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.

翻译：本文研究了作者提出的基于推荐会话的ARS算法在运行中的电子商务信息系统中的实现，并分析了所生成推荐系统的基本参数。文章首先对推荐系统进行了综合概述，随后介绍了基于推荐会话的专有ARS算法。采用图论与网络理论构建的推荐会话数学模型，作为ARS算法的输入。本文还探讨了图结构的表示方法，以及使用SQL标准在关系数据库中实现表示推荐会话集的G图。ARS算法已在实际运行的电子商务信息系统中实现，从而开发出一个可适配多种电子商务IT系统的全功能推荐系统。论文最后部分通过对推荐系统参数的研究，验证了该算法的有效性。