FIELD: computer equipment.
SUBSTANCE: invention relates to machine learning means for selection of recommended content for user of electronic device. Method is carried out by a recommendation server, which is accessible to an electronic device through a data network, recommendation server performs algorithm of machine learning after its training. Method includes: obtaining an indication of a plurality of user-element interactions, each interaction associated with a user and a digital element; based on a plurality of user-element interactions, creating a user-relevance assessment matrix; decomposition of the user-element relevance assessment matrix into the user matrix and the elements matrix, wherein the decomposition includes: initialisation of a matrix of elements using element vectors, vectors of elements have been created such that digital elements with identical content have identical vectors of elements, initialisation of user matrix using user vectors; iterative optimization of user matrix and elements matrix; maintaining an optimized matrix of elements.
EFFECT: technical result is widening the range of recommended content for a user.
17 cl, 6 dwg
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Authors
Dates
2020-09-07—Published
2016-09-09—Filed