Embracing cognitive factors and Fuzzy Logic in adaptive interactive systems

Abstract

The increased demand of services on the Web to satisfy the diverse characteristics of users have resulted in a plethora of applications that aim to provide personalized services based on the heterogeneous needs and preferences of users. With the aim to enhance and support the personalization process of Web applications, an innovative adaptation framework is proposed embracing cognitive factors of users which serve as the user model, and Computational Intelligence techniques that decide on the adaptation effects of Web applications for providing a personalized user experience. The user model is based on a series of psychometric measures which capture particular cognitive factors of users, and the adaptation mechanism includes the utilization of Artificial Neural Networks and Fuzzy Logic for exploiting the benefits of intelligent classification and partial truth in the adaptation process. The proposed method has been evaluated with a user study that has revealed a main effect of cognitive factors of users on the adaptation of Web content and functionality since users were more efficient and effective in completing tasks in the adapted than the non-adapted version of the same environment.