E-commerce shopping navigation method based on big data and system thereof

A navigation method and navigation system technology, applied in data processing applications, commerce, instruments, etc., can solve problems such as complex search functions, quality and price buyers are confused, and affect the shopping experience of buyers

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 frequently discussed by human beings. 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. With the development and growth of e-commerce platforms, sellers continue to settle in As a result, when buyers purchase products, there are tens of thousands of similar products, and factors such as quality and price can easily make buyers confused
[0004] At the same time, the search function of the current e-commerce website is too complicated, and there are too many recommended spam information. When the buyer enters the product name, a lot of product information that has nothing to do with the buyer's shopping needs will pop up, affecting the buyer's shopping experience.

Method used

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  • E-commerce shopping navigation method based on big data and system thereof
  • E-commerce shopping navigation method based on big data and system thereof
  • E-commerce shopping navigation method based on big data and system thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0060] Such as figure 1 As shown, this embodiment provides a big data-based e-commerce shopping navigation method, including:

[0061] S101: Obtain account information for logging into the current website;

[0062] S102: Obtain the shopping record of the account information, the shopping record includes the product name and the product price corresponding to the product name;

[0063] S103: Analyzing the shopping record, and classifying the product names into product categories according to the usage of the products;

[0064]S104: Establish a price range corresponding to the product category based on the product price, and save the corresponding relationship between the product category and the price range in the database;

[0065] S105: Obtain the shopping requirements input by the user, where the shopping requirements include product names and product uses;

[0066] S106: extract all product information that meets the shopping needs from the database, and the product info...

Embodiment 2

[0076] Such as image 3 As shown, establishing a price range corresponding to a product category based on the product price includes:

[0077] The price range includes at least half of the product prices in the product category;

[0078] respectively calculating the first quantity of product names located outside the price range and the second quantity of product names located within the price range;

[0079] A scaling factor for the first quantity is calculated.

[0080] Such as Figure 4 As shown, the product information output includes:

[0081] Calculate the number of all output product information;

[0082] The third quantity is obtained by the quantity and the proportional coefficient;

[0083] A third quantity of product information outside the price range is randomly extracted for output.

[0084] Specifically, a product category includes multiple product names. Therefore, a price range includes multiple product prices. If the price range includes product prices ...

Embodiment 3

[0087] Such as Figure 5 As shown, the product name included in the product information is in one-to-one correspondence with the product category, including:

[0088] Obtain the background data of the website;

[0089] Establish a consumption level based on product information, and save the consumption level in the database, the consumption level includes the price range;

[0090] Determine whether the product name included in the product information is included in the product category;

[0091] If not, analyze the consumption level corresponding to the account information;

[0092] Extract the product information corresponding to the consumption level and output the product information.

[0093] Specifically, when purchasing a product of a certain product category for the first time, the user's storage unit does not have the data of the product category, and the present invention cannot perform shopping navigation for the user's exclusive price range. The shopping record ...

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Abstract

The invention discloses an e-commerce shopping navigation method based on big data and a system thereof. The method comprises the steps of obtaining account information of logging in a current website; acquiring a shopping record of the account information, wherein the shopping record comprises a product name and a product price corresponding to the product name; analyzing the shopping records, and classifying the product names into product types according to the purposes of the products; establishing a price interval corresponding to the product type based on the product price; acquiring a shopping demand input by a user, wherein the shopping demand comprises a product name and a product purpose; extracting all product information meeting the shopping requirements from a database, whereinthe product information comprises product names and product prices; enabling the product names contained in the product information to be in one-to-one correspondence with the product types, and judging whether the product prices contained in the product information are located in price intervals corresponding to the product types or not; and if yes, outputting the product information.

Description

technical field [0001] The invention relates to the field of big data e-commerce, in particular to a big data-based e-commerce shopping navigation method and system thereof. 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 frequently discussed by human beings. 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. With the development and growth of e-commerce platforms, sellers continue to settle in , As a result, when buyers purchase products, there are thousands of similar products, and factors such as quality and price can easily make buyers confused. [0004] At the same time, the search function of the current e-commerce website is t...

Claims

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Application Information

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