Enhancing User Profile Accuracy for Personalized Web Systems

Abstract

Personalized Web Applications aim to improve the user's browsing experience by offering customized products and services based on his preferences and needs. A key feature of a successful personalization system is building profiles that accurately express the real interests and needs of each user. In this work, we focus on creating accurate, complete and dynamic profiles by capturing and tracking the users’ browsing activities. Moreover, we implement techniques to increase the accuracy of the retrieved user profiles by collecting more browsing data, identifying the most important concepts and removing irrelevant ones, and the number of levels from the concept hierarchy in the reference ontology that we should use to efficiently represent the users’ reel interests and needs. The result is a complete, dynamic, and accurate user profile that can be used to give users better-personalized browsing experience.