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Evaluation And Assessment Of Recommenders Using Monte Carlo Simulation, Renato Costa, Luiz Fernando Capretz
Evaluation And Assessment Of Recommenders Using Monte Carlo Simulation, Renato Costa, Luiz Fernando Capretz
Luiz Fernando Capretz
There have been various definitions, representations and derivations of trust in the context of recommender systems. This article presents a recommender predictive model based on collaborative filtering techniques that incorporate a fuzzy-driven quantifier, which includes two upmost relevant social phenomena parameters to address the vagueness inherent in the assessment of trust in social networks relationships. An experimental evaluation procedure utilizing a case study is conducted to analyze the overall predictive accuracy. These results show that the proposed methodology improves the performance of classical recommender approaches. Possible extensions are then outlined.