Mobile App Recommendation System Using Machine learning Classification

The introduction of new ideas with mobile applications can bring great change to people around the world. Nowadays Thousands of apps are developed to satisfy different needs of people such as for doing jobs, transactions, entertainment etc. and distributed over the Internet. So most of the existing app stores available might face difficulties for recommending a particular app to a particular user. So there is a need for recommending apps for the users according to their personal preferences and various other limitations. We made a mobile application recommendation system with ratings, Size, and Permission as parameters and we will recommend suitable apps to the user by evaluating these parameters. Here we are using Apkpure.com which is one of the famous android application markets and also makes use of Web Crawler which helps in collecting information about the website and helps in validating hyperlinks. After that by using the Clustering Algorithm, applications are grouped or clustered based on Popularity, Permission and Security aspects. This paper aims to provide a simple recommendation system without compromising rating, size and Permission aspects.