Random walks with “back buttons” (extended abstract)
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
BackRank: an alternative for PageRank?
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Beyond PageRank: machine learning for static ranking
Proceedings of the 15th international conference on World Wide Web
A probabilistic relevance propagation model for hypertext retrieval
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Fundamenta Informaticae
Agents, bookmarks and clicks: a topical model of web navigation
Proceedings of the 21st ACM conference on Hypertext and hypermedia
Dynamic pagerank using evolving teleportation
WAW'12 Proceedings of the 9th international conference on Algorithms and Models for the Web Graph
Fundamenta Informaticae
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Theoretical analysis of the Web graph is often used to improve the efficiency of search engines. The PageRank algorithm, proposed by Brin and Page, is used by the Google search engine to improve the results of the queries. The purpose of this article is to describe an enhanced version of the PageRank algorithm using a realistic model forthe back button. We introduce a limited history stack model (you cannot click more than m times in a row), and showthat when m=1, the computation of this Back PageRank can be as fast as that of a standard PageRank.