SODA

Towards Implicit User Modeling Based on Artificial Intelligence, Cognitive Styles and Web Interaction Data

Papatheocharous, Efi and Belk, Marios and Germanakos, Panagiotis and Samaras, George (2014) Towards Implicit User Modeling Based on Artificial Intelligence, Cognitive Styles and Web Interaction Data. International Journal on Artificial Intelligence Tools, 23 (2).

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Official URL: http://www.worldscientific.com/doi/abs/10.1142/S02...

Abstract

A key challenge of adaptive interactive systems is to provide a positive user experience by extracting implicitly the users' unique characteristics through their interactions with the system, and dynamically adapting and personalizing the system's content presentation and functionality. Among the different dimensions of individual differences that could be considered, this work utilizes the cognitive styles of users as determinant factors for personalization. The overarching goal of this paper is to increase our understanding about the effect of cognitive styles of users on their navigation behavior and content representation preference. We propose a Web-based tool, utilizing Artificial Intelligence techniques, to implicitly capture and find any possible relations between the cognitive styles of users and their characteristics in navigation behavior and content representation preference by using their Web interaction data. The proposed tool has been evaluated with a user study revealing that cognitive styles of users have an effect on their navigation behavior and content representation preference. Research works like the reported one are useful for improving implicit and intelligent user modeling in engineering adaptive interactive systems.

Item Type:Article
ID Code:5653
Deposited By:Efi Papatheocharous
Deposited On:17 Apr 2014 09:33
Last Modified:02 Jan 2018 12:18

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