FIELD: physics.
SUBSTANCE: invention relates to a method and a system for recommending goods on an online trading platform. Method comprises: receiving a request for recommendations on goods from an electronic device, wherein the request was initiated by the user who specified the product from the plurality of products for purchase on the online trading platform; identification, in a plurality of products based on said product, a set of recommended products; obtaining user data of a user, including browsing data by the user and data of the user device of the electronic device; determining, based on user data for a given recommended product, a corresponding ranking parameter value for a specific user, which indicates a value of probability of perception by the user of said recommended product as being of interest to the user, wherein determination includes application by processor of machine learning algorithm (MLA), including first model and second model; ranking the set of recommended products in accordance with corresponding values of the ranking parameter for a specific user, thereby generating a ranked set of recommended products; and selecting, by the MLA processor from the ranked set of recommended products, at least one recommended product for the server to transmit an indication thereof to the electronic device of the user for presenting at least one recommended product to the user.
EFFECT: wider range of technical means, which enable to determine the recommended product for a specific user, increase the relevance of the personalized recommendation for the selected user by increasing the quality of personalization; improved quality of recommendation system operation due to modified model (MLA) using user data.
17 cl, 8 dwg
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Authors
Dates
2024-08-07—Published
2021-03-15—Filed