Movie Recommendation System based on user’s search history using incremental clustering
Kondepudi Yasaswi, Neelisetty Sri Lakshmi Sai Charitha, Ch. Vyshnavi, Safia Begum M, Jonnalagadda Surya Kiran · 2022
In today’s world as the technology is advancing there has been a drastic increase in the number of websites, huge amounts of data have been generated and endless options emerged to choose from when it comes to movies. When there are several options available, one might be generally confused in making their choices. To avoid that, recommender systems are the ones that plays a major part in making recommendations of the movies to the users, by using some algorithms and techniques. These recommender systems are used for various purposes like, in recommending music, movies, products, research papers, youtube, temporal recommendation and so on. A recommender System gives suggestions based majorly on the user’s changing interest over time or the user searching patterns using some algorithms like Clustering, and suggests the movies based on the generated interests of the user in the course oftime