Certain Investigation on Automatic Recommendation for Online Users Using Web Usage Mining

Authors(2) :-P. Damodharan, Dr. C. S. Ravichandran

A real world-challenging task of the web master of an organization is to match the needs of user and keep their attention in their web site. So, only option is to capture the intuition of the user and provide them with the recommendation list. Most specifically, an online navigation behavior grows with each passing day, thus extracting information intelligently from it is a difficult issue. Web master should use web usage mining method to capture intuition. A WUM is designed to operate on web server logs which contain user’s navigation. Hence, recommendation system using WUM can be used to forecast the navigation pattern of user and recommend those to user in a form of recommendation list. In this paper, propose a two tier architecture for capturing users intuition in the form of recommendation list containing pages visited by user and pages visited by other user’s having similar usage profile. The practical implementation of proposed architecture and algorithm shows that accuracy of user intuition capturing is improved.

Authors and Affiliations

P. Damodharan
Department of Computer Science and Engineering, Akshaya College of Engineering and Technology, Coimbatore, Tamil Nadu, India
Dr. C. S. Ravichandran
Department of Electrical and Electronics Engineering, Sri Ramakrishna Engineering College, Coimbatore, Tamil Nadu, India

Data Mining, Web Usage mining, Web Intelligence, Personalization, Clustering, Classification

Publication Details

Published in : Volume 1 | Issue 1 | July-August 2016
Date of Publication : 2016-07-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 72-77
Manuscript Number : CSEIT1726175
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

P. Damodharan, Dr. C. S. Ravichandran, "Certain Investigation on Automatic Recommendation for Online Users Using Web Usage Mining", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 1, Issue 1, pp.72-77, July-August-2016.
Journal URL : http://ijsrcseit.com/CSEIT1726175

Article Preview

Follow Us

Contact Us