Extracting Users’Navigational Behavior from Web Log Data: a Survey

Maryam Jafari¹, Farzad SoleymaniSabzchi^1, and Shahram Jamali²

¹Sama Technical and Vocational College, Islamic Azad University, Ardabil Branch, Ardabil, Iran

²Computer Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran

Cite this paper:
Maryam Jafari, Farzad SoleymaniSabzchi and Shahram Jamali. Extracting Users’Navigational Behavior from Web Log Data: a Survey. Journal of Computer Sciences and Applications. 2013; 1(3):39-45. doi: 10.12691/jcsa-1-3-3

Abstract

Web Usage Mining (WUM) is a kind of data mining method that can be used to discover user access patterns from Web log data. A lot of research has been done already about this area and the obtained results are used in different applications such as recommending the Web usage patterns, personalization, system improvement and business intelligence. WUM includes three phases that are called preprocessing, pattern discovery and pattern analysis. There are different techniques for WUM that have their own advantages and disadvantages. This paper presents a survey on some of the existing WUM techniques and it is shown that how WUM can be applied to Web server logs.

Keywords:
web usage mining web log mining pattern discovery preprocessing sequence mining

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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