A Novel Approach to Predict Popularity Rating Using KNN and SVD

In this hectic world, every one of us wants some peaceful time by doing certain activities like playing our favorite games, watching movies, watching social media platforms, etc..The most popular among them is watching social media platforms. The stress can be reduced by watching different genre of movies like crime, thrillers, love, and emotions. Many social media platforms are available, like Disney + Hot Star, Amazon Prime Video, Netflix, and so on. Finding TRP for these social platforms is essential for the program broadcaster. It was quite challenging task to predict the TRP of each show. In this work, the TRP prediction is done by using the knowledge of machine learning. This paper imposes on finding the television rating point using K-Nearest Neighbors (KNN) and singular value decomposition (SVD) by using Kaggle, an open-source dataset. The KNN is used to find the TRP by calculating the characteristics of each one. Then, the similar one is taken from KNN, and then ranking is done by using SVD. Finally, result is validated with the previous one, which produces high accuracy.