  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. Due to the scale, it is not
possible to analyse them using traditional methods, therefore it makes a
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, the algorithm
based on data from various sets of information, both static (categories of
objects, features of objects) and dynamic (user behaviour).
