Paper Info
Title
Who Links to Whom: Mining Linkage between Web Sites
Abstract
Previous studies of the web graph structure have focused on the graph structure at the level of individual pages. In actuality the web is a hierarchically nested graph, with domains, hosts and web sites introducing intermediate levels of affiliation and administrativecontrol. To better understand the growth of the web we need to understand its macro-structure, in terms of the linkage between web sites. In this paper e approximate this by studying the graph of the linkage between hosts on the web. This as done based on snapshots of the web taken by Google in Oct 1999,Aug 2000 and Jun 2001.The connectivity between hosts is represented by a directed graph, with hosts as nodes and weighted edges representingthe count of hyperlinks between pages on the corresponding hosts. We demonstrate how such a "hostgraph" an be used to study connectivity properties of hosts and domains over time, anddiscuss a modified "copy model" too explain observed link eight distributions as a function of subgraph size. We discuss changes in the web over time in the size and connectivity of web sites and country domains. We also describe a data mining application of the hostgraph: a related host finding algorithm which achieves a precision of 0.65 at rank 3.
Year
DOI
Venue
2001
10.1109/ICDM.2001.989500
ICDM
Keywords
Field
DocType
hierarchically nested graph,web sites,graph structure,corresponding host,web graph structure,web site,copy model,country domain,subgraph size,connectivity property,mining linkage,data mining application,data mining,web pages,bibliometrics,country domains,directed graphs,citation analysis,couplings,navigation,weight distribution,directed graph,computer science,hyperlinks
Data mining,Graph,Web page,Hypermedia,Computer science,Citation analysis,Directed graph,Artificial intelligence,Hyperlink,Snapshot (computer storage),Machine learning,Country code top-level domain
Conference
ISBN
Citations 
PageRank 
0-7695-1119-8
94
13.22
References 
Authors
14
4
Name
Order
Citations
PageRank
Krishna A. Bharat11211252.86
Bay-Wei Chang252473.00
Monika Rauch Henzinger34307481.86
Matthias Ruhl460848.78