Federated product recommendation method, device and equipment and computer storage medium

Abstract

The invention discloses a federated product recommendation method, device and equipment and a computer storage medium. The method is applied to a recommendation terminal. The method comprises the following steps of when a product recommendation request is received, extracting target user data corresponding to the product recommendation request, acquiring candidate set product data, inputting the target user data and the candidate set product data into a collaborative memory network model, acquiring a feature representation set, the collaborative memory network model being obtained by executinga longitudinal federation process based on user feature information and product feature information and conducting iterative training on an initial analysis model, and generating a product recommendation set corresponding to the target user data according to the feature representation set. According to the method, the collaborative memory network model is constructed through longitudinal federation, the model is fully learned while data leakage is reduced, and the recommendation accuracy is improved.

Description

technical field [0001] This application relates to the artificial intelligence technology field of financial technology (Fintech), and in particular to a federal product recommendation method, device, equipment and computer storage medium. Background technique [0002] With the continuous development of financial technology, especially Internet technology and finance, more and more technologies (such as distributed, blockchain, artificial intelligence, etc.) are applied in the financial field. [0003] There are more and more products in the current financial business. The recommendation system can recommend products that are more suitable for users. The recommendation system is usually based on a large amount of user data. For most companies, it usually only has There is a small amount of user data, and for reasons such as protecting user privacy, companies cannot share their own user data, and each company can only build a recommendation system based on a small amount of u...

AI Technical Summary

Problems solved by technology

[0004] The main purpose of this application is to provide a federal product recommendation method, device, equipment and computer storage medium, aiming to solve the technical problem that it is difficult to accurately recommend products to users in the prior art, resulting in poor recommendation effect of the recommendation system

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