  This paper presents a study on the implementation of the author's Algorithm
of Recommendation Sessions (ARS) in an operational e-commerce information
system and analyses the basic parameters of the resulting recommendation
system. It begins with a synthetic overview of recommendation systems, followed
by a presentation of the proprietary ARS algorithm, which is based on
recommendation sessions. A mathematical model of the recommendation session,
constructed using graph and network theory, serves as the input for the ARS
algorithm. This paper also explores graph structure representation methods and
the implementation of a G graph (representing a set of recommendation sessions)
in a relational database using the SQL standard. The ARS algorithm was
implemented in a working e-commerce information system, leading to the
development of a fully functional recommendation system adaptable to various
e-commerce IT systems. The effectiveness of the algorithm is demonstrated by
research on the recommendation system's parameters presented in the final
section of the paper.
