Computational Intelligence
N. Pradeep; K. K. Rao Mangalore; B. Rajpal; N. Prasad; R. Shastri
Abstract
Recommendation based systems can be used for recommending different web page, books, restaurants, tv shows, movies etc. The aim of movie recommendation system is to recommend movies to different users based on their interests. This helps the user to save time browsing the internet looking for movies ...
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Recommendation based systems can be used for recommending different web page, books, restaurants, tv shows, movies etc. The aim of movie recommendation system is to recommend movies to different users based on their interests. This helps the user to save time browsing the internet looking for movies from the thousand already existing ones. Content-based recommendation system describes the items that may be recommended to the user. Based on a data set, it predicts what movies a user will like considering the attributes present in the previously liked movies. Recommendation systems can recommend movies based on one or a combination of two or more attributes. While designing a movie recommendation system various factors are considered such as the genre of the movie, the director or the actors present in it. In this paper, the recommendation system has been built on cast, keywords, crew, and genres. A single column is created which will be the sum of all the 4 attributes, and it acts as a dominant factor for this movie recommender system.
