Method and system for extracting online local characteristic products

Abstract

The invention particularly relates to a method and a system for extracting online local characteristic products. According to the method for extracting the online local characteristic products, public data of e-commerce platform commodities and shops are collected, and the collected data are subjected to cleaning processing and standardization processing; extracting keywords of local characteristic products, and establishing a keyword table of the local characteristic products; acquiring local characteristic product names, and extracting characteristic product keywords including geographical keywords and product keywords; screening local characteristic products, marking corresponding characteristic product name labels on the local characteristic products, and storing the local characteristic products into a theme library; the theme library further comprises local characteristic product sales information. According to the method and the system for extracting the online local characteristic products, the keywords of the local characteristic products can be automatically extracted and the local characteristic product database can be established according to the structural characteristics of the basic information of the commodities on the e-commerce platform, so that the management department, the e-commerce platform and the merchant can conveniently evaluate the development condition of the local characteristic products; and a basis is provided for adjusting a commodity marketing strategy.

Description

Technical Field

[0001] The present invention relates to the technical field of e-commerce, and in particular to a method and system for extracting online local specialty products. Background Art

[0002] E-commerce is the business activity of selling goods or providing services through the Internet and other information networks. my country's e-commerce has been deeply integrated into all areas of production and life. In recent years, traditional e-commerce platforms and live e-commerce platforms have flourished, and consumers are more inclined to shop online. Driven by e-commerce, the logistics industry is also developing continuously, and local specialty products are constantly expanding online markets.

[0003] Among online retail products, there are many local specialty products, such as "Snail rice noodle from state A", "navel orange from place B", "wig from place C", "pearl from place E" and other food, gold and silver jewelry and other products related to various aspects of life. The sales of these products on e-commerce platforms are necessary information and decision-making basis for management departments, e-commerce platforms and merchants to evaluate the market size of specialty products and adjust product marketing strategies.

[0004] It is relatively easy to collect sales and price data of online products on a large scale using data collection technology, but it is not possible to directly distinguish local specialty products. There is no unified category for specialty products of various types and in various places on various platforms, and it is impossible to quickly query the sales of local specialty products. How to further identify and extract local specialty products from the collected basic information of goods is a problem that must be solved. At present, there is no complete technical system on the market for large-scale extraction of local specialty product data.

[0005] Based on the above situation, the present invention proposes a method and system for extracting online local specialty products. Summary of the invention

[0006] In order to make up for the defects of the prior art, the present invention provides a simple and efficient method and system for extracting local specialty products online.

[0007] The present invention is achieved through the following technical solutions:

[0008] A method for extracting local specialty products online, characterized in that it comprises the following steps:

[0009] Step S1: collect the public data of products and stores on the e-commerce platform to obtain product names, product origins, store locations and sales information;

[0010] In step S1, crawler technology is used to obtain public data on online retail products on the e-commerce platform, including product name, product brand, product origin, product shipping location, product price, product sales volume, product category, product store location and the company to which the store belongs.

[0011] Step S2: cleaning and standardizing the collected online retail products and store data;

[0012] In the step S2, the collected online retail commodity data is cleaned and standardized according to the custom data standard;

[0013] Among them, data cleaning includes cleaning of abnormal data and duplicate data;

[0014] Standardization includes processing information on the location of product stores, product shipping locations, and product origins, using the latest administrative division codes, and using unified standard categories for product categories.

[0015] In step S2, the standardization process is as follows:

[0016] Step S2.1, pre-process the information of the store location, the place of shipment and the place of origin of the product, separate the basic information, obtain a short sentence containing the address keyword, and remove interference symbols such as spaces, commas, colons and other interference symbols to obtain the specific address, and then split it into province, city and county information;

[0017] The store location of the product is the store business license address obtained based on the basic information of the store to which the product belongs;

[0018] Step S2.2, extract the province, city and county information obtained by splitting, and use the latest administrative division code to standardize it to the latest administrative division;

[0019] Step S2.3: Obtain product category information from each e-commerce platform, combine the featured product types, and extract product categories according to a custom unified standard, including product subcategories and product categories.

[0020] Step S3, extracting keywords of local specialty products and establishing a keyword table of local specialty products; the keyword table of local specialty products includes the name of the local specialty products, the origin of the local specialty products, the product keywords and the category information to which the products belong;

[0021] The local specialty product keyword table includes N product keywords;

[0022] Each local specialty product has at least one product keyword; if the number of product keywords of a local specialty product is M, and M is less than N, then product keywords M+1 to product keywords N of the local specialty product are allowed to be empty.

[0023] Step S4, screen local specialty products, label local specialty products with corresponding specialty product names, and store them in the theme library; the theme library also includes sales information of local specialty products, which is convenient for management departments, e-commerce platforms and merchants to evaluate the development of specialty products and adjust product marketing strategies.

[0024] In step S4, the public data of online retail products on the e-commerce platform and the keyword table of local specialty products are combined to screen local specialty products, and the corresponding specialty product name tags are marked for the products that meet the following conditions at the same time:

[0025] 1) Any of the following addresses, including the place of origin of the product, the place of shipment of the product, the place of registration of the store’s business license, and the location of the store, is the place of origin of the local specialty product;

[0026] 2) The product name also contains all the keywords of the corresponding local specialty products;

[0027] 3) The product category is consistent with the product category in the local specialty product keyword table.

[0028] The subject library also includes the names of local specialty products, commodity names, e-commerce platforms to which they belong, commodity categories, commodity origins, commodity shipping locations, commodity store locations, companies to which the stores belong, commodity sales volumes, and commodity sales revenues.

[0029] A system for extracting online local specialty products, comprising:

[0030] The data collection module is responsible for collecting public data on products and stores on the e-commerce platform to obtain product names, product origins, store locations, and sales information;

[0031] The pre-processing module is responsible for cleaning and standardizing the collected online retail products and store data;

[0032] The keyword extraction module is responsible for extracting keywords of local specialty products and establishing a keyword table of local specialty products; the keyword table of local specialty products includes the name of the local specialty products, the origin of the local specialty products, the product keywords and the category information to which the products belong;

[0033] The local specialty product management module is responsible for screening local specialty products, labeling local specialty products with corresponding specialty product names, and storing them in the theme library; the theme library also includes local specialty product sales information, which is convenient for management departments, e-commerce platforms and merchants to evaluate the development of specialty products and adjust product marketing strategies.

[0034] A computing device, comprising:

[0035] One or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the above methods.

[0036] A readable storage medium, characterized in that: a computer program is stored on the readable storage medium, and the computer program implements the above method when executed by a processor.

[0037] The beneficial effect of the present invention is that the method and system for extracting online local specialty products can automatically extract local specialty product keywords according to the structural characteristics of the basic information of the products on the e-commerce platform, and establish a local specialty product database, which is convenient for management departments, e-commerce platforms and merchants to evaluate the development of local specialty products and provide a basis for adjusting product marketing strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Attached Figure 1 This is a schematic diagram of the method for extracting online local specialty products according to the present invention. DETAILED DESCRIPTION

[0040] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0041] The method for extracting online local specialty products comprises the following steps:

[0042] Step S1: collect the public data of products and stores on the e-commerce platform to obtain product names, product origins, store locations and sales information;

[0043] In step S1, crawler technology is used to obtain public data on online retail products on the e-commerce platform, including product name, product brand, product origin, product shipping location, product price, product sales volume, product category, product store location and the company to which the store belongs.

[0044] Step S2: cleaning and standardizing the collected online retail products and store data;

[0045] In the step S2, the collected online retail commodity data is cleaned and standardized according to the custom data standard;

[0046] Among them, data cleaning includes cleaning of abnormal data and duplicate data;

[0047] Standardization includes processing information on the location of product stores, product shipping locations, and product origins, using the latest administrative division codes, and using unified standard categories for product categories.

[0048] In step S2, the standardization process is as follows:

[0049] Step S2.1, pre-process the information of the store location, the place of shipment and the place of origin of the product, separate the basic information, obtain a short sentence containing the address keyword, and remove interference symbols such as spaces, commas, colons and other interference symbols to obtain the specific address, and then split it into province, city and county information;

[0050] The store location of the product is the store business license address obtained based on the basic information of the store to which the product belongs;

[0051] Step S2.2: Since the platform publishes non-standard addresses, there are abbreviations of provinces, cities and counties or they have not been updated to the latest names, it is necessary to unify the names of provinces, cities and counties, extract the province, city and district information obtained by splitting, and use the latest administrative division code to standardize it to the latest administrative division;

[0052] Step S2.3: Obtain product category information from each e-commerce platform, combine the featured product types, and extract product categories according to a custom unified standard, including product subcategories and product categories.

[0053] Step S3, extracting keywords of local specialty products and establishing a keyword table of local specialty products; the keyword table of local specialty products includes the name of the local specialty products, the origin of the local specialty products, the product keywords and the category information to which the products belong;

[0054] The local specialty product keyword table includes N product keywords;

[0055] Each local specialty product has at least one product keyword; if the number of product keywords of a local specialty product is M, and M is less than N, then product keywords M+1 to product keywords N of the local specialty product are allowed to be empty.

[0056] Table 1 Keyword list of local specialty products (example)

[0057]

[0058] Step S4, screen local specialty products, label local specialty products with corresponding specialty product names, and store them in the theme library; the theme library also includes sales information of local specialty products, which is convenient for management departments, e-commerce platforms and merchants to evaluate the development of specialty products and adjust product marketing strategies.

[0059] In step S4, the public data of online retail products on the e-commerce platform and the keyword table of local specialty products are combined to screen local specialty products, and the corresponding specialty product name tags are marked for the products that meet the following conditions at the same time:

[0060] 1) Any of the following addresses, including the place of origin of the product, the place of shipment of the product, the place of registration of the store’s business license, and the location of the store, is the place of origin of the local specialty product;

[0061] 2) The product name also contains all the keywords of the corresponding local specialty products;

[0062] 3) The product category is consistent with the product category in the local specialty product keyword table.

[0063] The thematic library also includes the names of local specialty products, commodity names, e-commerce platforms, commodity categories, commodity origins, commodity shipping locations, commodity store locations, store-owned companies, commodity sales volumes and commodity sales revenues, forming big data of multi-dimensional indicators, grasping the scale of online retail of local specialty products, etc., to provide guidance for the local development of specialty products.

[0064] The system for extracting local specialty products online includes:

[0065] The data collection module is responsible for collecting public data on products and stores on the e-commerce platform to obtain product names, product origins, store locations, and sales information;

[0066] The pre-processing module is responsible for cleaning and standardizing the collected online retail products and store data;

[0067] The keyword extraction module is responsible for extracting keywords of local specialty products and establishing a keyword table of local specialty products; the keyword table of local specialty products includes the name of the local specialty products, the origin of the local specialty products, the product keywords and the category information to which the products belong;

[0068] The local specialty product management module is responsible for screening local specialty products, labeling local specialty products with corresponding specialty product names, and storing them in the theme library; the theme library also includes local specialty product sales information, which is convenient for management departments, e-commerce platforms and merchants to evaluate the development of specialty products and adjust product marketing strategies.

[0069] The computer-readable storage medium stores one or more programs, wherein the one or more programs include instructions, and when the instructions are executed by a computing device, the computing device performs any one of the above methods.

[0070] The computing device comprises:

[0071] One or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the above methods.

[0072] The embodiment described above is only one specific implementation of the present invention. Common changes and substitutions made by those skilled in the art within the scope of the technical solution of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for extracting local specialty products online, characterized in that: The following steps are involved: Step S1: collect the public data of products and stores on the e-commerce platform to obtain product names, product origins, store locations and sales information; Step S2: cleaning and standardizing the collected online retail products and store data; Step S3, extracting keywords of local specialty products and establishing a keyword table of local specialty products; the keyword table of local specialty products includes the name of the local specialty products, the origin of the local specialty products, the product keywords and the category information to which the products belong; Step S4, screening local specialty products, and marking the local specialty commodities with corresponding specialty product name labels, and storing them in the theme library; the theme library also includes the sales information of local specialty products.

2. The method for extracting online local specialty products according to claim 1, characterized in that: In step S1, crawler technology is used to obtain public data on online retail products on the e-commerce platform, including product name, product brand, product origin, product shipping location, product price, product sales volume, product category, product store location and the company to which the store belongs.

3. The method for extracting online local specialty products according to claim 1, characterized in that: In the step S2, the collected online retail commodity data is cleaned and standardized according to the custom data standard; Among them, data cleaning includes cleaning of abnormal data and duplicate data; Standardization includes processing information on the location of product stores, product shipping locations, and product origins, using the latest administrative division codes, and using unified standard categories for product categories.

4. The method for extracting online local specialty products according to claim 3, characterized in that: In step S2, the standardization process is as follows: Step S2.1, pre-process the information of the store location, the place of shipment and the place of origin of the product, separate the basic information, obtain a short sentence containing the address keyword, remove the interference symbols, obtain the specific address, and then split it into province, city and county information; The store location of the product is the store business license address obtained based on the basic information of the store to which the product belongs; Step S2.2, extract the province, city and county information obtained by splitting, and use the latest administrative division code to standardize it to the latest administrative division; Step S2.3: Obtain product category information from each e-commerce platform, combine the featured product types, and extract product categories according to a custom unified standard, including product subcategories and product categories.

5. The method for extracting online local specialty products according to claim 1, characterized in that: The local specialty product keyword table includes N product keywords; Each local specialty product has at least one product keyword; if the number of product keywords of a local specialty product is M, and M is less than N, then product keywords M+1 to product keywords N of the local specialty product are allowed to be empty.

6. The method for extracting online local specialty products according to claim 5, characterized in that: In step S4, the public data of online retail products on the e-commerce platform and the keyword table of local specialty products are combined to screen local specialty products, and the corresponding specialty product name tags are marked for the products that meet the following conditions at the same time: 1) Any of the following addresses, including the place of origin of the product, the place of shipment of the product, the place of registration of the store’s business license, and the location of the store, is the place of origin of the local specialty product; 2) The product name also contains all the keywords of the corresponding local specialty products; 3) The product category is consistent with the product category in the local specialty product keyword table.

7. The method for extracting online local specialty products according to claim 1, characterized in that: The subject library also includes the names of local specialty products, commodity names, e-commerce platforms to which they belong, commodity categories, commodity origins, commodity shipping locations, commodity store locations, companies to which the stores belong, commodity sales volumes, and commodity sales revenues.

8. A system for extracting online local specialty products, characterized by: include: The data collection module is responsible for collecting public data on products and stores on the e-commerce platform to obtain product names, product origins, store locations, and sales information; The pre-processing module is responsible for cleaning and standardizing the collected online retail products and store data; The keyword extraction module is responsible for extracting keywords of local specialty products and establishing a keyword table of local specialty products; the keyword table of local specialty products includes the name of the local specialty products, the origin of the local specialty products, the product keywords and the category information to which the products belong; The local specialty product management module is responsible for screening local specialty products, labeling local specialty products with corresponding specialty product names, and storing them in the theme library; the theme library also includes local specialty product sales information, which is convenient for management departments, e-commerce platforms and merchants to evaluate the development of specialty products and adjust product marketing strategies.

9. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions which, when executed by a computing device, cause the computing device to perform any one of the methods according to claims 1 to 7.

10. A computing device, characterized in that: include: One or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the methods according to claims 1 to 7.

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