Randomized algorithms
WWW '99 Proceedings of the eighth international conference on World Wide Web
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
The stochastic approach for link-structure analysis (SALSA) and the TKC effect
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Using PageRank to Characterize Web Structure
COCOON '02 Proceedings of the 8th Annual International Conference on Computing and Combinatorics
Adaptive on-line page importance computation
WWW '03 Proceedings of the 12th international conference on World Wide Web
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
The effect of the back button in a random walk: application for pagerank
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Can link analysis tell us about web traffic?
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
The web as a graph: measurements, models, and methods
COCOON'99 Proceedings of the 5th annual international conference on Computing and combinatorics
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The World Wide Web with its billions of hyperlinked documents is a huge and important resource of information. There is a necessity of filtering this information. Link analysis of the Web graph turned out to be a powerful tool for automatically identifying authoritative documents. One of the best examples is the PageRank algorithm used in Google [1] to rank search results. In this paper we extend the model underlying the PageRank algorithm by incorporating "back button" usage modeling in order to make the model less simplistic. We explain the existence and uniqueness of the ranking induced by the extended model. We also develop and implement an efficient approximation method for computing the novel ranking and present succesful experimental results made on 80- and 50- million page samples of the real Web.