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Comparison of Two Algorithms for Computing Page Importance

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6124))

Abstract

In this paper we discuss the relation and the difference between two algorithms BrowseRank and PageRank. We analyze their stationary distributions by the ergodic theory of Markov processes. We compare in detail the link graph used in PageRank and the user browsing graph used in BrowseRank. Along with the comparison, the importance of the metadata contained in the user browsing graph is explored.

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References

  1. Brin, S., Page, L.: The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems 30(1-7), 107–117 (1998)

    Article  Google Scholar 

  2. Deng, Y., Liang, Z.: Stochastic Point Processes and Their Applications. Science Press, Beijing (1998) (in Chinese)

    Google Scholar 

  3. Golub, G.H., Loan, C.F.V.: Matrix computations, 3rd edn. Johns Hopkins University Press, Baltimore (1996)

    MATH  Google Scholar 

  4. Gyöngyi, Z., Garcia-Molina, H.: Web spam taxonomy. Technical Report TR 2004-25, Stanford University (2004)

    Google Scholar 

  5. Gyöngyi, Z., Garcia-Molina, H., Pedersen, J.: Combating web spam with trustrank. In: VLDB 2004: Proceedings of the Thirtieth International Conference on Very Large Data Bases, pp. 576–587, VLDB Endowment (2004)

    Google Scholar 

  6. Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. In: SODA 1998, Philadelphia, PA, USA, pp. 668–677 (1998)

    Google Scholar 

  7. Langville, A.N., Meyer, C.D.: Deeper inside pagerank. Internet Mathematics 1(3), 335–400 (2004)

    MATH  MathSciNet  Google Scholar 

  8. Liu, Y., Gao, B., Liu, T.-Y., Zhang, Y., Ma, Z., He, S., Li, H.: BrowseRank: letting web users vote for page importance. In: SIGIR 2008: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 451–458. ACM, New York (2008)

    Chapter  Google Scholar 

  9. Liu, Y., Liu, T.-Y., Gao, B., Ma, Z., Li, H.: A framework to compute page importance based on user behaviors. Information Retrieval 13(1), 22–45 (2010)

    Article  Google Scholar 

  10. Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: Bringing order to the web. Technical Report 1999-66, Stanford InfoLab, Previous number = SIDL-WP-1999-0120 (November 1999)

    Google Scholar 

  11. Qian, M.P., Gong, G.L.: Stochastic Process. Second version. Peking University Press (1997) (in Chinese)

    Google Scholar 

  12. Stewart, W.J.: Introduction to the Numerical Solution of Markov Chains. Princeton University Press, Princeton (1994)

    MATH  Google Scholar 

  13. Stroock, D.W.: An Introduction to Markov Processes, Graduate Texts in Mathematics. Springer, Heidelberg (2005)

    Google Scholar 

  14. Wang, Z.K., Yang, X.Q.: Birth and Death Processes and Markov Chains. Springer, New York (1992)

    MATH  Google Scholar 

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Liu, Y., Ma, ZM. (2010). Comparison of Two Algorithms for Computing Page Importance. In: Chen, B. (eds) Algorithmic Aspects in Information and Management. AAIM 2010. Lecture Notes in Computer Science, vol 6124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14355-7_1

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  • DOI: https://doi.org/10.1007/978-3-642-14355-7_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14354-0

  • Online ISBN: 978-3-642-14355-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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