Zusammenfassung
Any unassisted decision a user has to make can be difficult, even if it entails the simple task of selecting which movie to watch. The sheer volume of movies offered by streaming platforms makes this task all the more difficult and time consuming. Many platforms attempt to combat this problem through recommendation systems. These however seem more likely to be making wild suggestions than being a ...
Zusammenfassung
Any unassisted decision a user has to make can be difficult, even if it entails the simple task of selecting which movie to watch. The sheer volume of movies offered by streaming platforms makes this task all the more difficult and time consuming. Many platforms attempt to combat this problem through recommendation systems. These however seem more likely to be making wild suggestions than being a constructive aid to the selection process. In order to offer more accurate recommendations, we propose a system that is based on a user's current emotion, which is matched with the sentiments contained in the movies' spoken language. A study involving our newly designed mobile sentiment-based movie recommender named 'FROY' shows highly promising results. As it turns out, sentiment analysis of spoken language leads to appropriate recommendations.
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