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Commodity recommendation method and system based on big data

A product recommendation and big data technology, applied in data processing applications, commerce, instruments, etc., can solve problems such as blinding buyers, complex search functions, product name image user search results, etc., to increase frequency, improve industry standards, and comprehensively The effect of product reviews

Inactive Publication Date: 2019-08-23
HARBIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Online shopping is a topic that people are discussing now. With the development of the economy and the popularization of the Internet, various e-commerce platforms have risen, but there are also more and more problems in online shopping. In order to increase sales, most sellers buy trolls and publish a large number of false Products sold on the e-commerce platform may be marked with different product names or the same product sold in different stores on the e-commerce platform in different time periods It is also possible to mark a different product name, and errors in the product name will affect the user's search results
[0004] At the same time, the search function of the current e-commerce website is too complicated, and there are too many spam information recommended. When a buyer purchases a certain product, the e-commerce platform will recommend a large number of products of the same type to the buyer, and these products are often inferior. Products that affect the buyer's shopping experience

Method used

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  • Commodity recommendation method and system based on big data
  • Commodity recommendation method and system based on big data
  • Commodity recommendation method and system based on big data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0067] Such as figure 1 As shown, this embodiment provides a method for recommending commodities based on big data, including the following steps:

[0068] a) Obtain the first account information for logging into the current e-commerce platform;

[0069] b) Obtain the first product information selected by the user, and extract keywords included in the first product information, where the keywords include product name and product use;

[0070] c) Obtaining all second account information that has a friend relationship with the first account information in the e-commerce platform;

[0071] d) Extract the shopping record of the second account information, the shopping record includes a number of second product information, and the second product information includes product name, product use, product price and product evaluation;

[0072] e) judging whether keywords exist in the second product information;

[0073] f) If yes, extract the second product information including key...

Embodiment 2

[0079] Such as figure 2 As shown, the shopping record from which the second account information is extracted also includes:

[0080] Judging whether the product use included in the second product information is consistent with the product use included in the keyword;

[0081] If so, extract the second product information that is consistent with the product use in the keyword;

[0082] The second product information is exported to the first account information.

[0083] Obtaining all the second account information that has a friend relationship with the first account information in the e-commerce platform includes:

[0084] Obtain social software on the user's device;

[0085] Obtain the third account information on social software that has a friend relationship with the user;

[0086] Obtain the fourth account information that has a binding relationship with the third account information in the e-commerce platform;

[0087] Commodity recommendation is performed using the...

Embodiment 3

[0091] Such as Figure 4 As shown, the extracted product price and product evaluation in the second product information include:

[0092] Obtain the first favorable rating of the first product information on the e-commerce platform;

[0093] Obtain the second favorable rate of the second product information of the second account information, and the second favorable rate is an average value;

[0094] Judging whether the difference between the first favorable rate and the second favorable rate is within a preset range;

[0095] If not, the first product information is specially marked.

[0096] Extracting the product price and product evaluation in the second product information also includes:

[0097] Obtain the first account information and the second account information;

[0098] Outputting the first account information and the second product information to the second account information;

[0099] Obtain the detailed evaluation filled in by the second user;

[0100] Th...

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Abstract

The invention discloses a commodity recommendation method and system based on big data. The method comprises the steps of obtaining first account information logging in a current e-commerce platform;obtaining first product information selected by a user, and extracting a keyword included in the first product information, the keyword including a product name and a product purpose; obtaining all second account information having a friend relationship with the first account information in the e-commerce platform; extracting the shopping record of the second account information, wherein the shopping record comprises a plurality of pieces of second product information, and the second product information comprises product names, product uses, product prices and product evaluations; judging whether a keyword exists in the second product information or not; if yes, extracting second product information including the keyword; judging whether the product in the second product information is consistent with the product in the first product information or not; if yes, extracting a product price and product evaluation in the second product information; and outputting the extracted product price and the product evaluation to the first account information.

Description

technical field [0001] The present invention relates to the field of big data e-commerce, in particular to a method and system for recommending commodities based on big data. Background technique [0002] With the advent of big data, data is gradually realized to be of great use. A large amount of data is extracted and analyzed to classify useful data, and the target is judged by analyzing useful data. [0003] Online shopping is a topic that people are discussing now. With the development of the economy and the popularization of the Internet, various e-commerce platforms have risen, but there are also more and more problems in online shopping. In order to increase sales, most sellers buy trolls and publish a large number of false Products sold on the e-commerce platform may be marked with different product names or the same product sold in different stores on the e-commerce platform in different time periods It is also possible to mark a different product name, and errors ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06
CPCG06Q30/0629G06Q30/0631
Inventor 王克朝
Owner HARBIN UNIV