Knowledge and Information Systems

, Volume 10, Issue 4, pp 515–528

Mining user access patterns with traversal constraint for predicting web page requests

  • Mei-Ling Shyu
  • Choochart Haruechaiyasak
  • Shu-Ching Chen
Short Paper

DOI: 10.1007/s10115-006-0004-z

Cite this article as:
Shyu, ML., Haruechaiyasak, C. & Chen, SC. Knowl Inf Syst (2006) 10: 515. doi:10.1007/s10115-006-0004-z


The recent increase in HyperText Transfer Protocol (HTTP) traffic on the World Wide Web (WWW) has generated an enormous amount of log records on Web server databases. Applying Web mining techniques on these server log records can discover potentially useful patterns and reveal user access behaviors on the Web site. In this paper, we propose a new approach for mining user access patterns for predicting Web page requests, which consists of two steps. First, the Minimum Reaching Distance (MRD) algorithm is applied to find the distances between the Web pages. Second, the association rule mining technique is applied to form a set of predictive rules, and the MRD information is used to prune the results from the association rule mining process. Experimental results from a real Web data set show that our approach improved the performance over the existing Markov-model approach in precision, recall, and the reduction of user browsing time.


Web usage mining Association rule mining Mining user access patterns 

Copyright information

© Springer-Verlag London Limited 2006

Authors and Affiliations

  • Mei-Ling Shyu
    • 1
  • Choochart Haruechaiyasak
    • 2
  • Shu-Ching Chen
    • 3
  1. 1.Department of Electrical and Computer EngineeringUniversity of MiamiCoral GablesUSA
  2. 2.Information Research and Development Division (RDI)National Electronics and Computer Technology Center (NECTEC)PathumthaniThailand
  3. 3.Distributed Multimedia Information System LaboratorySchool of Computer Science, Florida International UniversityMiamiUSA

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