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Y. Liu, Z. M. Ma, C. Zhou: Y. Liu, Z. M. Ma, C. Zhou
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tarix | 08.08.2018 | ölçüsü | 3,17 Mb. | | #61560 |
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Y. Liu, Z. M. Ma, C. Zhou: Y. Liu, Z. M. Ma, C. Zhou: Web Markov Skeleton Processes and Their Applications, Tohoku Math J. 63 (2011), 665-695 Y. Liu, Z. M. Ma, C. Zhou: Further Study on Web Markov Skeleton Processes, in Stochastic Analysis and Applications to Finance,World Scientific,2012 C. Zhou: Some Results on Mirror Semi-Markov Processes, manuscript
From probabilistic point of view, PageRank is the stationary distribution of a Markov chain.
Using only static web graph structure Reflecting only the will of web managers, but ignore the will of users e.g. the staying time of users on a web.
Markov property
Stationary distribution: - Stationary distribution:
- is the mean of the staying time on page i.
- The more important a page is, the longer staying time on it is.
- is the mean of the first re-visit time at page i. The more important a page is, the smaller the re-visit time is, and the larger the visit frequency is.
Browse Rank the next PageRank says Microsoft
Browsing Processes will be a Basic Mathematical Tool in Beyond: --General fromework of Browsing Processes? --How about inhomogenous process? --Marked point process --Mobile Web: not really Markovian
[10] B. Gao, T. Liu, Z. M. Ma, T. Wang, and H. Li [10] B. Gao, T. Liu, Z. M. Ma, T. Wang, and H. Li A general markov framework for page importance computation, In proceedings of CIKM '2009, [11] B. Gao, T. Liu, Y. Liu, T. Wang, Z. M. Ma and H. LI Page Importance Computation based on Markov Processes, Information Retrieval online first:
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