Hybrid Framework Using Ant Colony Clustering and K-Means Genetic Algorithm (ANT-KGA) For Optimizations of Web Usage Pattern

Published in Journal

Anusandhan (RNTUJ-AN) [RNTUJ-AN] (Vol:17/ Issue: 26) DOI: [NA]
Authors: Seema C. P.* Pradeep Chouksey Gajendra K. Vaiker
Subjects: Technology & Management

Year: Sep, 2012
Volume: 17 / Issue: 26
Pages: 40-45
Publisher: RNTU
Source:
ISSN: 2278-4187
E-ISSN: 2457-0656
DOI: NA
Published URL:
Published On: Sep, 2012

Article Details

Hybrid Framework Using Ant Colony Clustering and K-Means Genetic Algorithm (ANT-KGA) For Optimizations of Web Usage Pattern | Original Article

Seema C. P.* Pradeep Chouksey Gajendra K. Vaiker in Anusandhan (RNTUJ-AN) | Multidisciplinary Academic Research

ABSTRACT:

The web usage Mining (WUM) is the process of discovering hidden patterns from the web usage. The proper analysis of web log file is beneficial to manage the websites effectively for administrative and users’ prospective. In this research paper, a hybrid framework is proposed Using Ant Colony Clustering and Linear Genetic Programming Approach (ANT-LGP) for optimizations of web usage pattern. The hybrid framework uses an ant colony optimization algorithm to cluster Web usage patterns. In this work, we investigate the performance aspect of proposed hybrid method with well famous K-means genetic algorithm (K-GA) based ant colony clustering method for web usage log pattern analysis. We present a comparative performance evaluation model of ANT-LGP versus ANT-KGA by means of an analytical approach. Quantitative measurements are performed using number clusters, error rate, number of iteration and execution time performance parameters in this research work. The results proposed framework offers a superior performance compared to existing L-GP based system.