Recommendation Systems: Overview, Future Scope, and Effectiveness of Modelling Based on Mind Maps

Abstract

Recommendation systems/engine do the filtrations the data for that it uses different algorithms and recom- mend/predict the most suitable items for users. It starts capturing which users may purchase. Three main methods are  used  in our recommendation programs. Another Demographic Filtering i.e. Basic premise behind this system is that such  films  are  they are very popular and highly respected  they  will  have  highs opportunities to appeal to the average audience. One is cooperation filtering, when we try to bring the same person together to form the group to make recommendations for the user. Hybrid Recommendation System for movie use a combination of filtering in conjunction with content of complimentary programs. One of the best ways to get the recommendation is using the sites like IMDB, rotten Tomato’s etc. because they give the ratings to movies based on user reviews and critics comments and various factors included. Hence, we can also use ratings as a base to make our model to predict the recommended movies based on some kind or numerical rating or value. Hence, Higher the values of rating or number the more the movies are recommended to the users.