KNN based Entertainment Enhancing System
Abdul Gafoor, Athi Lakshmi Srujana, Arvapalli Nagasri, Garikipati Sri Sai Durgaprasad, Lokesh Sai Kumar Dasari · 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) · 2022
Entertainment is the one thing every individual strives to have besides the common or basic needs in one's life. In the other requirements of humanity, that can be widely generalized. When thirsty one seeks for the same water as any other person in the world. But when it comes to entertainment sector, every individual has their own requirement in what they seek. There are huge number of sources of entertainment in the current technological era. So, one obviously expects the movies or shows are tailored for his own diversified taste. There are already filters available for filtering the content on the basis of the genre like collaborative filtering. But that single parameter is not always sufficient for delivering most of the time. So, in this paper a movie recommendation system is developed using one of the most powerful, well known and widely being used machine learning algorithm KNN to enhance the prediction of likeliness of particular digital content to a user whose likeliness is previously analyzed.