Live It - Recommendation System based on Emotion Detection
Diana-Isabela Crainic, Adrian Iftene · 2021
This paper presents the development of a web application that integrates a system of movie recommendations using the collaborative filtering algorithm with a component of realtime recording and detection of emotions.So far, there were no implementations that combine recommendations and emotions, so this application proposes these two to work together to make our lives better regarding the moviewatching experience.To recognize emotions, we created a component that examines facial expressions, which offers, as a result, one of the emotion types: happy, sad, neutral, anger, surprise.This component was later integrated into a movie recommendation application, which analyzes the user's emotions in real-time while watching the presentation video.In the second part of the paper, we presented how we performed usability tests in order to improve the quality of the application.The results were promising, with a high degree of accuracy and usefulness coming from end-users, showing the future potential of this application, for instance adding new functionalities or recommendation algorithms.