Determining a User's Behavioral Model Based on Their Purchases

Many people spend considerable time in grocery stores looking for a suitable or new product. This process can be accelerated and made more convenient. As a part of determining the user's behavioral model based on their purchases, the task is to develop an iOS application that will recommend products to users in grocery stores based on their preferences. This paper describes the development of iOS application, building a recommendation system, development of the server part, as well as ways to store and organize user data. As a result, an application was developed on the iOS platform using the Swift 5.2 language, using architectural approaches to build the application. The basis of the recommendation system is collaborative filtering, the paper describes the method of its construction and gives the implementation. To store user data, the Google Firebase service is used, and to obtain recommendations from the server, an API was written in Python using the Flask library.