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Fresh agricultural product online recommendation method considering customer consumption behaviors and preferences

A recommendation method, a technology for agricultural products, applied in the fields of instruments, buying and selling/lease transactions, electrical digital data processing, etc., to achieve the effect of accurate recommendation

Pending Publication Date: 2020-11-06
SOUTHEAST UNIV
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  • Claims
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AI Technical Summary

Problems solved by technology

[0005] Purpose of the invention: In order to solve the problem of accurate prediction of fresh agricultural products in e-commerce under the background of big data, the present invention provides an online recommendation method for fresh agricultural products that considers customer consumption behavior and preferences

Method used

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  • Fresh agricultural product online recommendation method considering customer consumption behaviors and preferences
  • Fresh agricultural product online recommendation method considering customer consumption behaviors and preferences
  • Fresh agricultural product online recommendation method considering customer consumption behaviors and preferences

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Embodiment Construction

[0053] The technical solution of the present invention will be described more comprehensively and in detail below in conjunction with the accompanying drawings and embodiments of the specification.

[0054] The present invention is based on the user and commodity data of the Alibaba Tianchi Competition website about fresh products, and constructs an embodiment applicable to the online purchase recommendation method for fresh agricultural products. The data set is divided into three parts: the first part is the historical behavior of the user on the product, the possible behaviors include click (click), purchase (buy), add to shopping cart (add-to-cart), favorite (add-to -favorite); the second part is user characteristic data; the third part is fresh agricultural product characteristic data.

[0055] A recommendation method for online purchase of fresh agricultural products based on customer choice behavior analysis, the implementation process is as follows figure 1 shown. Fi...

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Abstract

The invention discloses a fresh agricultural product online recommendation method considering customer consumption behaviors and preferences. The method comprises the following steps of (1) data analysis and preprocessing; (2) constructing a fresh agricultural product utility function based on latent semantics and behavior sequence utility; (3) constructing a fresh agricultural product selection model for traversing the purchase cycle; (4) solving the constructed fresh agricultural product selection model by adopting a gradient descent method; and (5) evaluating the prediction effect by usingthe recall rate and the precision. According to the method, seasonal characteristics of fresh agricultural products and interest preference characteristic factors of customers for the agricultural products can be effectively reflected, customer selection behaviors and user product characteristics are fully considered, and experiments prove that the method has a better prediction effect compared with other methods.

Description

technical field [0001] The invention relates to the field of fresh food e-commerce, in particular to an online recommendation method for fresh agricultural products that considers customer consumption behavior and preferences. Background technique [0002] With the development of cold chain logistics technology in the circulation of agricultural products and the continuous optimization of the e-commerce model, user stickiness and consumption habits of fresh food e-commerce are gradually formed, and e-commerce has become an indispensable channel for purchasing fresh products. Fresh agricultural products are perishable and must be sold within the season, otherwise there will be a lot of slow sales and waste. At the same time, the high operating costs caused by high loss and complicated supply and circulation links are also the current development of fresh food e-commerce. One of the bottlenecks encountered. Therefore, combined with big data, artificial intelligence and other ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06G06F16/9535
CPCG06Q30/0631G06F16/9535
Inventor 何勇陈静
Owner SOUTHEAST UNIV
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