Browsing Pattern Analysis: What user browsing Patterns Indicate

Abstract

With the advent of the Internet of Things (IoT) the number of users and the number of websites in the World Wide Web increase exponentially by the day. Consequently, the users have issues searching required content in the plethora of available websites. Optimisation, speed, and convenience of browsing through data have never been more important. This is where the role of user preference mapping through the process of browsing pattern analysis comes in. The process of user browsing pattern analysis using the experimental setup of a self-constructed tool LAZY has been done to show a sample of browsing pattern analysis and the effects it might have on today's applications. Why is it needed? The tool analyses the browser data of the user and places the user into certain demographic which is greatly beneficial to the user who now receives suggestions for relevant content. It is also beneficial to the content developers who can now receive data about user preferences which could further boost the navigability of the website and thereby the profitability of the website.

Machine Learning and AI Application Behaviour Prediction for User Experience Modelling and Optimization

“…A Bayesian inference approach is used to estimate the posterior distribution of the important parameters rather than a probabilistic estimator or an expectation-maximization procedure. Sagar, Srivastava and Arora [18], drawing on UBM's assumptions about user behavior, suggested a Bayesian Browsing Model (BBM). In order to evaluate the model's usefulness and efficiency, series of experiments were conducted.…”