A fresh agricultural product recommendation method based on multi-granularity fuzzy data

A technology of fuzzy data and recommendation methods, applied in data processing applications, buying and selling/lease transactions, instruments, etc., can solve problems such as information overload, product failure, and recommendation to the hand, so as to improve user experience, enhance user viscosity, and improve conversion. rate effect

Active Publication Date: 2022-04-12
FUYANG NORMAL UNIVERSITY
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  • Application Information

AI Technical Summary

Problems solved by technology

However, in the existing e-commerce systems for fresh agricultural products, the recommendation effect for fresh agricultural products is not very ideal. The problem of "information overload" will lead to a large number of repeated recommendations or recommendation results that do not meet user expectations. The preferred product cannot be recommended to the hands smoothly

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  • A fresh agricultural product recommendation method based on multi-granularity fuzzy data
  • A fresh agricultural product recommendation method based on multi-granularity fuzzy data
  • A fresh agricultural product recommendation method based on multi-granularity fuzzy data

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Embodiment Construction

[0030] A specific embodiment of the present invention will be described in detail below in conjunction with the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific embodiment.

[0031] Referring to 1-2, the present invention provides a method for recommending fresh agricultural products based on multi-granularity fuzzy data, the method comprising:

[0032] Step S1, obtaining the characteristic parameters of users and products;

[0033] Step S2, constructing a feature model according to the feature parameters, and determining user preference parameters according to the feature model;

[0034] In step S3, the user preference parameters are input into the multi-granularity fuzzy data recommendation model to obtain the recommendation result, and the recommendation result is fed back to the user.

[0035] The specific analysis of the above step S1 is as follows:

[0036] User analysis: Compared with ...

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Abstract

The invention discloses a method for recommending fresh agricultural products based on multi-granularity fuzzy data. The method includes: obtaining characteristic parameters of users and products; constructing a characteristic model based on the characteristic parameters to determine user preference parameters; The parameters are input into the multi-granularity fuzzy data recommendation model to obtain the recommendation result, and the recommendation result is fed back to the user. The above solution provided by the present invention is not only based on the similarity between the user's preferred product and the recommended product, but also considers user satisfaction. Therefore, the recommendation can not only recommend products that meet the user's preferred behavior, but also generate the best recommendation for the user on this basis. For the current fresh agricultural products e-commerce platform, this will have great practical significance. It can not only increase the conversion rate and bring higher profits, but also improve user experience and increase user viscosity, so as to promote the promotion of fresh agricultural products in the current market. Stand out in the increasingly competitive market of e-commerce.

Description

technical field [0001] The invention relates to the technical field of agricultural product recommendation, in particular to a fresh agricultural product recommendation method based on multi-granularity fuzzy data. Background technique [0002] With the rapid development of the Internet and the e-commerce industry, people now choose more online shopping in terms of shopping methods. Buying fresh agricultural products online is becoming more and more known and used by people, and has become the most popular way for many young people to purchase fresh agricultural products. [0003] At present, the recommendation technology of major e-commerce platform systems has matured, and recommendation information has become one of the most convenient ways for Internet users to obtain information. Diversified recommendation services and personalized recommendation technology for users not only provide convenient information channels, but also enhance user stickiness. However, in the ex...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q30/06G06Q30/02G06Q50/02
CPCG06Q30/0603G06Q30/0631G06Q30/0282G06Q50/02
Inventor 陈秀明彭明星杨颖曹红兵南淑萍
Owner FUYANG NORMAL UNIVERSITY
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