• Mr. S. Areef Basha
• Mr. Dr M. Sravan Kumar Reddy

Users can utilize the application suggestion feature in recent Android operating systems to find a replacement application that is similar to the one they are looking for. The current Google and Google Play store recommendation system is said to suggest apps that are similar to a target application while also taking into account the popularity of each app. It does not, however, account for the security features of each program or the user's preferences. Through app markets, end users can access a variety of mobile applications (or apps) in abundance. These apps frequently produce network traffic, which uses up users' mobile data plans and could even pose a security risk. However, a mobile device's amount and kind of network traffic Due to the absence of a formal assessment methodology, the app in the real world is still only partially known. The cost of network traffic for Android apps in the official Android markets is first measured and analyzed in this study. We conclude from the findings that the traffic costs for apps in various categories vary. Particularly, the cost of network traffic varies noticeably among apps with comparable functionality. Then, in contrast to traditional methods for app recommendation, we incorporate measures for traffic cost into our algorithm. The suggested recommendation algorithm can effectively assist mobile app users in avoiding a variety of potential security and privacy issues brought on by the needless network traffic consumption, according to experimental results.

Unsupervised Machine Learning, Recommendation System, Content Based Filtering.

"Recommending Android APPs Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 8, page no.a92-a95, August-2023, Available :http://www.jetir.org/papers/JETIR2308015.pdf

"Recommending Android APPs Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 8, page no. ppa92-a95, August-2023, Available at : http://www.jetir.org/papers/JETIR2308015.pdf