Anime Recommendation System

Abstract

Anime is popular nowadays, particularly among the younger generation. The project is an anime recommendation system. Recently everyone has been at home due to the corona virus but if you’re like me and really enjoy anime, finding a new one to watch is a job on its own. Finding a new anime in and of itself is not hard, but just randomly picking and watching an anime which can range from 7–1000 episodes can lead to some bad results. So we built a recommendation system using the data mining algorithms to try and find anime that will be enjoyable based on the user ratings of different anime as well as the sentiment, genre and vector scores of their reviews. Each user may rate anime and add it to their finished list. Thereafter, machine learning techniques have been applied to obtain top 10 matching recommendations and predicted ratings.