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Effectively user pattern discover and classification from web log database


Article Information

Title: Effectively user pattern discover and classification from web log database

Authors: K. Abirami, P. Mayilvaganan

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2018

Volume: 13

Issue: 5

Language: English

Categories

Abstract

This paper is involve the three phases on web usage mining. The first phase focused on data preprocessing stage to remove irrelevant data from web log file. In the second phase involve cleaned log file. It is used for discovering usage patterns. Final phase, the discovered the user behaviors patterns it provide to the classification of users, who have frequently visitor, rare visitor, referred by the other web site, distinct user. The cluster analysis or clustering is the task of assigning a set of objects into groups so that the objects in the same cluster are more similar to each other than to those in other clusters. This information will help to website administrators for efficient administration and personalization of their websites. Accurate analysis of these patterns leads to understanding of users visiting the web site thereby improved user satisfaction. We have conducted vivid experiments and the results are shown in this paper.


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