The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
SALSA: the stochastic approach for link-structure analysis
ACM Transactions on Information Systems (TOIS)
Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search
IEEE Transactions on Knowledge and Data Engineering
Sic transit gloria telae: towards an understanding of the web's decay
Proceedings of the 13th international conference on World Wide Web
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Link analysis ranking
Link analysis ranking: algorithms, theory, and experiments
ACM Transactions on Internet Technology (TOIT)
BackRank: an alternative for PageRank?
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Relevance and Impact of Tabbed Browsing Behavior on Web Usage Mining
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Combating web spam with trustrank
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Many random walks are faster than one
Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures
BrowseRank: letting web users vote for page importance
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Recursive Markov chains, stochastic grammars, and monotone systems of nonlinear equations
Journal of the ACM (JACM)
What's in a session: tracking individual behavior on the web
Proceedings of the 20th ACM conference on Hypertext and hypermedia
Beyond the usual suspects: context-aware revisitation support
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
Classification of user interest patterns using a virtual folksonomy
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
No search result left behind: branching behavior with browser tabs
Proceedings of the fifth ACM international conference on Web search and data mining
Online multitasking and user engagement
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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We present a model of tabbed browsing that represents a hybrid between a Markov process capturing the graph of hyperlinks, and a branching process capturing the birth and death of tabs. We present a mathematical criterion to characterize whether the process has a steady state independent of initial conditions, and we show how to characterize the limiting behavior in both cases. We perform a series of experiments to compare our tabbed browsing model with pagerank, and show that tabbed browsing is able to explain 15-25% of the deviation between actual measured browsing behavior and the behavior predicted by the simple pagerank model. We find this to be a surprising result, as the tabbed browsing model does not make use of any notion of site popularity, but simply captures deviations in user likelihood to open and close tabs from a particular node in the graph.