The Film Recommendation System uses the Recursive Elimination Algorithm
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Abstract
The number of films has increased to become denser. Therefore, it is very difficult to find the film that users are looking for through existing technology. For this reason, users want a system that can suggest their film needs and the best technology about this is a recommendation system. However, the most recommended system is to use the collaborative filtering method to predict user needs because this method provides the most accurate predictions. Currently, many researchers are concerned with developing methods for increasing accuracy rather than using collaborative screening methods. In this paper we use the Recursive Elimination (RElim) algorithm for the film recommendation system. As a result, each itemset is annotated with its support. Itemset support is the number of times the itemset appears in the transaction database
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