Recommender System for Mobile Applications
Rajiv Kumar, Shivani Joshi, Chitvan Gupta, Raghav Aggarwal · 2023
Recommender Systems have turn out to be a critical part of any e-commerce internet site. It can used for any product primarily based on web sites or movie streaming websites. This paper is centered towards the recommender systems that can be used for recommending movies. The recommendation systems are not uncommon for movies but they lack a certain opinion poll of the people about the recommended movie. The system makes use of the popularity opinion of the people which can be drawn from the sentiment analysis of popular micro blogging website such as twitter. The content based filtering method of machine learning is used to find recommendation. Cosine similarities score is used for the movie recommendation system. Further the sentiment analysis of the recommended movies gives validity whether they are actually recommendable or not. The proposed system will develop an android application for recommendation system. This android application is named Ticket.