Modeling users on the World Wide Web based on cognitive factors, navigation behavior and clustering techniques

• Investigate the effect of users’ cognitive styles on Web navigation behavior.
• Modeling cognitive styles of users based on measures obtained from psychometric tests and Web navigation behavior.
• Propose navigation metrics for tracking the Web navigation behavior of users.
• Clustering of users revealed promising results since users were grouped consistently based on their navigation behavior.
• Clustering can be used as an alternative method for grouping users with particular cognitive style.

This paper focuses on modeling users’ cognitive styles based on a set of Web usage mining techniques on user navigation patterns and clickstream data. Main aim is to investigate whether specific clustering techniques can group users of particular cognitive style using measures obtained from psychometric tests and content navigation behavior. Three navigation metrics are proposed and utilized to find identifiable groups of users that have similar navigation patterns in relation to their cognitive style. The proposed work has been evaluated with two user studies which entail a psychometric-based survey for extracting the users’ cognitive styles, combined with a real usage scenario of users navigating in a controlled Web 2.0 environment. A total of 106 participants of age between 17 and 25 participated in the study providing interesting insights with respect to cognitive styles and navigation behavior of users. Studies like the reported one can be useful for modeling users and assist adaptive Web 2.0 environments to organize and present information and functionalities in an adaptive format to diverse user groups.