Abstract:

The enormous development of the Internet, both in the geographical scale and in the area of using its possibilities in everyday life, determines the creation and collection of huge amounts of data. Data for which, due to the scale, it is not possible to analyze them using traditional methods, which in turn makes it necessary to use modern methods and techniques. Such methods are provided, among others, by the area of recommendations. The aim of this study is to present a new algorithm in the area of recommendation systems, an algorithm based on data from various sets of information, both static (categories of objects, features of objects) and dynamic (user behavior).