Extraction of Web Usage Profiles using Simulated Annealing Based Biclustering Approach

TL;DR

This paper introduces a novel simulated annealing based biclustering method to identify correlated user groups in web usage data, enhancing web personalization and customization.

Contribution

It presents a new optimization-based biclustering approach using simulated annealing for extracting user profiles from web usage data.

Findings

Successfully extracted highly correlated user groups

Improved web personalization capabilities

Effective on real web usage dataset

Abstract

In this paper, the Simulated Annealing (SA) based biclustering approach is proposed in which SA is used as an optimization tool for biclustering of web usage data to identify the optimal user profile from the given web usage data. Extracted biclusters are consists of correlated users whose usage behaviors are similar across the subset of web pages of a web site where as these users are uncorrelated for remaining pages of a web site. These results are very useful in web personalization so that it communicates better with its users and for making customized prediction. Also useful for providing customized web service too. Experiment was conducted on the real web usage dataset called CTI dataset. Results show that proposed SA based biclustering approach can extract highly correlated user groups from the preprocessed web usage data.