Skip to main content

A New Algorithm to Discover Page-Action Rules on Web

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3683))

  • 1318 Accesses

Abstract

In the past, a number of researches have been devoted to web mining. However, only page browsing behaviors have been studied. The actions performed in the pages were omitted. To the best of our knowledge, no previous researches were able to find out page-action browsing sequences. This paper proposes an algorithm, called WebPAN, to analyze customers’ browsing pages and their action paths. The algorithm’s efficiency was examined in our prototype. This study would help website managers to restructure their website layouts or advertisement positions more correctly in electronic commerce.

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. Agrawal, R., Srikant, R.: Fast Algorithms for Mining Association Rules. In: Proc. of the 20th Int’l Conference on Very Large Databases (1994)

    Google Scholar 

  2. Chen, S.-S., Hsu, P.-Y., Chen, Y.-L.: Mining Web Traversal Rules with Sequences. MIS Review 9, 53–71 (1999)

    MathSciNet  Google Scholar 

  3. Chen, M.-S., Park, J.-S., Yu, P.S.: Efficient Data Mining for Path Traversal Patterns. IEEE Trans. on Knowledge and Data Engineering 10(2), 209–221 (1998)

    Article  Google Scholar 

  4. Cooley, R., Mobasher, B., Srivastava, J.: Web Mining: Information and Pattern Discovery on the World Wide Web. In: Proceedings of the 9th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 1997 (1997)

    Google Scholar 

  5. Cooley, R., Mobasher, B., Srivastava, J.: Grouping Web Page References into Transactions for Mining World Wide Web Browsing Patterns. In: Proceedings of the 1997 IEEE Knowledge and Data Engineering Exchange Workshop, KDEX 1997 (1997)

    Google Scholar 

  6. Hsieh, C.C., Chang, C.T.: An Enhanced Transaction Identification Module on Web Usage Mining. Asia Pacific Management, 241–252 (2001)

    Google Scholar 

  7. Srikant, R., Agrawal, R.: Mining Sequential Patterns: Generalizations and Performance Improvements. In: Proc. of the Fifth Int’l Conference on Extending Database Technology, EDBT (1996)

    Google Scholar 

  8. Yun, C.H., Chen, M.S.: Using Pattern-join and Purchase-Combination for Mining Transaction Patterns in an Electronic Commerce Environment. In: The 24th Annual International Conference On Computer Software and Applications, pp. 99–104 (2000)

    Google Scholar 

  9. Zhang, W., Xu, B., Song, W., Yung, H., Liu, K.: Data Mining Algorithms for Web Prefetching. In: Proceeding of the First International Conference On Web Information Systems Engineering, vol. 2, pp. 34–38 (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Yang, HL., Lin, QF. (2005). A New Algorithm to Discover Page-Action Rules on Web. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553939_185

Download citation

  • DOI: https://doi.org/10.1007/11553939_185

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28896-1

  • Online ISBN: 978-3-540-31990-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics