Skip to main content

Improving Convergence Performance of PageRank Computation Based on Step-Length Calculation Approach

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Abstract

We address the task of improving convergence performance of PageRank computation. Based on a step-length calculation approach, we derive three methods, which respectively calculates its step-length so as to make the successive search directions orthogonal (orthogonal direction), minimize the error at the next iteration (minimum error) and make the successive search directions conjugate (conjugate direction). In our experiments using a real Web network, we show that the minimum error method is promising for this task.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Bishop, C.M.: Neural networks for pattern recognition. Clarendon Press, Oxford (1995)

    Google Scholar 

  2. Brin, S., Page, L.: The anatomy of a large scale hypertextual Web search engine. In: Proceedings of the Seventh International World Wide Web Conference, pp. 107–117 (1998)

    Google Scholar 

  3. Gleich, D., Zhukov, L., Berkhin, P.: Fast parallel PageRank: a linear system approach. In: Proceedings of the 14th International World Wide Web Conference (2004)

    Google Scholar 

  4. Golub, G.H., Van Loan, C.F.: Matrix Computations. Johns Hopkins University Press, Baltimore (1989)

    MATH  Google Scholar 

  5. Kleinberg, J.: Authoritative sources in a hyperlinked environment. In: Proceedings of the Ninth ACM-SIAM Symposium on Discrete Algorithms, pp. 668–677 (1998)

    Google Scholar 

  6. Langville, A.N., Meyer, C.D.: Deeper inside PageRank. Internet Mathematics 1(3), 335–380 (2005)

    Article  MathSciNet  Google Scholar 

  7. Luenberger, D.G.: Linear and nonlinear programming. Addison-Wesley, Reading (1984)

    MATH  Google Scholar 

  8. Newman, M.E.J.: The structure and function of complex network. SIAM Review 45(2), 167–256 (2003)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Saito, K., Nakano, R. (2006). Improving Convergence Performance of PageRank Computation Based on Step-Length Calculation Approach. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004_121

Download citation

  • DOI: https://doi.org/10.1007/11893004_121

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46537-9

  • Online ISBN: 978-3-540-46539-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics