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Commodity recommendation method and system based on federal learning

A product recommendation and product technology, applied in machine learning, instruments, buying and selling/leasing transactions, etc., can solve the problems that private data cannot provide product recommendation decisions, and the repurchase rate of product recommendations is not high, so as to enhance the repurchase rate and improve the general sexual effect

Inactive Publication Date: 2022-04-12
青岛上禾文化传媒有限公司
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  • Summary
  • Abstract
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AI Technical Summary

Problems solved by technology

[0005] The embodiment of this application provides a product recommendation method and system based on federated learning, which is used to solve the problems in the prior art that private data cannot provide product recommendation decisions and the repurchase rate of product recommendation is not high

Method used

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  • Commodity recommendation method and system based on federal learning
  • Commodity recommendation method and system based on federal learning
  • Commodity recommendation method and system based on federal learning

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Embodiment Construction

[0046] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0047] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude one or Presence or addition of multiple other features, integers, steps, operations, elements, components and / or collections thereof.

[0048] It should also be understood that the terminology used in the specificati...

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Abstract

The invention discloses a federal learning-based commodity recommendation method, which comprises the following steps that: a cloud server obtains commodity purchase parameters, and the commodity purchase parameters comprise an ID of a commodity purchase user, a purchase time period, purchase times and a purchase place; based on the commodity purchase parameters, determining a time-space sequence of commodity purchase and user satisfaction; based on the space-time sequence and the user satisfaction, determining the matching degree of the commodity and the user through a federal learning model; obtaining a user portrait of the user, and determining high-correlation user features of the commodity based on the matching degree of the commodity and the user and the user portrait; and recommending the commodity to a user similar to the commodity purchasing user based on the commodity high-association user characteristics.

Description

technical field [0001] This application relates to the technical field of e-commerce, in particular to a product recommendation method and system based on federated learning. Background technique [0002] With the further popularization of e-commerce, people's demand for online commodity purchase is increasing day by day. At present, major e-commerce platforms can identify similar products by taking images, and recommend them to users for purchase, which increases the efficiency of product purchases to a certain extent. [0003] At present, the server will generate a user portrait based on the user's purchase records, and use the user portrait to find products that match the user's consumption habits or personality for recommendation. A typical example is the "thousands of people and thousands of faces" technology, which recommends according to the attributes of different consumers different commodities. [0004] However, there are two defects in the above-mentioned techno...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06G06N20/00
Inventor 周晓惠
Owner 青岛上禾文化传媒有限公司
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