Silk from a sow's ear: extracting usable structures from the Web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Improved algorithms for topic distillation in a hyperlinked environment
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Finding related pages in the World Wide Web
WWW '99 Proceedings of the eighth international conference on World Wide Web
Trawling the Web for emerging cyber-communities
WWW '99 Proceedings of the eighth international conference on World Wide Web
Small worlds: the dynamics of networks between order and randomness
Small worlds: the dynamics of networks between order and randomness
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
An efficient algorithm to rank Web resources
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
What is this page known for? Computing Web page reputations
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Approximating Aggregate Queries about Web Pages via Random Walks
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
The Small-World Phenomenon: An Algorithmic Perspective
The Small-World Phenomenon: An Algorithmic Perspective
Graph Theory with Applications to Engineering and Computer Science (Prentice Hall Series in Automatic Computation)
The web as a graph: measurements, models, and methods
COCOON'99 Proceedings of the 5th annual international conference on Computing and combinatorics
A Random Walk through Human Associations
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
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The World Wide Web is growing rapidly and revolutionizing the means of information access. It can be modeled as a directed graph in which a node represents a Web page and an edge represents a hyperlink. Currently the number of nodes in this gigantic Web graph is over four billion and is growing by more than seven million nodes a day--without any centralized control. The study of this graph is essential for designing efficient algorithms for crawling, searching, and ranking Web resources. Knowledge of the structure of the Web graph can be also exploited for attaining efficiency and comprehensiveness in Web navigation. This paper describes algorithms for graph-theoretic analysis of the Web.