Abstract

The information overload resulting from the growth of the Internet increases the need for efficient mechanisms to identify and manage information relevant for users and groups of users within web-based interactive applications. As users can be grouped according to shared interests, characteristics and interactions, groups form convenient structures to support the required personalization.Previous work on the subject of implicit groups, carried out in areas such as computer networks and social media, suggests its usefulness in the development of web-based applications, specially in the way content is shared and user personalization is achieved. In this paper we investigate the dynamic identification of such groups based on the generation of extended user profiles and the application of content-analysis features, provided by an external framework. Our approach extends common explicit user profiles with implicit extracted data reflecting each user interests and interactions with other users and with the system. In order to draw conclusions about the use of implicit groups as building blocks for web applications, we present a tool that allows an easy integration of the concept in web applications. Finally we specify an application scenario and discuss the tool integration into the Moodle platform.

Full Text
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