Abstract: In todays world ,the recommendation system are grownly important. Peoples now days finding out best services or products for themselves.
Due to this, the recommendation system are important as they helping to make the right choice, without expending the cognitive resource.
In this article, we aim to reduce human efforts by giving him the suggestion, to the users on the basis of their interest. we use Collaborative recommendation by implementing K-Nearest Neighbors algorithm.
Collaborative filtering technique most widely used by recommendation system. Collaborative filtering predicts the user choice in item selection based on the known user rating of the items. It is effective for solving the information overload problem.’
Collaborative filtering can be divided into two main branches, Memory based collaborative filtering and model based collaborative filtering.

Keyword: Recommendation System, Movie Recommendation System, KNN, Machine Learning.

PDF | DOI: 10.17148/IJARCCE.2022.11570

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