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Multi-dimensional agricultural product supply and demand bidirectional personalized recommendation method

A recommendation method and technology for agricultural products, applied in resources, instruments, sales/lease transactions, etc., can solve problems such as difficult sales of agricultural products, asymmetric information between supply and demand of agricultural products, and information asymmetry between supply and demand of agricultural products, so as to achieve high recommendation accuracy and improve marketing performance effect

Pending Publication Date: 2021-12-21
KUNMING UNIV OF SCI & TECH
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, the information asymmetry between the supply and demand of agricultural products in my country's "three rural problems" and the difficulty in selling agricultural products, the existing one-way recommendation system cannot effectively solve the problem of information asymmetry between the supply and demand of agricultural products in the network environment
Most of the previous studies only used single-dimensional static analysis from the perspective of customers, and accurate identification of the situation of both the supply and demand of agricultural products, the characteristics of customers and agricultural products is very important to improve the accuracy of personalized recommendations, so the applicant designed a multi-dimensional two-way personality of agricultural product supply and demand The recommended method to solve the above problems

Method used

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  • Multi-dimensional agricultural product supply and demand bidirectional personalized recommendation method
  • Multi-dimensional agricultural product supply and demand bidirectional personalized recommendation method
  • Multi-dimensional agricultural product supply and demand bidirectional personalized recommendation method

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Experimental program
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Effect test

Embodiment 1

[0059] Development and verification of two-way scene recognition system for agricultural products based on perceived value theory and S-O-R theoretical model;

[0060] This project takes the perceived value theory and S-O-R model as the theoretical basis of situation recognition, combines the characteristics of agricultural products, and adopts empirical methods to develop measurement items in each dimension of the situation recognition system from both macro and micro aspects, and to identify the impact of farmers' production and agricultural product customer preferences. important contextual indicators for the project and validate them.

[0061] (1) Macro situation identification

[0062] It mainly refers to the production, processing and consumption situations of agricultural products in the areas where producers and customers are located. It focuses on the geographical location of logistics, network communication and other infrastructure service providers, farmers, and cus...

Embodiment 2

[0068] Use the network platform to extract the characteristics of agricultural product customers and agricultural products;

[0069] Agricultural product customer feature extraction

[0070] The main customer in this study is the registered user of the agricultural product website, and the feature analysis includes attribute and behavior analysis ( figure 2 );

[0071] (1) Attribute characteristics: attributes are often static or relatively stable within a certain period of time, including the customer's location, gender, age, marriage, education, occupation and income, etc.;

[0072] (2) Behavior characteristics: mainly refers to customer consumption behavior and evaluation behavior, including the collection of all behavior information when visiting on the page.

[0073] This research includes several types of behavior data when users visit web pages: (1) marking behaviors, such as adding to favorites, adding bookmarks, sharing to Moments, putting in shopping carts, etc.; ...

Embodiment 3

[0079] Construct a customer preference model for agricultural products based on situation identification, agricultural product customers and product characteristics;

[0080] The construction of the customer preference model for agricultural products consists of three parts: the acquisition and update of the user model and the construction of the user group. Construct a reference ontology to realize the learning and updating of the customer preference model; the user group is obtained through similarity calculation for each customer preference ontology;

[0081] Further, the customer trust similarity:

[0082]

[0083] The above formula calculates the significant trust degree, using B u Denotes the set of rated products for user u, B v Denotes the set of rated products for user v, B m Represents the product set with the most co-rated products with user v, the numerator represents the intersection of the co-rated products of user u and user v, and the denominator represen...

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Abstract

The invention discloses a multi-dimensional agricultural product supply and demand bidirectional personalized recommendation method. An agricultural product bidirectional situation recognition system based on a perceptual value theory and an S-O-R theoretical model is developed; features of customers and agricultural products are extracted by using a network platform; an agricultural product customer preference model is constructed based on situation identification, customer and product features; an agricultural product supply and demand two-way personalized recommendation model is constructed based on the preference model and the agricultural product features; and agricultural product supply and demand two-way personalized recommendation is carried out by constructing a two-way personalized recommendation model. For a demand side, accurately recommending similar social groups according to customer similarity, accurately recommending agricultural products with high preference degree according to neighbor preference, and accurately recommending agricultural product project groups according to agricultural product similarity; and, for a supplier, similar customer groups are accurately recommended, and demand preference information is accurately recommended according to a project prediction score calculated according to the similarity of agricultural product projects, so that the supplier adjusts a production and sales decision according to the demand information.

Description

technical field [0001] The invention relates to the technical field of information recommendation, in particular to a two-way personalized recommendation method for multi-dimensional supply and demand of agricultural products. Background technique [0002] With the continuous advancement and development of the national socialist cause construction process, the development of my country's agricultural economy has gradually presented a completely different development model from the past. The traditional concept of agricultural information analysis can no longer be synchronized with the economic development model of today's society. The application of the innovative development model of the national agricultural economy makes the existence of the agricultural monitoring and early warning system indispensable. Through the extraction of information characteristics, observation of information changes, and tracking of information flow in agricultural processes and links such as a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06G06Q10/06G06Q50/02G06K9/62G06F16/9535
CPCG06Q30/0631G06F16/9535G06Q10/06393G06Q50/02G06F18/211
Inventor 龚映梅侯玉寒王有刚王宁
Owner KUNMING UNIV OF SCI & TECH
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