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Conceptualizing Mining of Firm’s Web Log Files

Author

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  • Trakunphutthirak Ruangsak

    (Faculty of IT, Clayton Campus, Monash University, 25 Exhibition Walk, Clayton, Australia)

  • Cheung Yen

    (Faculty of IT, Clayton Campus, Monash University, 25 Exhibition Walk, Clayton, Australia)

  • Lee Vincent C. S.

    (Faculty of IT, Clayton Campus, Monash University, 25 Exhibition Walk, Clayton, Australia)

Abstract

In this era of a data-driven society, useful data (Big Data) is often unintentionally ignored due to lack of convenient tools and expensive software. For example, web log files can be used to identify explicit information of browsing patterns when users access web sites. Some hidden information, however, cannot be directly derived from the log files. We may need external resources to discover more knowledge from browsing patterns. The purpose of this study is to investigate the application of web usage mining based on web log files. The outcome of this study sets further directions of this investigation on what and how implicit information embedded in log files can be efficiently and effectively extracted. Further work involves combining the use of social media data to improve business decision quality.

Suggested Citation

  • Trakunphutthirak Ruangsak & Cheung Yen & Lee Vincent C. S., 2017. "Conceptualizing Mining of Firm’s Web Log Files," Journal of Systems Science and Information, De Gruyter, vol. 5(6), pages 489-510, December.
    • Handle: RePEc:bpj:jossai:v:5:y:2017:i:6:p:489-510:n:1
    DOI: 10.21078/JSSI-2017-489-22
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    References listed on IDEAS

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    1. Xiang-ying Li, 2013. "Data Preprocessing in Web Usage Mining," Springer Books, in: Ershi Qi & Jiang Shen & Runliang Dou (ed.), The 19th International Conference on Industrial Engineering and Engineering Management, edition 127, chapter 0, pages 257-266, Springer.
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