Recommendation method for business scope of enterprise establishment based on industry classification and industry description

Abstract

The present application discloses a method and device for recommending business scopes for business start-ups based on industry classifications and industry descriptions. The method comprises the following steps: S1, pre-processing of historical enterprise registration data to obtain the most matching industry description; S2, statistics and analysis of historical enterprise registration data; S3, generation of main business recommendation plans based on industry descriptions and industry classifications; S4, generation of secondary business recommendation plans based on industry descriptions and industry classifications; S5, generation of business scope recommendation plans based on industry descriptions and industry classifications. The present application can facilitate market entities to recommend possible national economic classifications and related business scope items by only paying attention to individual or enterprise names during registration, thereby reducing confusion and selection difficulties faced by market entities during enterprise registration, overcoming problems such as difficulty in understanding the business and relatively complicated selection process faced by applicants when applying for or changing the business scope, and simplifying the service process.

Description

Technical Field

[0001] The present application relates to the technical field of information processing, and in particular, to a method for recommending business scopes for enterprise establishment based on industry classification and industry description. Background Art

[0002] Market entities in the government services sector, including enterprises, individuals, and unincorporated organizations, have a business scope in their business licenses that describes their primary production and operations and legally defines the scope of their business activities. The business scope, composed of a combination of multiple business items or descriptions, is a standardized textual statement and is of great significance when establishing or changing market entities.

[0003] The traditional business scope of market entities is generated by market entities based on their own business scope, and is selected from thousands of business activities or business scope items based on keyword matching. Because there are many industries involved and there are similarities in the expressions between business scope items, they are usually divided into pre-licensing items, post-licensing items and general items. There are also regional differences, which makes it difficult for people to understand the business when applying for or changing the business scope, and the selection process is relatively complicated, which is not conducive to simplifying the business process. Summary of the Invention

[0004] In response to the above technical problems, this application provides a method for recommending business scope for enterprise establishment based on industry classification and industry description.

[0005] The technical solutions adopted in this application are as follows:

[0006] A method for recommending business scopes for enterprise establishment based on industry classification and industry description, comprising the steps of:

[0007] S1. Preprocessing of historical enterprise registration data: Reading individual and enterprise historical registration data, cleaning and preprocessing the data for subsequent statistical analysis to obtain the most suitable industry description;

[0008] S2. Statistics and analysis of historical enterprise registration data: Based on the industry description field obtained in step S1 and the industry classification field in the original data, perform grouped statistical analysis on the historical registration data and calculate the main business recommendation index and the secondary business recommendation index of the business scope items;

[0009] S3. Generate a main business recommendation plan based on the industry description and industry classification: Based on the main business statistical analysis results of the business scope items obtained in step S2, set an appropriate weight distribution plan to calculate the main business recommendation degree, and form a final main business recommendation plan;

[0010] S4. Generate a recommended plan for concurrently operated businesses based on the industry description and industry classification: Based on the statistical analysis results of the concurrently operated businesses of the business scope items obtained in step S2, set an appropriate weight distribution plan to form a final recommendation result for the concurrently operated businesses of the business scope items;

[0011] S5. Generate a business scope recommendation plan based on the industry description and industry classification: Merge the main business recommendation results determined in step S3 and the concurrent business recommendation results determined in step S4. If the main business recommendation results appear in the concurrent business recommendation results, remove the entry from the concurrent business recommendation results, and finally establish a correspondence table between industry descriptions and business scope recommendation plans.

[0012] Furthermore, the step S1 specifically includes the steps of:

[0013] S11. Missing value processing: read the historical registration data of individuals and enterprises, and delete the data that lacks the name of the business name or individual name;

[0014] S12. Industry Expression Extraction: First, the registered name of the enterprise or individual is segmented to obtain a keyword list. Then, the similarity between the keywords and the words in the previously accumulated industry expression dictionary is calculated to obtain the most matching industry expression. The industry expression refers to the colloquial expression in the registered name of the enterprise;

[0015] S13. Standardize business scope item names: Replace incorrect or abnormal business scope names (old version business scope) with standardized business scope names;

[0016] S14. Extraction of business scope items: Split the business scope description in the enterprise and individual data into a list consisting of multiple business scope items, and store the first business scope item that appears in the business scope separately as the main business.

[0017] Furthermore, the step S2 specifically includes the steps of:

[0018] S21. Analyzing statistical results of business scope items based on industry descriptions: Based on the industry description fields obtained in step S1, statistically analyze the data to calculate the frequency of each business scope item appearing in the main business items, the frequency of all business scope items appearing, and the frequency index of each national economic industry classification;

[0019] S22. Analysis of statistical results of business scope items based on industry classification: Based on the industry classification field in the original data, the data is grouped and counted, and the frequency of each business scope item appearing in the main business items and the frequency index of all business scope items in each group of data are calculated.

[0020] Furthermore, the step S3 specifically includes the steps of:

[0021] S31: Calculation of the recommended degree of the main business of the business scope items: According to the degree of relevance between the main business and the industry description and industry classification, set an appropriate weight distribution scheme and calculate the recommended degree of the main business of each business scope item;

[0022] S32. Determine the recommended results of the business scope main business: Based on the recommendation degree of each business scope item under different industry descriptions obtained in step S31 as the main business, obtain the business scope item with the highest recommendation degree under each industry description as the final main business recommendation result corresponding to the industry description.

[0023] Furthermore, in step S31, the main business recommendation degree of each business scope item is calculated and obtained, specifically including:

[0024] Recommended degree of main business of each business scope item =

[0025] The frequency of main business based on industry description*w1+∑(frequency of occurrence of national economic industry classification*frequency of main business of corresponding industry classification)*w2,

[0026] Among them, w1 and w2 are weights, and the sum of the two is 1.

[0027] Furthermore, the step S4 specifically includes the steps of:

[0028] S41. Calculation of the Concurrent Business Recommendation Degree for Business Scope Items: Based on the degree of relevance between the business scope items and the industry classification and industry description, an appropriate weighting scheme is set to calculate the concurrent business recommendation degree for each business scope item;

[0029] S42. Determine the recommended results of concurrent business items within the business scope: Based on the recommendation degree of each business scope item as a concurrent business under different industry descriptions obtained in step S41, set a threshold to filter the concurrent business recommendation degree of the business scope items, and obtain the top N business scope items with high recommendation degrees as the final concurrent business recommendation results, wherein the top N number of recommended items is determined based on the statistical results of historical data.

[0030] Furthermore, in step S41, the calculation of the concurrent business recommendation degree of each business scope item specifically includes:

[0031] Recommended degree of concurrent business for each business scope item =

[0032] Frequency of concurrent business based on industry description * W1 + ∑ (frequency of occurrence of national economic industry classification * frequency of concurrent business of corresponding industry classification) * W2,

[0033] Where W1 and W2 are weights, and their sum is 1.

[0034] On the other hand, the present application also provides a device for recommending business scopes for business start-ups based on industry classification and industry description, including:

[0035] Data cleaning and preprocessing module, used for preprocessing historical enterprise registration data: reading individual and enterprise historical registration data, cleaning and preprocessing the data for subsequent statistical analysis to obtain the most suitable industry description;

[0036] The data statistics and analysis module is used for statistics and analysis of the company's historical registration data: based on the industry description field obtained in step S1 and the industry classification field in the original data, the historical registration data is grouped and statistically analyzed to calculate the main business recommendation index and the secondary business recommendation index of the business scope items;

[0037] The main business recommendation module is used to generate a main business recommendation plan based on the industry description and industry classification: according to the main business statistical analysis results of the business scope items obtained in step S2, an appropriate weight distribution plan is set to calculate the main business recommendation degree, and a final main business recommendation plan is formed;

[0038] The concurrent business recommendation module is used to generate a concurrent business recommendation scheme based on the industry description and industry classification: according to the statistical analysis results of the concurrent businesses of the business scope items obtained in step S2, an appropriate weight distribution scheme is set to form the final concurrent business recommendation results of the business scope items;

[0039] The business scope recommendation module is used to generate a business scope recommendation plan that combines industry descriptions and industry classifications: the main business recommendation results determined in step S3 and the concurrent business recommendation results determined in step S4 are merged. If the main business recommendation results appear in the concurrent business recommendation results, the entry will be removed from the concurrent business recommendation results, and finally a correspondence table between industry descriptions and business scope recommendation plans will be established.

[0040] On the other hand, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the method for recommending the business scope for starting a business based on industry classification and industry description are implemented.

[0041] On the other hand, the present application also provides a storage medium, which includes a stored program, and when the program is running, controls the device where the storage medium is located to execute the steps of the method for recommending the business scope of an enterprise based on industry classification and industry description.

[0042] Compared with the existing technology, this application has the following beneficial effects:

[0043] The present application provides a method and device for recommending business scopes for business start-ups based on industry classification and industry description. The method includes steps S1, preprocessing of historical enterprise registration data: reading individual and enterprise historical registration data, cleaning and preprocessing the data for subsequent statistical analysis to obtain the most matching industry description; S2, statistics and analysis of historical enterprise registration data: based on the industry description field obtained in step S1 and the industry classification field in the original data, grouping and statistically analyzing the historical registration data, and calculating the main business recommendation degree and the secondary business recommendation degree index of the business scope items; S3, generating a main business recommendation plan based on the industry description and industry classification: generating a main business recommendation plan based on the main business statistical analysis results of the business scope items obtained in step S2 , set a suitable weight distribution scheme to calculate the main business recommendation degree, and form the final main business recommendation scheme; S4, generate the concurrent business recommendation scheme based on the industry description and industry classification: according to the statistical analysis results of the concurrent business of the business scope items obtained in step S2, set a suitable weight distribution scheme to form the final business scope item concurrent business recommendation results; S5, generate the business scope recommendation scheme based on the industry description and industry classification: merge the main business recommendation results determined in step S3 and the concurrent business recommendation results determined in step S4. If the main business recommendation results appear in the concurrent business recommendation results, remove the item from the concurrent business recommendation results, and finally establish a correspondence table between the industry description and the business scope recommendation scheme.

[0044] This application uses natural language processing technology and data analysis related knowledge to mine the relationship between industry descriptions and business scopes from historical data, thereby facilitating the selection of business scopes by market entities. In response to the problem that the business scope involves many industry categories, this application constructs a relationship table between industry descriptions and industry classifications based on historical data, and conducts statistical analysis on the data based on industry descriptions and industry classifications respectively; when recommending the business scope, it considers both the impact of industry descriptions on the selection of business scopes and the correspondence between industry descriptions and industry classifications, designs main business recommendation and concurrent business recommendation indicators, and quickly obtains the final business scope recommendation plan in a quantitative manner. Market entities only need to input the corresponding industry description to obtain the final business scope recommendation plan, including the main business and concurrent business.

[0045] This application can facilitate market entities to register and register, and they only need to pay attention to the individual or enterprise name to recommend possible national economic classifications and related business scope items, reducing the confusion and difficulty in choosing when market entities register their enterprises. It overcomes the problems of business understanding difficulties and relatively complicated selection process when applying for or changing the business scope, and simplifies the service process.

[0046] In addition to the above-described purposes, features and advantages, the present application has other purposes, features and advantages. The present application will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0048] Figure 1 It is a flowchart of a method for recommending business scope for starting a business based on industry classification and industry description in a preferred embodiment of the present application.

[0049] Figure 2 It is a schematic flow chart of the sub-steps of step S1 of the preferred embodiment of the present application.

[0050] Figure 3 It is a schematic flow chart of the sub-steps of step S2 of the preferred embodiment of the present application.

[0051] Figure 4 This is a schematic flow chart of the sub-steps of step S3 of the preferred embodiment of the present application.

[0052] Figure 5 It is a schematic flow chart of the sub-steps of step S4 of the preferred embodiment of the present application.

[0053] Figure 6 This is a schematic diagram of a module of a business scope recommendation device for starting a business based on industry classification and industry description in a preferred embodiment of the present application.

[0054] Figure 7 It is a schematic block diagram of an electronic device entity of a preferred embodiment of the present application.

[0055] Figure 8 It is a diagram of the internal structure of a computer device according to a preferred embodiment of the present application. DETAILED DESCRIPTION

[0056] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0057] Reference Figure 1 In one embodiment of the present invention, a method for recommending business scopes for enterprises based on industry classification and industry description is provided, which generates main business recommendation plans and concurrent business recommendation plans based on individual and enterprise registration data from July 26, 2021 to July 26, 2022 in XX Province. Figure 1The process shown in the figure first pre-processes the historical data, mainly including missing value processing, industry description extraction, business scope standardization, and business scope item extraction. Then, the processed structured data is grouped and statistically analyzed by industry description and industry classification. Finally, the statistical results of industry description and industry classification are combined to generate the final main business recommendation plan and concurrent business recommendation plan. The specific steps include:

[0058] S1. Preprocessing of historical enterprise registration data: Reading individual and enterprise historical registration data, cleaning and preprocessing the data for subsequent statistical analysis to obtain the most suitable industry description;

[0059] S2. Statistics and analysis of historical enterprise registration data: Based on the industry description field obtained in step S1 and the industry classification field in the original data, perform grouped statistical analysis on the historical registration data and calculate the main business recommendation index and the secondary business recommendation index of the business scope items;

[0060] S3. Generate a main business recommendation plan based on the industry description and industry classification: Based on the main business statistical analysis results of the business scope items obtained in step S2, set an appropriate weight distribution plan to calculate the main business recommendation degree, and form a final main business recommendation plan;

[0061] S4. Generate a recommended plan for concurrently operated businesses based on the industry description and industry classification: Based on the statistical analysis results of the concurrently operated businesses of the business scope items obtained in step S2, set an appropriate weight distribution plan to form a final recommendation result for the concurrently operated businesses of the business scope items;

[0062] S5. Generate a business scope recommendation plan based on the industry description and industry classification: Merge the main business recommendation results determined in step S3 and the concurrent business recommendation results determined in step S4. If the main business recommendation results appear in the concurrent business recommendation results, remove the entry from the concurrent business recommendation results, and finally establish a correspondence table between industry descriptions and business scope recommendation plans.

[0063] This embodiment uses natural language processing technology and data analysis-related knowledge to mine the relationship between industry descriptions and business scopes from historical data, thereby facilitating the selection of business scopes by market entities. In response to the problem that the business scope involves many industry categories, this embodiment constructs a relationship table between industry descriptions and industry classifications based on historical data, and performs statistical analysis on the data based on industry descriptions and industry classifications respectively; when recommending the business scope, it considers both the impact of industry descriptions on the selection of business scopes and the correspondence between industry descriptions and industry classifications, designs the main business recommendation degree and the secondary business recommendation degree indicators, and quickly obtains the final business scope recommendation plan in a quantitative manner. Market entities only need to input the corresponding industry description to obtain the final business scope recommendation plan, including the main business and secondary business.

[0064] This embodiment can facilitate market entities to register and register, and they only need to pay attention to the individual or enterprise name to recommend possible national economic classifications and related business scope items, thereby reducing the confusion and difficulty in choosing when market entities register their enterprises, overcoming the problems of business understanding difficulties and relatively complicated selection process when applying for or changing the business scope, and simplifying the service process.

[0065] Preferably, if Figure 2 As shown, the step S1 specifically includes the following steps:

[0066] S11. Missing value processing: Read the historical registration data of individuals and enterprises. In this embodiment, the individual and enterprise registration data of XX Province from July 26, 2021 to July 26, 2022 are read. There are 1,191,164 individual business registration data and 356,139 enterprise registration data. The data that lacks the business name, that is, the business name or individual name is deleted. In this embodiment, there are 212,984 data that lack the business name in the individual business registration data, and no data that lacks the business name is found in the enterprise registration data. Therefore, the remaining data is 1,334,319 after processing.

[0067] S12. Industry expression extraction: First, the registered name of the enterprise or individual is segmented to obtain a keyword list. During the segmentation process, the registered name of the individual or enterprise is segmented using natural language processing technology to obtain a keyword list. For example, the segmentation result of Hunan Kechuang Information Technology Co., Ltd. is ["Hunan", "Kechuang", "Information Technology", "Co., Ltd."]; then, by calculating the similarity between the keywords and the words in the industry expression dictionary table accumulated in the early stage, the most matching industry expression is obtained. The industry expression refers to the colloquial expression in the registered name of the enterprise. For example, the industry expression extracted from the enterprise name mentioned in this embodiment is "Information Technology";

[0068] S13. Standardize business scope entry names: Replace incorrect or abnormal business scope names (old version business scope) with standardized business scope names. For example, in some individual or corporate registration data, the business scope name is "clothing retail", but the corresponding expression in the latest business scope coding and name specifications should be "clothing and accessories retail". This part mainly standardizes the business scope expression in the data based on the business scope coding and name specifications;

[0069] S14. Extraction of business scope items: Split the business scope expressions in enterprise and individual data into a list consisting of multiple business scope items, and store the first business scope item that appears in the business scope separately as the main business. For example, for the business scope expression in the original data "General projects: professional design services; graphic design; landscaping project construction; engineering management services (except for projects that require approval according to law, business activities can be carried out independently in accordance with the law with a business license). (Projects that require approval according to law can only carry out business activities after approval by relevant departments)", after processing this paragraph of text, the main business is "professional design services", and the concurrent businesses are: ["graphic design", "landscape construction", "engineering management services"].

[0070] Preferably, if Figure 3 As shown, the step S2 specifically includes the following steps:

[0071] S21. Analysis of statistical results of business scope items based on industry descriptions: Based on the industry description fields obtained in step S1, statistics are performed on the data to calculate the frequency of each business scope item appearing in the main business item, the frequency of all business scope items, and the frequency index of each national economic industry classification. For example, the industry description "fried chicken snacks" appears 23 times, and the corresponding national economic industry classification frequency statistics are [(6291, 'snack services', '96%'), (6220, 'fast food services', '4%')], among which the frequency distribution of main business is: [('H2004', 'small restaurants', 10, '43%'), ('H2002', 'catering services', 7, '30%'), ('H2003', 'small restaurants, small snacks, and small food workshops', 4, '17%'), ('F1041', 'food sales ... ,2,'10%')], while the frequency distribution of concurrently operated businesses is: [('H2004','Small restaurants','5%'),('F1041','Food sales','30%'),('H2001','Takeaway delivery service','39%'),('H2002','Catering service','9%'),('H2003','Small restaurants, small snacks, and small food workshops','9%' ),('F1040','Food sales (only pre-packaged food)','17%'),('F1201','Health food (pre-packaged) sales','13%'),('F3002','Food Internet sales','4%'),('F3235','Food Internet sales (only pre-packaged food)','4%'),('F2065','Alcohol business','4%')];

[0072] S22. Analysis of statistical results of business scope items based on industry classification: Based on the industry classification field in the original data, the data is grouped and counted, and the frequency of each business scope item appearing in the main business items and the frequency index of all business scope items in each group of data are calculated.

[0073] Preferably, if Figure 4 As shown, the step S3 specifically includes the following steps:

[0074] S31: Calculation of the recommended degree of the main business of the business scope items: According to the degree of relevance between the main business and the industry description and industry classification, set an appropriate weight distribution scheme and calculate the recommended degree of the main business of each business scope item:

[0075] Recommended degree of main business of each business scope item =

[0076] The frequency of main business based on industry description*w1+∑(frequency of occurrence of national economic industry classification*frequency of main business of corresponding industry classification)*w2,

[0077] Among them, w1 and w2 are weights, and the sum of the two is 1.

[0078] For example, the main business recommendation degree of the business scope item "Small Restaurants" when the industry description is "Fried Chicken Snacks" is (20% * 96% + 10% * 4%) * 0.2 + 43% * 0.8 = 0.3832. Here, the weight assigned to the industry description main business is 0.8, and the weight assigned to the industry classification main business statistics is 0.2;

[0079] S32. Determine the recommended results of the main business of the business scope: According to the recommendation degree of each business scope item as the main business under the different industry descriptions obtained in step S31, obtain the business scope item with the highest recommendation degree under each industry description as the final main business recommendation result corresponding to the industry description. For example, the main business recommendation list corresponding to the industry description "fried chicken snacks" is: [('H2004','Small catering',0.3832),('H2002','Catering services',0.3012),('H2003','Small catering, small snacks, and small food workshops',0.1656),('F1041','Food sales',0.10232)], so the final recommended main business is "Small catering".

[0080] Preferably, if Figure 5 As shown, the step S4 specifically includes the following steps:

[0081] S41. Calculation of the concurrent business recommendation degree for business scope items: Based on the degree of relevance between the business scope items and the industry classification and industry description, set an appropriate weight distribution scheme and calculate the concurrent business recommendation degree for each business scope item:

[0082] Recommended degree of concurrent business for each business scope item =

[0083] Frequency of concurrent business based on industry description * W1 + ∑ (frequency of occurrence of national economic industry classification * frequency of concurrent business of corresponding industry classification) * W2,

[0084] Where W1 and W2 are weights, the sum of the two is 1,

[0085] For example, the recommended degree of a concurrent business for the business scope entry "Small Restaurants" when the industry description is "Fried Chicken Snacks" is (40% * 96% + 35% * 4%) * 0.2 + 5% * 0.8 = 0.1196. Here, the weight assigned to the main business of the industry description is 0.8, and the weight assigned to the statistical results of the main business of the industry classification is 0.2;

[0086] S42. Determine the recommended results of concurrent business items within the scope of business: Based on the recommendation degree of each business item as a concurrent business under the different industry descriptions obtained in step S41, set a threshold to filter the concurrent business recommendation degree of the business item, and obtain the top N business items with high recommendation degrees as the final concurrent business recommendation results. The top N number of recommended items is determined based on the statistical results of historical data. For example, after statistical analysis of historical data, it is found that the number of business items included in the concurrent business of the catering industry is generally 5. Therefore, for the industry description of the catering industry, this embodiment selects n=5.

[0087] like Figure 6 As shown, another preferred embodiment of the present application discloses a device for recommending business scopes for business start-ups based on industry classification and industry description, comprising:

[0088] Data cleaning and preprocessing module, used for preprocessing historical enterprise registration data: reading individual and enterprise historical registration data, cleaning and preprocessing the data for subsequent statistical analysis to obtain the most suitable industry description;

[0089] The data statistics and analysis module is used for statistics and analysis of the company's historical registration data: based on the industry description field obtained in step S1 and the industry classification field in the original data, the historical registration data is grouped and statistically analyzed to calculate the main business recommendation index and the secondary business recommendation index of the business scope items;

[0090] The main business recommendation module is used to generate a main business recommendation plan based on the industry description and industry classification: according to the main business statistical analysis results of the business scope items obtained in step S2, an appropriate weight distribution plan is set to calculate the main business recommendation degree, and a final main business recommendation plan is formed;

[0091] The concurrent business recommendation module is used to generate a concurrent business recommendation scheme based on the industry description and industry classification: according to the statistical analysis results of the concurrent businesses of the business scope items obtained in step S2, an appropriate weight distribution scheme is set to form the final concurrent business recommendation results of the business scope items;

[0092] The business scope recommendation module is used to generate a business scope recommendation plan that combines industry descriptions and industry classifications: the main business recommendation results determined in step S3 and the concurrent business recommendation results determined in step S4 are merged. If the main business recommendation results appear in the concurrent business recommendation results, the entry will be removed from the concurrent business recommendation results, and finally a correspondence table between industry descriptions and business scope recommendation plans will be established.

[0093] like Figure 7As shown, a preferred embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for recommending the business scope of an enterprise based on industry classification and industry description in the above-mentioned embodiment are implemented.

[0094] like Figure 8 As shown, the preferred embodiment of the present application further provides a computer device, which can be a terminal or a liveness detection server, and its internal structure diagram can be as shown in FIG. Figure 8 As shown. The computer device includes a processor, memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with other external computer devices via a network connection. When the computer program is executed by the processor, the steps of the above-mentioned method for recommending the business scope of an enterprise based on industry classification and industry description are implemented.

[0095] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0096] A preferred embodiment of the present application further provides a storage medium, which includes a stored program, and when the program is run, controls the device where the storage medium is located to execute the steps of the method for recommending business scope for enterprise establishment based on industry classification and industry description in the above embodiment.

[0097] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0098] If the functions described in the method of this embodiment are implemented in the form of a software functional unit and sold or used as an independent product, they can be stored in a storage medium readable by one or more computing devices. Based on this understanding, the part of the embodiment of the present application that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computing device (which can be a personal computer, server, mobile computing device or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

[0099] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal translation scripting language JavaScript, etc.

[0100] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0101] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0102] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0103] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0104] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for recommending business scopes for business start-ups based on industry classification and industry description, characterized in that: Including steps: S1. Preprocessing of historical enterprise registration data: Reading individual and enterprise historical registration data, cleaning and preprocessing the data for subsequent statistical analysis to obtain the most suitable industry description; S2. Statistics and analysis of historical enterprise registration data: Based on the industry description field obtained in step S1 and the industry classification field in the original data, perform grouped statistical analysis on the historical registration data and calculate the main business recommendation index and the secondary business recommendation index of the business scope items; S3. Generate a main business recommendation plan based on the industry description and industry classification: Based on the main business statistical analysis results of the business scope items obtained in step S2, set an appropriate weight distribution plan to calculate the main business recommendation degree, and form a final main business recommendation plan; S4. Generate a recommended plan for concurrently operated businesses based on the industry description and industry classification: Based on the statistical analysis results of the concurrently operated businesses of the business scope items obtained in step S2, set an appropriate weight distribution plan to form a final recommendation result for the concurrently operated businesses of the business scope items; S5. Generate a business scope recommendation plan based on the industry description and industry classification: Merge the main business recommendation results determined in step S3 and the concurrent business recommendation results determined in step S4. If the main business recommendation results appear in the concurrent business recommendation results, remove the entry from the concurrent business recommendation results, and finally establish a correspondence table between industry descriptions and business scope recommendation plans.

2. The method for recommending business scopes for starting a business based on industry classification and industry description according to claim 1, characterized in that: The step S1 specifically includes the following steps: S11. Missing value processing: read the historical registration data of individuals and enterprises, and delete the data that lacks the name of the business name or individual name; S12. Industry Expression Extraction: First, the registered name of the enterprise or individual is segmented to obtain a keyword list. Then, the similarity between the keywords and the words in the previously accumulated industry expression dictionary is calculated to obtain the most matching industry expression. The industry expression refers to the colloquial expression in the registered name of the enterprise; S13. Standardize business scope item names: Replace incorrect or abnormal business scope names with standardized business scope names; S14. Extraction of business scope items: Split the business scope description in the enterprise and individual data into a list consisting of multiple business scope items, and store the first business scope item that appears in the business scope separately as the main business.

3. The method for recommending business scopes for starting a business based on industry classification and industry description according to claim 1, characterized in that: The step S2 specifically includes the following steps: S21. Analyzing statistical results of business scope items based on industry descriptions: Based on the industry description fields obtained in step S1, statistically analyze the data to calculate the frequency of each business scope item appearing in the main business items, the frequency of all business scope items appearing, and the frequency index of each national economic industry classification; S22. Analysis of statistical results of business scope items based on industry classification: Based on the industry classification field in the original data, the data is grouped and counted, and the frequency of each business scope item appearing in the main business items and the frequency index of all business scope items in each group of data are calculated.

4. The method for recommending business scopes for starting a business based on industry classification and industry description according to claim 1, characterized in that: The step S3 specifically includes the following steps: S31: Calculation of the recommended degree of the main business of the business scope items: According to the degree of relevance between the main business and the industry description and industry classification, set an appropriate weight distribution scheme and calculate the recommended degree of the main business of each business scope item; S32. Determine the recommended results of the business scope main business: Based on the recommendation degree of each business scope item under different industry descriptions obtained in step S31 as the main business, obtain the business scope item with the highest recommendation degree under each industry description as the final main business recommendation result corresponding to the industry description.

5. The method for recommending business scopes for starting a business based on industry classification and industry description according to claim 4 is characterized in that: In step S31, the main business recommendation degree of each business scope item is calculated and obtained, specifically including: Recommended degree of main business of each business scope item = The frequency of main business based on industry description*w1+∑(frequency of occurrence of national economic industry classification*frequency of main business of corresponding industry classification)*w2, Among them, w1 and w2 are weights, and the sum of the two is 1.

6. The method for recommending business scopes for starting a business based on industry classification and industry description according to claim 1, characterized in that: The step S4 specifically includes the following steps: S41. Calculation of the Concurrent Business Recommendation Degree for Business Scope Items: Based on the degree of relevance between the business scope items and the industry classification and industry description, an appropriate weighting scheme is set to calculate the concurrent business recommendation degree for each business scope item; S42. Determine the recommended results of concurrent business items within the business scope: Based on the recommendation degree of each business scope item as a concurrent business under different industry descriptions obtained in step S41, set a threshold to filter the concurrent business recommendation degree of the business scope items, and obtain the top N business scope items with high recommendation degrees as the final concurrent business recommendation results, wherein the top N number of recommended items is determined based on the statistical results of historical data.

7. The method for recommending business scopes for starting a business based on industry classification and industry description according to claim 6, characterized in that: In step S41, the calculation of the concurrent business recommendation degree of each business scope item specifically includes: Recommended degree of concurrent business for each business scope item = Frequency of concurrent business based on industry description * W1 + ∑ (frequency of occurrence of national economic industry classification * frequency of concurrent business of corresponding industry classification) * W2, Where W1 and W2 are weights, and their sum is 1.

8. A device for recommending business scopes for business start-ups based on industry classification and industry description, characterized in that: include: Data cleaning and preprocessing module, used for preprocessing historical enterprise registration data: reading individual and enterprise historical registration data, cleaning and preprocessing the data for subsequent statistical analysis to obtain the most suitable industry description; The data statistics and analysis module is used for statistics and analysis of the company's historical registration data: based on the industry description field obtained in step S1 and the industry classification field in the original data, the historical registration data is grouped and statistically analyzed to calculate the main business recommendation index and the secondary business recommendation index of the business scope items; The main business recommendation module is used to generate a main business recommendation plan based on the industry description and industry classification: according to the main business statistical analysis results of the business scope items obtained in step S2, an appropriate weight distribution plan is set to calculate the main business recommendation degree, and a final main business recommendation plan is formed; The concurrent business recommendation module is used to generate a concurrent business recommendation scheme based on the industry description and industry classification: according to the statistical analysis results of the concurrent businesses of the business scope items obtained in step S2, an appropriate weight distribution scheme is set to form the final concurrent business recommendation results of the business scope items; The business scope recommendation module is used to generate a business scope recommendation plan that combines industry descriptions and industry classifications: the main business recommendation results determined in step S3 and the concurrent business recommendation results determined in step S4 are merged. If the main business recommendation results appear in the concurrent business recommendation results, the entry will be removed from the concurrent business recommendation results, and finally a correspondence table between industry descriptions and business scope recommendation plans will be established.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method for recommending business scope for starting a business based on industry classification and industry description as described in any one of claims 1 to 7 are implemented.

10. A storage medium comprising a stored program, characterized in that: When the program is running, the device where the storage medium is located is controlled to execute the steps of the method for recommending business scope for starting a business based on industry classification and industry description as described in any one of claims 1 to 7.

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