Mobile Content Personalisation Using Intelligent User Profile Approach

As there are several limitations using mobile internet, mobile content personalization seems to be an alternative to enhance the experience of using mobile internet. In this paper, we propose the mobile content personalization framework to facilitate collaboration between the client and the server. This paper investigates clustering and classification techniques using K-means and Artificial Neural Networks (ANN) to predict user´s desired content and WAP pages based on device´s listed-oriented menu approach. We make use of the user profile and user´s information ranking matrix to make prediction of the desired information for the user. Experimental results show that it can generate promising prediction. The results show that it works best when used for predicting 1 matched menu item on the screen.