Commodity recommendation method based on countermeasure network, electronic device and storage medium

A product recommendation and electronic device technology, applied in neural learning methods, biological neural network models, business, etc., can solve problems such as accuracy needs to be improved

Pending Publication Date: 2019-03-22
PING AN TECH (SHENZHEN) CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, single-domain recommendation systems are mainly implemented using traditional Bayesia

Method used

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  • Commodity recommendation method based on countermeasure network, electronic device and storage medium
  • Commodity recommendation method based on countermeasure network, electronic device and storage medium
  • Commodity recommendation method based on countermeasure network, electronic device and storage medium

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Embodiment Construction

[0067] It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0068] Specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0069] The present invention provides a product recommendation method based on an adversarial network, which is applied to an electronic device 1 . refer to figure 1 As shown, it is a schematic diagram of the application environment of the preferred embodiment of the product recommendation method based on the adversarial network of the present invention.

[0070] In this embodiment, the electronic device 1 may be a server, a mobile phone, a tablet computer, a portable computer, a desktop computer, or other terminal equipment with computing functions.

[0071] The electronic device 1 includes a memory 11 , a processor 12 , a network interface 13 and a communication bus 14 .

[0072]...

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Abstract

The invention relates to a commodity recommendation method based on antagonistic network, an electronic device and a storage medium, comprising: obtaining behavior data of a user to a commodity, wherein the behavior data comprises purchase data and browse data; obtaining the behavior data of the user to the commodity; obtaining the behavior data of the user to the commodity. Generating a random input vector according to the behavior data; Inputting a random input vector and behavior data into a countermeasure network model, the countermeasure network model comprising a generator and a discriminator, wherein the random input vector input generator obtains a randomly generated vector, the randomly generated vector is used as a virtual input of the discriminator, and the behavior data is usedas a real input of the discriminator; judging the true input and the virtual input by The discriminator, judging the ratio of the true input and the virtual input by output, and judging whether thediscriminator converges or not. When the discriminator does not converge, the generator is driven to update until the discriminator converges, and the randomly generated vector of the generator is used as a recommendation sequence. The method, apparatus and medium accurately learn the characteristics of the recommending entity.

Description

technical field [0001] The present invention relates to the technical field of commodity recommendation, and more specifically, relates to a commodity recommendation method based on an adversarial network, an electronic device and a storage medium. Background technique [0002] With the development of network technology, more and more users browse and purchase products through the Internet, APP, etc. In order to facilitate users to purchase products, products that they may like can be recommended to users. [0003] At this stage, single-domain recommendation systems are mainly implemented using traditional Bayesian prior / collaborative filtering algorithms or deep learning network models such as CNN / RNN / DBN. improve. Contents of the invention [0004] In view of the above problems, the object of the present invention is to provide a recommendation method based on a generative adversarial network for accurately learning features of recommended entities, an electronic device...

Claims

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Application Information

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IPC IPC(8): G06Q30/06G06N3/04G06N3/08
CPCG06Q30/0631G06N3/08G06N3/044G06N3/045Y02D10/00
Inventor 邓悦金戈徐亮肖京
Owner PING AN TECH (SHENZHEN) CO LTD
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