Product recommendation method and device, electronic equipment and readable storage medium

Abstract

The invention relates to an artificial intelligence technology, and discloses a product recommendation method, which comprises the following steps of: vectorizing acquired historical numerical value feature information to obtain a historical numerical value feature vector; performing vectorization processing on the obtained historical character feature information to obtain a historical character feature vector; carrying out vector fusion on the historical numerical value feature vector and the historical character feature vector to obtain a corresponding fusion feature vector; performing iterative training on a pre-constructed deep learning model by using the fusion feature vector to obtain a product recommendation model; according to an obtained product recommendation request, utilizing a product recommendation model to analyze the recommendation probability of each product in a pre-constructed product set; and screening the products in the product set by using the recommendation probability to obtain recommended products. The invention further relates to a blockchain technology, and the user historical information can be stored in a blockchain node. The invention further provides a product recommendation device, equipment and a medium. The accuracy of product recommendation can be improved.

Description

technical field [0001] The invention relates to artificial intelligence technology, in particular to a product recommendation method, device, electronic equipment and readable storage medium. Background technique [0002] With the development of the economy, users have higher and higher requirements for the purchase experience of various products. In order for users to have a better shopping experience, it is necessary to be able to accurately recommend the products that users need to improve the user's shopping experience. [0003] However, most of the current product recommendation methods can only extract the characteristics of a certain dimension of the user for product recommendation, such as the user's age, gender, job, etc. The dimension of product matching is relatively single, and the accuracy of product recommendation is low. Contents of the invention [0004] The invention provides a product recommendation method, device, electronic equipment and computer-readab...

AI Technical Summary

Problems solved by technology

[0003] However, most of the current product recommendation methods can only extract the characteristics of a certain dimension of the user for product recommendation, such as the user's age, gender, job, etc. The dimension of product matching is relatively single, and the accuracy of product recommendation is low.

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