E-commerce platform commodity recommendation method and device, server and storage medium

A technology of e-commerce platform and recommendation method, which is applied in the direction of business, equipment, sales/lease transactions, etc., can solve the problems of improving sales performance that cannot be intelligentized, and achieve the effect of improving sales performance and increasing purchase rate

Pending Publication Date: 2020-04-28
深圳市华宇讯科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Each user has different interests. Existing solutions cannot provide users with a friendly shopping experience, and cannot intelligently improve sales performance.

Method used

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  • E-commerce platform commodity recommendation method and device, server and storage medium
  • E-commerce platform commodity recommendation method and device, server and storage medium
  • E-commerce platform commodity recommendation method and device, server and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0049] figure 1 The flow diagram of a method for recommending products on an e-commerce platform provided in Embodiment 1 of the present invention is applicable to the scenario of recommending products for different users. The method can be executed by a device for recommending products on an e-commerce platform. It can be realized by means of software and / or hardware, and can be integrated on a server.

[0050] Such as figure 1 As shown, the method for recommending commodities on an e-commerce platform provided in Embodiment 1 of the present invention includes:

[0051] S110. Acquire user behavior data of the first user.

[0052] Wherein, the first user refers to a user who uses the e-commerce platform for shopping. In this embodiment, the first user does not refer to a specific user. User behavior data refers to the data of users using the e-commerce platform. Specifically, user behavior data includes but is not limited to one or more of the basic information of purchas...

Embodiment 2

[0081] figure 2 It is a schematic flowchart of a method for recommending commodities on an e-commerce platform provided in Embodiment 2 of the present invention. This embodiment is a further refinement of the above-mentioned technical solution, and is applicable to scenarios in which commodities are recommended for different users. The method can be executed by a device for recommending commodities on an e-commerce platform, and the device can be implemented in the form of software and / or hardware, and can be integrated on a server.

[0082] Such as figure 2 As shown, the method for recommending commodities on the e-commerce platform provided in Embodiment 2 of the present invention includes:

[0083] S210. Acquire user behavior data of the first user.

[0084]Wherein, the first user refers to a user who uses the e-commerce platform for shopping. In this embodiment, the first user does not refer to a specific user. User behavior data refers to the data of users using th...

Embodiment 3

[0102] image 3 It is a schematic structural diagram of a device for recommending products on an e-commerce platform provided by Embodiment 3 of the present invention. This embodiment is applicable to the scenario of recommending products for different users. The device can be implemented in the form of software and / or hardware, and can integrated on the server.

[0103] Such as image 3 As shown, the device for recommending products on an e-commerce platform provided in this embodiment may include an acquisition module 310, an image module 320, an algorithm training module 330, a recall module 340, a sorting module 350, and a display module 360, wherein:

[0104] An acquisition module 310, configured to acquire user behavior data of the first user;

[0105] A portrait module 320, configured to determine a user portrait of the first user based on the user behavior data;

[0106] The algorithm training module 330 is configured to train a preset recall model based on a first ...

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PUM

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Abstract

The embodiment of the invention provides an e-commerce platform commodity recommendation method and device, a server and a storage medium. The e-commerce platform commodity recommendation method comprises the steps of obtaining user behavior data of a first user; determining a user portrait of the first user based on the user behavior data; training a preset recall model based on a first preset algorithm; training a click prediction model based on a second preset algorithm; determining a recommended commodity set according to the user portrait and the preset recall model, wherein the recommended commodity set comprises a plurality of recommended commodities; sorting a plurality of recommended commodities in the recommended commodity set according to the user behavior data and the click prediction model; and returning a sorting result to the commodity recommendation list and displaying the commodity recommendation list to the first user. According to the invention, the effect of providing different recommended commodities for different users to improve the purchase rate of the users is achieved.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of e-commerce, and in particular to a method, device, server and storage medium for recommending commodities on an e-commerce platform. Background technique [0002] With the rapid development of the Internet, more and more users start to shop and consume online. [0003] Users need to find products on the e-commerce platform, and then place an order for the products they like. At present, in order to increase the purchase rate of users, when a user opens an e-commerce platform, a product is recommended to the user, and the user can select a product of interest from the recommended products to purchase. [0004] However, currently, the products recommended to users in e-commerce are the same, and each user sees the same sorted product list. However, the interests of each user are different, and the existing solutions cannot provide users with a friendly shopping experience with th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06
CPCG06Q30/0631G06Q30/0625
Inventor 史继群周大臣陈旺贺欢
Owner 深圳市华宇讯科技有限公司
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