ANALYSIS OF USER COSTS BASED ON PAYMENTS FOR RECOMMENDATIONS IN MOBILE APPLICATIONS

Abstract

The innovation in payment methods has become one of the breakthroughs
in the ways of consumption of goods and services. The system provided by mobile
payments is also an important platform for promoting online business. Personalization
of the recommendation system is an important part of the business, which is based
on personal preferences, interests and purchasing behavior. User data collected from
previous purchase histories will be further processed and used to offer similar or
interesting products and information based on certain machine learning algorithms for
them. This article introduces cost analysis of a mobile application user based on artificial
intelligence to enable online platforms to create a business model for recommendation
systems inside the application. Machine learning is one of the tools with highly
automated information extraction from large amounts of data. In this paper, we will
consider machine learning in forecasting and analysis.