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Product recommending method and system

A recommendation method and technology of a recommendation system, applied in the field of product recommendation methods and systems, can solve problems such as waste of Internet resources, no combination of buyers and users, and insufficient use of Internet human resources, etc., to achieve fast recommendation and sharing effects

Inactive Publication Date: 2015-04-29
阳珍秀
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Using the above method to recommend products to buyers and users does not make full use of the human resources of the Internet, and does not fully combine various buyers and users, resulting in a waste of Internet resources

Method used

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  • Product recommending method and system
  • Product recommending method and system

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0021] Embodiment 1. A product recommendation method. Combine below figure 1 The method provided in this embodiment will be described in detail.

[0022] figure 1 Among them, S101. Collect historical operation behavior records of buyer users from the e-commerce website platform.

[0023] Specifically, the buyer user clicks on the e-commerce platform, browses or purchases products, and other behaviors are collected, that is, the historical operation behavior records of the buyer user on the product are collected as the data basis for subsequent analysis of the buyer user's interests and hobbies.

[0024] S102. Analyze the interests and hobbies of the buyer user according to the collected historical operation behavior records of the buyer user.

[0025] Specifically, step S101 collects historical operation behavior records of buyer users, and this step analyzes the collected historical operation behavior records of buyer users to analyze the interests and hobbies of buyer use...

Embodiment 2

[0031] Embodiment 2, a product recommendation system. Combine below figure 2 The system provided in this embodiment will be described in detail.

[0032] figure 2 Among them, the system provided by this embodiment includes a behavior record collection module 201 , an interest analysis module 202 , a search module 203 , a product recommendation module 204 and an update module 205 .

[0033] Among them, the behavior record collection module 201 is mainly used to collect historical operation behavior records of buyer users from the e-commerce website platform.

[0034] Specifically, the behavior record collection module 201 collects behaviors such as clicking operations or browsing or purchasing products from the e-commerce platform of the buyer user, that is, collecting the historical operation behavior records of the buyer user on the product as a basis for subsequent analysis of the buyer user's interests and hobbies. data base.

[0035] The interest analysis module 202 ...

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Abstract

The invention discloses a product recommending method and system, wherein the product recommending method comprises the following steps that historical operation behavior records of buyers are collected from an e-commerce website platform; hobbies and interests of the buyers are analyzed according to the collected historical operation behavior records of the buyers; users with the similar hobbies and interests are found; products concerned by the users with the similar hobbies and interests are recommended to the buyers. The product recommending method provided by the invention has the advantages that the products concerned by other users with the similar hobbies and interests can be recommended to the buyers, so the fast recommendation of the products is realized, and the product resource sharing is also realized.

Description

technical field [0001] The invention relates to the technical field of product recommendation, in particular to a product recommendation method and system. Background technique [0002] E-commerce is a major manifestation of modern B2B, providing services to customers. In recent years, the scale of Internet transactions (B2B) of Chinese enterprises has been among the best in the global market. With the continuous expansion of e-commerce scale, the number of products has grown rapidly. It becomes more complicated. Faced with countless product information, users often get lost in a large amount of product information space and cannot find the product they need smoothly. [0003] In order to solve this problem and improve the service capability of e-commerce platform, personalized recommendation system came into being. At present, the main recommendation method is to analyze the interests and hobbies of the buyers based on the historical operation behavior records of the buye...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q30/02
CPCG06F16/337G06F16/9535G06Q30/0201
Inventor 阳珍秀
Owner 阳珍秀
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