In this paper we are trying to focus on, how user’s different activities on web can be stored and how these information can be used for retrieving some important patterns. Most of the commercial websites which are totally dependent on their website for the business for example matrimonial sites, online shopping websites etc. can store each and every click streams of their visitors in the server log. Later these data can be utilized for the discovery of Association patterns using the concept of Web Usage Mining (WUM) and Association Rule Mining for knowing their frequent browsing behavior, we can use this knowledge for various applications, like website modification (so that is can better fit the user’s requirement) and page pre-caching of frequent associated pages (so that load balancing on server can be provided).This paper aims to give an overview about the discovery of frequent patterns from web log data coming from HTTP server using the concept of Web Usage Mining (WUM).
This paper focuses all the stages of data mining i.e. 1. Data Pre-processing 2. Pattern Discovery and 3. Pattern Analysis.
Cite this article:
Preeti Sharma, Sanjay Kumar. WUM for the Discovery of User’s Frequent Navigation Patterns. Research J. Engineering and Tech. 2(2): April-June 2011 page 54-58
Preeti Sharma, Sanjay Kumar. WUM for the Discovery of User’s Frequent Navigation Patterns. Research J. Engineering and Tech. 2(2): April-June 2011 page 54-58 Available on: https://ijersonline.org/AbstractView.aspx?PID=2011-2-2-1