Trawling the Web for emerging cyber-communities
WWW '99 Proceedings of the eighth international conference on World Wide Web
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Efficient identification of Web communities
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Who Links to Whom: Mining Linkage between Web Sites
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Extraction and classification of dense communities in the web
Proceedings of the 16th international conference on World Wide Web
Statistical properties of community structure in large social and information networks
Proceedings of the 17th international conference on World Wide Web
Web Structure Mining by Isolated Stars
Algorithms and Models for the Web-Graph
Web Structure Mining by Isolated Cliques
IEICE - Transactions on Information and Systems
Dynamic Graph Clustering Using Minimum-Cut Trees
WADS '09 Proceedings of the 11th International Symposium on Algorithms and Data Structures
The web as a graph: measurements, models, and methods
COCOON'99 Proceedings of the 5th annual international conference on Computing and combinatorics
Linear-time enumeration of isolated cliques
ESA'05 Proceedings of the 13th annual European conference on Algorithms
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The link structure of the Web is generally viewed as the webgraph. One of the main objectives of web structure mining is to find hidden communities on the Web based on the webgraph, and one of its approaches tries to enumerate substructures each of which corresponds to a set of web pages of a community or its core. Through those research, it has been turned out that certain substructures can find sets of pages that are inherently irrelevant to communities. In this paper, we propose a model, which we call contracted webgraphs, where such substructures are contracted into single nodes to hide useless information. We then try structure mining iteratively on those contracted webgraphs since we can expect to find further hidden information once irrelevant information is eliminated. We also explore structural properties of contracted webgraphs from the viewpoint of scale-freeness, and we observe that they exhibit novel and extreme self-similarities.