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Website Structure Improvement Based on the Combination of Selected Web Structure and Web Usage Mining Methods

Author

Listed:
  • Jozef Kapusta

    (Constantine the Philosopher University in Nitra, Nitra, Slovakia)

  • Michal Munk

    (Constantine the Philosopher University in Nitra, Nitra, Slovakia)

  • Martin Drlik

    (Constantine the Philosopher University in Nitra, Nitra, Slovakia)

Abstract

The different web mining methods and techniques can help to solve some typical issues of the contemporary websites, contribute to more effective personalization, improve a website structure and reorganize its web pages. However, only several papers tried to combine web structure and web usage mining (WUM) methods with this aim. The paper researches if and how the combination of selected web structure and WUM methods can identify misplaced web pages and how they can contribute to improving the website structure. The paper analyzes the relationship between the estimated importance of the web page from the web page creator’s point of view using the web structure mining method based on PageRank and visitors’ real perception of the importance of that individual web page using the WUM method based on sequence patterns analysis, which eliminates the problem with repeated visits of the same web page during one session. The results prove that the expected probability of accesses to the individual web page correlates with the observed visit rate obtained from the log files using the WUM method. Furthermore, the website can be improved based on the consequent application of the residual analysis on the obtained results. The applicability of the proposed combination of the web structure and WUM methods is presented on two case studies from different application domains of the contemporary web. As a result, the web pages, which are underestimated or overestimated by the web page creators, are successfully identified in both cases.

Suggested Citation

  • Jozef Kapusta & Michal Munk & Martin Drlik, 2018. "Website Structure Improvement Based on the Combination of Selected Web Structure and Web Usage Mining Methods," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(06), pages 1743-1776, November.
    • Handle: RePEc:wsi:ijitdm:v:17:y:2018:i:06:n:s0219622018500402
    DOI: 10.1142/S0219622018500402
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    References listed on IDEAS

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    1. Yiqun Liu & Min Zhang & Rongwei Cen & Liyun Ru & Shaoping Ma, 2007. "Data cleansing for Web information retrieval using query independent features," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(12), pages 1884-1898, October.
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    5. David Gunnarsson Lorentzen, 2014. "Webometrics benefitting from web mining? An investigation of methods and applications of two research fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 409-445, May.
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    Cited by:

    1. Bahareh Rahmati & Mohammad Karim Sohrabi, 2019. "A Systematic Survey on High Utility Itemset Mining," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1113-1185, July.

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