Movie Recommendation System using RNN and Cognitive thinking
Shubhada Labde, Vishesh Karan, Shubham Shah, Dhruv Krishnan · 2023
Systems such as Netflix, Amazon, Flipkart, etc. have a huge user base spanning the entire globe. The products and services that these giants provide are also commensurately overwhelming in amount. A particular user can’t be expected to browse through the entire repertoire on his/her own. This is where a recommendation system comes in handy. Such a system can suggest a user similar as well as completely different products and services without any explicit search being carried out by the user. A recommendation system helps increase user engagement and may ensure a loyal consumer base if deployed correctly. Incase of movies, demographic factors such as age and region play an important role in determining user preferences. Age of a person is a latent factor which influences his or her genre preferences. Hence, we have decided to explore the trends that come into play in determining a person’s genre preferences. The main aim is to build a recommendation system for an app in order to increase convenience as well as user interaction using an ensemble Recommendation System model which will utilize 4 different individual learners and combine their results accordingly to provide near perfect recommendations to any user.The movie recommendation system will incorporate cognitive thinking by considering the age of the user and recommending genres based on age group psychology.