Personal_Movie - A Geolocated Movie Recommendation System For Events

Abstract

Considering how hard it is to provide more assertive and personalized information, products and service for people/tourists who are searching for a service, such as: having lunch/dinner, searching what's hot about films in theaters right now in the "Olympic villa", for instance. In order to fill this gap this paper describes a Recommendation System (RS) that applies contextual information and people' personality as recommender inputs in order to predict more personalized films for Cinemark's clients (Personal_Movie). In order to illustrate our discussion we present an experiment that uses a software for mobile that uses geo-location and people's personality to further improve the quality of the film recommendation. The experiment has shown promising results and its potential in the generation of more assertive recommendation. We believe the results might by asl applicable for other products and services requested in Brazilian mega events

Keywords

• Recommender Systems
• Personality
• contextual information
• Megaevents