Commodity recommendation method and device

A product recommendation and product technology, applied in the field of data analysis, can solve the problem of low recommendation accuracy, and achieve the effect of increasing the possibility, increasing the breadth, and improving the accuracy

Active Publication Date: 2019-11-15
PING AN TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, the present invention provides a product recommendation method and device, the main purpose of which is to solve the problem of low recommendation accuracy in the prior art

Method used

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  • Commodity recommendation method and device
  • Commodity recommendation method and device
  • Commodity recommendation method and device

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Embodiment Construction

[0027] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0028] The embodiment of the present invention provides a product recommendation method, such as figure 1 As shown, the method includes:

[0029] 101. Obtain recommendation data.

[0030] Recommended data refers to the basic data required to calculate recommended products. Recommended data includes user information, product data information and product text information. User information refers to the user's age, name, registration...

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Abstract

The invention discloses a commodity recommendation method and device, relates to the technical field of data analysis, and aims to solve the problem of low recommendation accuracy in the prior art. The method mainly comprises the following steps: acquiring recommendation data, wherein the recommendation data comprises user information, commodity data information and commodity text information, theuser information refers to the age, name, registration duration and registration address of a user, the commodity data information refers to digital description information of commodities browsed bythe user, and the commodity text information refers to text description information of commodities browsed by the user; encoding the commodity text information according to a self-encoding algorithm to generate a text feature code; inputting the user information, the commodity data information and the character feature codes into a parallel recurrent neural network, and calculating the probabilitythat each commodity in a commodity library is clicked by a user; and according to the descending order of the probabilities, selecting and displaying a preset number of recommended commodities corresponding to the probabilities. The commodity recommendation method and device are mainly applied to the commodity recommendation process.

Description

technical field [0001] The present invention relates to the technical field of data analysis, in particular to a commodity recommendation method and device. Background technique [0002] Commodity recommendation is becoming more and more important in the modern network, and many network services are dedicated to helping users find the most relevant content in the shortest time. In the prior art, commodities are recommended to each user according to user information and commodity information searched by the user. Specifically, extract the target user’s associated user information and associated product information, train the deep neural network model according to the user’s historical behavior data, input the associated user information and associated product information into the deep neural network model, and calculate the correlation between the user and the product Coefficient, recommend products to users according to the correlation coefficient. [0003] There are many ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06G06N3/04G06N3/08
CPCG06Q30/0631G06N3/08G06N3/044G06N3/045
Inventor 金戈徐亮
Owner PING AN TECH (SHENZHEN) CO LTD
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