Predicting the Rating of Google Play Store Ap...

Predicting the Rating of Google Play Store Apps Using KNN and Random Forest Algorithms

Author Name : A. M. Rangaraj, T. Bhargavi, S. Ruksana\, S. Rehaman

ABSTRACT

Nowadays online reviews play a huge position in influencing the selection of consumers. Consumers display their revel in and records approximately first-rate of their evaluations. Online reviews normally encompass qualitative (textual content layout) and quantitative (score) formats. In the case of Google Play shop numeric scores can play a large position with inside the fulfillment of apps. People generally tend to consider that a high-big name score can be considerably connected with a terrific review. However, person big name stage score records does now no longer generally healthy with textual content layout of review. Despite many efforts to clear up this issue, Google Play Store continues to be dealing with this problem. Here, proposes a unique Google App numeric reviews & scores contradiction prediction framework the usage of Machine Learning approaches. Star scores are expected from textual content layout of evaluations after schooling Machine Learning models. Experimental effects display that primarily based totally on real person evaluations the proposed framework considerably predicts Exact score of app.

KEYWORDS: Online, Playstore, Applications, Score, Machine learning