An Emotional and Context-Aware Model for Adapting RSS News to Users and Groups

Authors:
Eugénia Vinagre;Goreti Marreiros;Carlos Ramos;Lino Figueiredo
Affiliations:
Polytechnic of Porto, Institute of Engineering, Porto, Portugal;Polytechnic of Porto, Institute of Engineering, Porto, Portugal and Knowledge Engineering and Decision Support Group, GECAD, Porto, Portugal;Polytechnic of Porto, Institute of Engineering, Porto, Portugal and Knowledge Engineering and Decision Support Group, GECAD, Porto, Portugal;Polytechnic of Porto, Institute of Engineering, Porto, Portugal and Knowledge Engineering and Decision Support Group, GECAD, Porto, Portugal
Venue:
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
Year:
2009

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Abstract

The exhibition of information does not always attend to the preferences and characteristics of the users, nor the context that involves the user. With the aim of overcoming this gap, we propose an emotional context-aware model for adapting information contents to users and groups. The proposed model is based on OCC and Big Five models to handle emotion and personality respectively. The idea is to adapt the representation of the information in order to maximize the positive emotional valences and minimize the negatives. To evaluate the proposed model it was developed a prototype for adapting RSS news to users and group of users.