Open AccessMovie Recommending System Using Collaborative Filtering
Author(s) -
P. Rama Rao
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.36377
Subject(s) - collaborative filtering , computer science , recommender system , cosine similarity , similarity (geometry) , domain (mathematical analysis) , content (measure theory) , entertainment , information retrieval , multimedia , data mining , artificial intelligence , pattern recognition (psychology) , image (mathematics) , mathematics , art , mathematical analysis , visual arts
Movies are one of the sources of entertainment, but the problem is in finding the content of our choice because content is increasing every year. However, recommendation systems plays here an important role for finding the content of desired domain in these situations. The aim of this paper is to improve the accuracy and performance of a filtration techniques existed. There are several methods and algorithms existed to implement a recommendation system. Content-based filtering is the simplest method, it takes input from the users, checks the movie and its content and recommends a list of similar movies. In this paper, to prove the effectiveness of our system, K-NN algorithms and collaborative filtering are used. Here, the usage of cosine similarity is done for recommending the nearest neighbours.