Paper Info
Title
An approach to relate the Web communities through bipartite graphs
Abstract
The Web harbors a large number of community structures. Early detection of community structures has many purposes such as reliable searching and selective advertising. In this paper we investigate the problem of extracting and relating the web community structures from a large collection of Web-pages by performing hyper-link analysis. The proposed algorithm extracts the potential community signatures by extracting the corresponding dense bipartite graph (DBG) structures from the given data set of web pages. Further, the proposed algorithm can also be used to relate the extracted community signatures. We report the experimental results conducted on 10 GB TREC (Text REtrieval Conference) data collection that contains 1.7 million pages and 21.5 million links. The results demonstrate that the proposed approach extracts meaningful community signatures and relates them.
Year
DOI
Venue
2001
10.1109/WISE.2001.996491
WISE
Keywords
Field
DocType
indexing terms,data mining,internet,graph theory,link analysis,data collection,community structure,web pages,relation,web mining,bipartite graph
Data mining,Web mining,Web page,Link analysis,Computer science,Text Retrieval Conference,The Internet,Graph theory,Data collection,World Wide Web,Information retrieval,Bipartite graph,Database
Conference
Volume
ISBN
Citations 
1
0-7695-1393-X
23
PageRank 
References 
Authors
2.02
16
2
Name
Order
Citations
PageRank
Reddy, P.K.1232.02
Masaru Kitsuregawa23188831.46