
Citation:
Feng Luo, James Z. Wang, Eric Promislow, "Exploring Local Community Structures in Large Networks," wi, pp.233-239, 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI'06), 2006
Usage of this product signifies your acceptance of the Terms of Use.