Abstract
The proposed work is to analyse the user’s behaviour in web access. Worldwide, the web users are browsing through different websites every second. Aim of this paper is to identify the behaviour of user's in a time bound using an Expectation Maximization (EM) algorithm and the maximum likelihood estimates of the model parameters. A novel approach based on Mixture normal distribution is used to discuss the percentage of user along with web page frequency.
Highlights
The number of accessible web pages grows significantly; it is becoming increasingly difficult for users to find documents that are relevant to their particular needs
A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data or hidden data is presented at various levels of generality [2], [3], [4] and [5]
In this paper we have studied the web user’s behaviour using Expectation Maximization (EM) algorithm
Summary
Department of Mathematics Hindustan Institute of Technology & Science, Chennai, India Research Scholar, Bharathiyar University G B Pant Govt. Engineering College, New Delhi, India Department of Mathematics and Statistics, Faculty of Applied Science and Technology Abstract—The proposed work is to analyse the user’s behaviour in web access. Worldwide, the web users are browsing through different websites every second. Aim of this paper is to identify the behaviour of user's in a time bound using an Expectation Maximization (EM) algorithm and the maximum likelihood estimates of the model parameters. A novel approach based on Mixture normal distribution is used to discuss the percentage of user along with web page frequency. Keywords—EM algorithm; maximum likelihood; mixture normal distribution; web page frequency
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