The aim of this work is to build a neural network architecture for the recommendation of texts, adapted to solve the problem of cold start, training one complete model instead of two, responsible for the translation of object into a vector space and the interaction of vectors of objects and users, without compromising the quality of recommendations.
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This work is designed to improve the recommendations of new objects that will allow the platform using this approach to navigate faster in the information space and capture more and more users, which will increase the profit of the service
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vklyukin/news_rec_sys
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This work is designed to improve the recommendations of new objects that will allow the platform using this approach to navigate faster in the information space and capture more and more users, which will increase the profit of the service
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