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Commodity strict selection method and system based on e-commerce big data

A technology of big data and products, applied in the field of big data, to achieve high product quality and cost-effectiveness, avoid product quality or other disputes, and improve the performance of anchors with goods

Pending Publication Date: 2022-04-29
浪潮卓数大数据产业发展有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Online shopping has become a very important part of people's lives. At present, more and more people choose online shopping, which can not only enjoy the convenience of shopping, but also enjoy the price advantage, but not all products are cost-effective and of high quality.

Method used

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Examples

Experimental program
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Effect test

Embodiment 1

[0067] as attached figure 1 As shown in the present invention, the product selection method based on e-commerce big data, the method is to acquire and accumulate the average price of the product industry, store operating conditions and preferential prices through big data technology, and obtain products with good credit, merchants with good evaluation and For relatively hot-selling products, provide a reference for product selection for the anchor with the goods; the details are as follows:

[0068] S1. Use crawler technology to obtain basic information of online stores and store commodities, and store them in the database;

[0069] S2. Obtain the store's price information and hot-selling product information, obtain the latest lowest price information of the product, and store it in the database;

[0070] S3. Establish a product classification and grading model (decision classification model model): classify and label the products of high-quality online stores, establish a se...

Embodiment 2

[0109] The product strict selection system based on e-commerce big data of the present invention, the system includes:

[0110] Obtaining module 1, which is used to obtain basic information of online business stores and basic information of store products by using crawler technology, and store them in the database;

[0111] Obtaining module 2, which is used to obtain the store's price information and hot-selling product information, obtain the latest lowest price information of the product, and store it in the database;

[0112] The model building module is used to establish a product classification and grading model (decision classification model model), classify and label the products of high-quality online stores, establish a selection library, and eliminate stores with poor reputation;

[0113] The selection module is used to provide selections of different categories and levels according to the anchor's delivery or consumer purchase needs.

[0114] The basic store inform...

Embodiment 3

[0119] The embodiment of the present invention also provides an electronic device, including: a memory and a processor;

[0120] Wherein, the memory stores computer-executable instructions;

[0121] The processor executes the computer-executed instructions stored in the memory, so that the processor executes the product selection method based on e-commerce big data in any embodiment of the present invention.

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Abstract

The invention discloses a commodity strict selection method and system based on e-commerce big data, belongs to the technical field of big data, and aims to solve the technical problem of how to quickly and reasonably select commodities and improve the cost performance of the commodities while ensuring the commodity quality. According to the technical scheme, the method obtains and accumulates commodity industry average prices, store operation conditions and preferential prices through a big data technology, obtains commodities with good credit, merchants with good evaluation and relatively hot selling commodities, and provides commodity selection reference for anchors with commodities; the method specifically comprises the following steps: acquiring basic information of a network business shop and basic information of shop commodities by utilizing a crawler technology, and storing in a database; obtaining price information and hot commodity information of a shop, obtaining recent minimum price information of commodities, and storing the recent minimum price information in a database; establishing a commodity classification and grading model: carrying out grading and labeling on commodities of high-quality network shops, and establishing a commodity selection library; and according to the goods carried by the anchor or the purchase demand of the consumer, different categories and different grades of selected goods are provided.

Description

technical field [0001] The present invention relates to the field of big data technology, in particular to the field of big data technology applied to online shopping product selection, specifically a method and system for strict product selection based on e-commerce big data. Background technique [0002] Online shopping has become a very important part of people's lives. At present, more and more people choose online shopping, which can not only enjoy the convenience of shopping, but also enjoy the price advantage. However, not all products are cost-effective and of up-to-standard quality. With the rise of the anchor delivery model, various delivery scandals have emerged, such as allegedly high prices, counterfeit and shoddy products, which have seriously misled consumers and affected the reputation of the anchor. So how to quickly and reasonably select products, Improving the cost performance of commodities while ensuring the quality of commodities is a technical problem ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2457G06F16/951G06F16/906G06F16/9535G06Q30/02
CPCG06F16/24573G06F16/951G06F16/906G06F16/9535G06Q30/0282G06Q30/0201
Inventor 张彪谢传家
Owner 浪潮卓数大数据产业发展有限公司
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