The thesis presents the implementation of the architecture of a recommendation system for recommending consumer goods. The main focus of the implementation is on the architecture of this system and on improving the speed of product recommendation. In the first part of the thesis, a brief introduction is given on what the consumer goods sector is, which products belong to it and what are the differences when shopping for these products compared to other products. This is followed by a presentation of recommender systems, where they are used and how they are used to recommend products. The second part of the thesis will present the implementation of a recommendation system architecture for the case of an online grocery store. The frontend of the application, which should contain the web site through which the user purchases the product, will be omitted. Instead, the system will receive the necessary data in JSON format and then return the recommended products in JSON format. Finally, the thesis will conclude with an analysis of the implemented recommender system architecture and conclusions.
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