Applying data mining technology to analyze user behavior in course website

Jiann-Yun Day, Chen Chieh Yeh, Chi Jun Lu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Information of network grows up fast, and there is an important thing providing user a tool which could search information quickly. In order to achieve this purpose and we must track and analyze user behavior of network. We apply data mining approach which is used to accurately capture user behavior of network traffic, and the proposed prediction model is constructed by log database. This research is used Petri-net method to grasp the user behavior accurately, and it offers path of user behavior. And we use converted weight matrix method to construct rule table and prediction model, and it has flexibility to make management and access of the database more convenient. The experimental results showed that improve site of website and predict path of user behavior efficiently.

Original languageEnglish
Title of host publicationProceedings of the 3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007
Pages495-499
Number of pages5
Publication statusPublished - 2007 Dec 1
Event3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007 - Phuket, Thailand
Duration: 2007 Apr 22007 Apr 4

Publication series

NameProceedings of the 3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007

Other

Other3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007
CountryThailand
CityPhuket
Period07/4/207/4/4

Keywords

  • Data mining
  • Prediction model
  • User behavior

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Science Applications

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  • Cite this

    Day, J-Y., Yeh, C. C., & Lu, C. J. (2007). Applying data mining technology to analyze user behavior in course website. In Proceedings of the 3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007 (pp. 495-499). (Proceedings of the 3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007).