CHATBOT MOVIE RECOMMENDER SYSTEM

CHATBOT MOVIE RECOMMENDER SYSTEM

Akarshita Singh1, Adarsh Tripathi2, Ashutosh Mishra3

1BTECH(pursuing), Department of Computer Science Institute of Technology and Management(ITM), Gida, Gorakhpur, U.P, 273001, India

2BTECH(pursuing), Department of Computer Science Institute of Technology and Management(ITM), Gida, Gorakhpur, U.P, 273001, India

3BTECH(pursuing), Department of Computer Science Institute of Technology and Management(ITM), Gida, Gorakhpur, U.P, 273001, India

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Abstract – This paper deals with the recommender engine and chatbot through python using machine learning, artificial intelligence, to assist movie buffs by recommending what film to watch without requiring them to go through the timeconsuming and complex process of selecting from a vast number of films ranging from thousands to millions. Our goal in this post is to decrease human effort by recommending movies based on the user's preferences. To address these issues, we developed a paradigm that combines both a content-based and a collaborative approach. When compared to other systems that use a content-based approach, it will provide more explicit results. People are limited by content-based recommendation systems; these algorithms do not prescribe things out of the box, restricting your ability to learn more. As a result, when used in a chatbot, it produces reliable results.

Key Words:  Machine Learning, Collaborative filtering, similarity, user, Content Based, recommender system.