Keyword Search:

A web usage mining approach based on LCS algorithm in online predicting recommendation systems

Jalali, Mehrdad and Mustapha, Norwati and Sulaiman, Md. Nasir and Mamat, Ali (2008) A web usage mining approach based on LCS algorithm in online predicting recommendation systems. Information Visualisation . 302 -307. ISSN 1550-6037

Full text not available from this repository.

Abstract

The Internet is one of the fastest growing areas of intelligence gathering. During their navigation Web users leave many records of their activity. This huge amount of data can be a useful source of knowledge. Advanced mining processes are needed for this knowledge to be extracted, understood and used. Web Usage Mining (WUM) systems are specifically designed to carry out this task by analyzing the data representing usage data about a particular Web site. WUM can model user behavior and, therefore, to forecast their future movements. Online prediction is one Web Usage Mining application. However, the accuracy of the prediction and classification in the current architecture of predicting users' future requests systems can not still satisfy users especially in huge Web sites. To provide online prediction efficiently, we advance an architecture for online predicting in Web Usage Mining system and propose a novel approach based on LCS algorithm for classifying user navigation patterns for predicting users' future requests. The Excremental results show that the approach can improve accuracy of classification in the architecture.

Item Type:Article
Subject:Web usage mining
Subject:LCS (Information retrieval system)
Subject:Data mining
Faculty or Institute:Faculty of Computer Science and Information Technology
Publisher:IEEE
DOI Number:10.1109/IV.2008.40
Altmetrics:http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/IV.2008.40
ID Code:19054
Deposited By: Erni Suraya Abdul Aziz
Deposited On:29 Aug 2012 11:09
Last Modified:30 Oct 2014 03:39

Repository Staff Only: Edit item detail

Document Download Statistics

This item has been downloaded for since 29 Aug 2012 11:09.

View statistics for "A web usage mining approach based on LCS algorithm in online predicting recommendation systems"

 
 
 
 

Universiti Putra Malaysia Institutional Repository is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.
Universiti Putra Malaysia Institutional Repository supports OAI 2.0 with a base URL of http://psasir.upm.edu.my/cgi/oai2
Best viewed using IE version 7.0 (and above) Mozilla Firefox version 3 (and above) with the resolution of 1024 x 768.