Методи класифікації клієнтської бази на основі поведінкової моделі користувачів

Abstract

The given paper analyzes currently available methods for client base classification, their benefits and importance for businesses. The main purpose of this article is to provide information regarding one of the derivatives of classification methods, which are based on user behavioral model – recommendation systems. Recommendation systems can be divided into three general groups. More precisely, they can be divided into: collaborative filtering systems, content-based filtering systems and hybrid systems. Each of these recommendation methods are described in this paper, providing possible use cases and examples.