Evaluation of Visualization of a Fuzzy-Based Recommender System for Political Community-Building

Recommender systems are mainly used to reduce information overload and to provide recommendations of products likely to interest a user when given some information about his profile and preferences. The use of recommender systems on eGovernment is a research topic that is intended to improve the interaction among public administrations, citizens, and the private sector through reducing information overload on eGovernment services. In this work, the evaluation of visualization provided by a fuzzy-based recommender system for stimulating political participation and collaboration is proposed, using different evaluation methods for dimensionality reduction and fuzzy clustering algorithms that are the core of the recommender system approach. The results and recommendations given in this work are used for the implementation of the SmartParticipation project for the creation of political/thematic groups, which assumes that profiles of citizens and candidates cannot be considered unique items, but, rather are dynamic.