A system and method for evaluating the qualifications of a business

Abstract

The present application relates to the technical field of enterprise management, in particular to an enterprise qualification evaluation system and method. The enterprise qualification evaluation system comprises: a file interpretation module for extracting relevant files according to the evaluation type and interpreting the relevant files to obtain file information related to the evaluation of enterprise qualification. An enterprise information acquisition module is used to collect relevant information of the enterprise and obtain enterprise qualification information. An enterprise information comparison module is used to determine whether the enterprise qualification information item in the enterprise qualification information exists. The enterprise qualification information item is compared with the data standard, and it is determined whether the enterprise qualification information item meets the data standard. An evaluation analysis module is used to calculate the evaluation value of each project directory and the total evaluation value of the evaluation type. The present application can automatically extract relevant files and relevant information of the enterprise, and then compare them. It can quickly and automatically locate the uncollected and unqualified enterprise qualification information items.

Description

Technical Field

[0001] This invention relates to the field of enterprise management technology, specifically to an enterprise qualification evaluation system and method. Background Technology

[0002] Enterprise qualifications refer to licenses, certifications, or certificates that an enterprise holds in legal, financial, management, and technical fields. They are key indicators for measuring an enterprise's capabilities and credibility. Obtaining and maintaining enterprise qualifications plays a crucial role in enhancing competitiveness, attracting customers and partners, and securing preferential policies. Here are some common types of enterprise qualifications: 1. Business License: Proof of legal registration and operation, issued by the State Administration for Industry and Commerce. 2. Tax Registration Certificate: Obtained by the tax bureau after legally registering for tax purposes and obtaining a tax registration number. 3. Organization Code Certificate: A unique identification code set up by the State Administration for Technical Supervision for public safety and management needs. 4. Trademark Registration Certificate: Proof of independent intellectual property rights, issued by the State Administration for Industry and Commerce. 5. Patent Certificate: A certificate of technological achievements with independent intellectual property rights, issued by the State Intellectual Property Office. Evaluating and improving enterprise qualifications requires enterprises to focus on cultivating their own strengths, continuously improving the quality of their products and services, perfecting company management and system construction, and establishing a good corporate image and reputation.

[0003] When companies conduct policy qualification evaluations, the efficiency of on-site communication by sales representatives is low, the application conditions and policy requirements vary for each project, timeframes are limited, there are many offline steps, technical requirements, and long communication cycles with high costs. As a result, the timeliness and success rate of project applications cannot be guaranteed. If a project is missed, it will have to wait another year, and there is no guarantee that the project will continue to receive relevant policy support next year. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides an enterprise qualification evaluation system for rating enterprise qualifications and providing targeted supplementation to enterprise qualification materials. The enterprise qualification evaluation system may include:

[0005] The document interpretation module is used to extract relevant documents based on the evaluation type and interpret these documents to obtain information related to the evaluated company's qualifications. This information includes a project directory and corresponding data standards. These relevant documents form the basis for our evaluation of company qualifications, defining the category, direction, content, and standards of our evaluation. Generally, these documents can be obtained by linking to the website where the relevant documents are published or through a dedicated section on that website.

[0006] The enterprise information acquisition module is used to collect relevant information about enterprises and obtain their qualification information. Enterprise qualification information is the fundamental document for evaluating an enterprise's qualifications. It can include a project directory and individual enterprise qualification information entries. These entries correspond to data standards; the data standards are derived from relevant documents, while the enterprise qualification information entries are derived from the enterprise's relevant information. For the same project directory, both the data standards and the enterprise qualification information entries describe that directory. The data standards are the criteria for evaluating the enterprise qualification information entries. Relevant enterprise information can be obtained from the enterprise's historical background data. This requires collecting historical information about the enterprise and predicting its future development.

[0007] The enterprise information comparison module is used to determine if there are any empty enterprise qualification information entries in the enterprise qualification information. If so, a level one alert signal is sent; otherwise, no alert signal is sent. In actual operation, the documents related to enterprise qualification evaluation include a project directory and corresponding data standards. The enterprise qualification information contains a project directory and corresponding enterprise qualification information entries, and they are all one-to-one. If the enterprise qualification information entry corresponding to a project directory is empty, it means that no information has been collected for that project directory, and a level one alert signal needs to be sent. Through real-time alerts, the level one alert signal includes empty project directories. The module compares the enterprise qualification information entries with the data standards and determines whether the enterprise qualification information entries in the same project directory meet the data standards. If they do, no alert signal is sent; otherwise, a level two alert signal is sent. The level two alert signal includes project directories that do not meet the data standards.

[0008] The evaluation and analysis module is used to calculate the evaluation value q for each project directory. l And the total evaluation value F for this evaluation type, where l is the item catalog number for this evaluation type. The evaluation values ​​for each item catalog here can be calculated through numerical comparison or keyword overlap.

[0009] A preferred method for obtaining document information related to enterprise qualifications may include: scanning relevant documents to obtain textual data; comparing the textual data with a pre-set keyword database related to qualification information to obtain qualification keywords; and then obtaining the corresponding project directory and data standards based on preset related keywords. The project directory and data standards together constitute the document information related to the enterprise qualifications.

[0010] Preferred methods for obtaining enterprise qualification information may include: online data retrieval, extraction of information from paper documents, on-site questioning of staff, and / or manual input. One method can be used, or multiple methods can be combined. Using only one method can lead to information delays or excessive workload; therefore, multiple methods are generally used in combination, with priority given to information from the same category.

[0011] Preferred method for web data retrieval may include: obtaining web page information data, which may be information content obtained directly from a web page, then extracting key information groups from the web page information data to obtain enterprise qualification information bars, and then arranging and combining the enterprise qualification information bars according to the preset key information groups to form the required enterprise qualification information.

[0012] Preferred options include: preset key information groups may include: project directory and corresponding keyword groups, information coverage, extraction method of enterprise qualification information bars, and combination method of enterprise qualification information bars, etc.

[0013] Preferred methods for extracting information from paper documents include: scanning paper documents and converting them into electronic data; the paper documents are typically tabular materials. Methods for obtaining electronic data include: scanning the paper document to obtain a scanned image; embedding the scanned image into a preset planar coordinate system; obtaining the grayscale value G of each coordinate point; and setting a standard grayscale value difference ΔG between two adjacent coordinate points to be greater than a preset standard grayscale value difference ΔG. 标 The midpoint of the nearest coordinates is used as the dividing point, and the nearest coordinates are generally 2-50 pixels. The standard grayscale difference ΔG 标 The determination can be based on the image's clarity and the difference between the font depth pixels and the background pixels. Adjacent boundary points are connected sequentially to form a boundary line. Then, points are selected along the boundary line at a preset density ρ to obtain frame points. Finally, the straightness Sn of the boundary line is calculated. I Then determine the straightness Sn I Is it greater than a preset straightness standard Sn? 标 If yes, calculate I+1; otherwise, determine if I is greater than a pre-set standard width frame point count I. 标 If not, the boundary line is determined to be a frame line and discarded; if it is, the boundary line is defined as a frame line, and the area separated by each frame line is defined as the information coverage area.

[0014] Preferably: the number of standard width frame points Where A is the minimum width of the table, and ρ is the preset density, which can generally be calculated based on the number of pixels.

[0015] Preferred: Enterprise qualification information includes historical data and predictive data, with predictive data being operating revenue (O). j Where j is the year number, and its value range is j = 1, 2, ..., J; generally, three years of existing data are needed. j = 1 basically represents the annual operating revenue of the past three years, while O4 represents the current year's data. This provides a basis for predicting operating revenue. The value of J is generally 6, but this is only a general case and does not exclude other possibilities, which will not be elaborated here. The aforementioned operating revenue... Where k is the number of each business transaction of the enterprise, K is the total number of business transactions of the enterprise, and k = 1, 2, ..., K; k It represents the annual operating revenue of the business segment numbered k.

[0016] Preferred: Annual operating revenue k The forecasting method may include: constructing a revenue curve for the year j and an annual revenue curve. The annual revenue curve has the horizontal axis representing the time points within the year and the vertical axis representing the revenue amount. This involves embedding the revenue at each time point of the year into the coordinate system to obtain individual revenue points, and then connecting these points sequentially to obtain the annual revenue curve. Similarly, the annual revenue curve has the horizontal axis representing the year and the vertical axis representing the revenue amount. This involves embedding the revenue at each time point of the year into the coordinate system to obtain individual revenue points, and then connecting these points sequentially to obtain the annual revenue curve. The year-on-year growth rate Yg for each year is then calculated. j and month-on-month growth rate Mg m Year-on-year growth rate Yg j The slope of the revenue curve at each annual time point, and the year-on-year growth rate Mg m Let Y be the slope of the revenue curve at time point m within the year. Then, when j = T, T represents the current year number, and Y represents the revenue at time point m within the current year. j,m =ε Y Y j-1,m (1+Yg j )+ε M Y j,m-1 (1+Mg m ), where m is the time unit number within year j, preferably in month format, Y j，m It is the operating revenue for the m-th time unit in year j, ε Y As a year-on-year weighting, ε M The weighting is based on year-on-year changes, and its value can be determined according to the impact of changes within the year or year. ε Y +ε M=1, and its value can be between 0.2 and 0.8, which will not be elaborated here. This allows us to fit and obtain the current year's operating revenue curve, and then, based on Y... j+s =ε Y Y j+s-1,m (1+Yg j+s-1 ), where s is a natural number. Fit the revenue curves for subsequent years. Then integrate the revenue curves for each year to obtain the revenue o. k .

[0017] Preferably, the time point coordinate unit can be month, ten-day period, week, or day, with month being the most suitable.

[0018] Preferred: Straightness of the dividing line In the formula, i is the number of the frame point on the same dividing line, and g i The slope of the frame point numbered i is represented by g; i is the average slope of the n frame points preceding frame i. When the number is less than n, the maximum value is used. The value of n can be between 3 and 10, but other values ​​are not excluded. I is the total number of frame points currently evaluated on the same boundary line. i = 1, 2, ..., I; α is the device parameter factor, the specific value of which is related to the camera's capabilities or can be obtained through settings. Generally, the higher the resolution of the camera, the smaller the device parameter factor. Without considering camera differences, the device parameter factor can be set to 1.

[0019] Preferred: Whether the enterprise qualification information meets the data standards is determined by comparing numerical values ​​or keyword overlap.

[0020] The preferred method for determining keyword overlap is to determine whether the number of keywords in the enterprise qualification information section that overlap with the data standard is equal to the number of keywords in the data standard. If so, the enterprise qualification information section is deemed to meet the data standard; otherwise, it is deemed not to meet the data standard.

[0021] Preferred approach: If a company's qualification information does not meet the data standards, a general reminder will be given, and the instances of non-compliance will be highlighted with a specific color. If all company qualification information meets the data standards, the corresponding positions on the display page will be displayed in a normal color.

[0022] Preferred methods for obtaining evaluation scores may include: even if an evaluation score is obtained... Where A l V represents the actual value corresponding to the enterprise qualification information bar. l This refers to the standard numerical value in the data standard. Then, the evaluation value q corresponding to its level is determined based on the evaluation score. l This method allows for a more intuitive and clear understanding of the status of each project directory.

[0023] Preferred: The overall evaluation value for this evaluation type Where l is the item number of the evaluation type catalog, L is the total number of items in the evaluation type catalog, l = 1, 2, ..., L; W l It is the weight of the project directory with the number l.

[0024] This invention also provides a method for evaluating enterprise qualifications, comprising the following steps:

[0025] S1. Extract relevant documents based on the evaluation type, and interpret these documents to obtain information related to the enterprise's qualifications. This information includes a project directory and corresponding data standards.

[0026] S2. Collect relevant information about the company and obtain its qualification information.

[0027] S3. Determine if there are any empty enterprise qualification information bars in the enterprise qualification information. If so, send a level 1 reminder signal; otherwise, do not send a reminder signal.

[0028] S4. Compare the enterprise qualification information bar with the data standard, and determine whether the enterprise qualification information bar in the same project directory meets the data standard. If it does, do not send a reminder signal; otherwise, send a secondary reminder signal.

[0029] The technical effects and advantages of this invention are as follows: This invention can automatically extract relevant information from related documents and enterprises, and then compare it to quickly locate any missing or unqualified enterprise qualification information, avoiding multiple supplementation and verification by staff, while ensuring the accuracy of the information data. The generated report can evaluate the evaluation type both individually and overall, providing a rapid understanding from both micro and macro perspectives. Attached Figure Description

[0030] Figure 1 This is a structural block diagram of an enterprise qualification evaluation system proposed in this invention.

[0031] Figure 2 This is a flowchart illustrating a method for obtaining document information related to enterprise qualifications in an enterprise qualification evaluation system proposed in this invention.

[0032] Figure 3 This is a flowchart of a method for network data retrieval in an enterprise qualification evaluation system proposed in this invention.

[0033] Figure 4 This is a flowchart of a method for obtaining electronic information data in an enterprise qualification evaluation system proposed in this invention.

[0034] Figure 5 This is a flowchart of a method for evaluating enterprise qualifications proposed in this invention. Detailed Implementation

[0035] Embodiments of this disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are used only to explain this disclosure, and should not be construed as limiting this disclosure. Rather, embodiments of this disclosure include all variations, modifications, and equivalents falling within the spirit and scope of the appended claims.

[0036] Example 1

[0037] refer to Figure 1 This embodiment proposes an enterprise qualification evaluation system for rating enterprise qualifications and supplementing enterprise qualification materials accordingly. The enterprise qualification evaluation system may include:

[0038] The document interpretation module is used to extract relevant documents based on the evaluation type and interpret these documents to obtain information related to the evaluated enterprise's qualifications. Evaluation types can include enterprise self-evaluation, high-tech enterprises, specialized and innovative enterprises, provincial and municipal enterprise technology centers, provincial and municipal enterprise engineering technology research centers, and small and medium-sized enterprises. Each evaluation type has its own defined project directory. The document information related to the evaluated enterprise's qualifications includes the project directory and corresponding data standards. These relevant documents are the foundational documents we need to refer to and rely on when evaluating enterprise qualifications; they define the category, direction, content, and standards of our evaluation. Generally, these documents can be obtained by linking to the website where the relevant documents are published or through a dedicated section of the website via the document interpretation module; details will not be elaborated here. (Reference) Figure 2Methods for obtaining document information related to enterprise qualification evaluation can include: scanning relevant documents to obtain textual data. We can pre-set a keyword database related to qualification information, then compare the textual data with this database to identify qualification keywords. Based on pre-defined related keywords, we can obtain the corresponding project directory and data standards. The project directory and data standards together constitute the document information related to enterprise qualification evaluation. Initially, the document information related to enterprise qualification evaluation is generally created manually, although automatic extraction is possible. While the project directory and corresponding data standards for enterprise qualification evaluation can be extracted manually or automatically, relevant documents may change over time—sometimes the project directory changes, sometimes the corresponding data standards change. This requires relevant personnel to interpret the documents regularly and frequently, increasing workload and increasing the risk of errors. Therefore, generally, the keyword database related to qualification information consists of existing domain keywords. For example, a relevant document is published on a website that publishes relevant documents. This document contains personnel data related to the evaluation of enterprise qualifications. We pre-set a keyword database related to qualification information as "enterprise personnel data." Then, we compare the relevant document with the keyword database related to qualification information, obtaining the qualification keyword "enterprise personnel data." We then analyze the relevant document, which contains the following: "Enterprise personnel data includes: a total number of employees of 100 or more, a number of R&D personnel of 10 or more, a number of people with a bachelor's degree or above of 10 or more, and a number of people with provincial or higher-level qualifications of 2 or more." Further analysis reveals the related keyword "including," resulting in the corresponding item directory and data standards: "total number of employees of 100 or more, number of R&D personnel of 10 or more, number of people with a bachelor's degree or above, number of people with provincial or higher-level qualifications of 2 or more, and their corresponding numbers." The standard information data are "100 people, 10 people, 10 people, and 2 people," respectively. Of course, this is just a simple example and may not be universally applicable; other situations will not be elaborated upon here. Relevant keywords can be pre-set, generally including covert, restrictive, and enumerative keywords. Covert keywords typically include "for," "including," "contains," "composed of," etc. Other cases will not be elaborated here. The document information related to the evaluation of enterprise qualifications can also be manually improved and supplemented. The document information obtained by the document interpretation module may contain deviations or formatting issues, requiring manual intervention for revision. Specifically, the document information related to the evaluation of enterprise qualifications can be exported and made editable for easy manual revision; details will not be elaborated here.

[0039] The enterprise information acquisition module is used to collect relevant enterprise information and obtain enterprise qualification information. Enterprise qualification information is a fundamental document for evaluating an enterprise's qualifications. It can include a project directory and individual enterprise qualification information entries. These entries correspond to data standards; the data standards are derived from relevant documents, while the enterprise qualification information entries are derived from the enterprise's relevant information. For the same project directory, both the data standards and the enterprise qualification information entries describe that directory. Data standards are the criteria for evaluating the enterprise qualification information entries. Relevant enterprise information can be obtained from the enterprise's historical background data. This requires collecting historical information about the enterprise and predicting its future development. Various methods exist for acquiring enterprise qualification information, including online data retrieval, extraction from paper documents, on-site interviews with staff, and / or manual input. One method can be used, or multiple methods can be combined. Using only one method can lead to information delays or excessive workload; generally, multiple methods are used in combination, prioritizing the acquisition of information from the same project directory. Specific details are not elaborated here. Online data retrieval involves searching online and collecting relevant information to obtain publicly available information about a company. This information can typically be found through platforms like Qichacha, Tianyancha, or the company's official website. Specific search procedures will not be detailed here. (Reference) Figure 3Methods for retrieving network data can include: obtaining webpage information data, which can be obtained directly from webpages; extracting key information groups from the webpage information data to obtain enterprise qualification information bars; and then arranging and combining these enterprise qualification information bars according to the preset key information groups to form the required enterprise qualification information. The preset key information groups can include: a project directory and corresponding keyword groups, information coverage, extraction methods for enterprise qualification information bars, and combination methods for enterprise qualification information bars. The project directory is the name of the project we need to extract. For example, if we need to count the total number of employees in an enterprise, the project directory obtained from a relevant file would be the total number of employees. Keyword groups are generally synonyms or equivalent words of the project directory. This method increases the completeness of information coverage, avoids data extraction errors caused by keyword setting deviations, ensures the accuracy of data extraction, and allows for information normalization processing using a project directory. For example, if the project directory is the total number of employees, its keyword groups could be the total number of personnel, the number of insured persons, the number of employees, etc. The information coverage content refers to the relative position of the enterprise qualification information bars corresponding to the project directory we want to extract. For example, tabular webpage information data can be used where the information coverage is the right-hand table area of ​​the corresponding table position. This is not the only method; other methods will not be elaborated upon here. This method allows for targeted segmentation of information coverage, followed by targeted extraction, narrowing the extraction scope, significantly reducing computational load, and improving extraction efficiency and accuracy. The extraction method for enterprise qualification information bars can include the form and nature of the information bars. For example, the extracted information bars might be in the form of numbers or in the nature of nouns, etc., details will not be elaborated upon here. This method allows for rapid location of enterprise qualification information bars, improving extraction accuracy and efficiency. The combination method for enterprise qualification information bars is the information export method, which can be exported in tables or other formats, details will not be elaborated upon here. Extraction of information from paper documents can be done by scanning paper documents and then converting them into electronic information data. The post-processing of electronic information data is similar to the methods used for online data retrieval, details will not be elaborated upon here. (Reference) Figure 4 Paper documents are typically in tabular form. Traditional scanning methods for acquiring electronic data don't segment data into regions but directly convert it into text. Therefore, scanning paper documents requires first identifying the table borders. Specifically, this can involve: scanning the paper document to obtain a scanned image; embedding the scanned image into a preset coordinate system; obtaining the grayscale value G of each coordinate point; and setting a standard grayscale value difference ΔG between two adjacent coordinate points to be greater than a preset standard grayscale value difference ΔG. 标The midpoint of the nearest coordinates is used as the dividing point. These nearest coordinates are generally 2-50 pixels, and can be determined based on the clarity of the scanned image; details will not be elaborated here. Standard grayscale difference ΔG 标 The determination can be based on the image's clarity and the difference between the font depth pixels and the background pixels; details will not be elaborated here. The method for obtaining the grayscale values ​​of each coordinate point in the image is existing technology and will not be detailed here either. The line formed by connecting adjacent boundary points sequentially is defined as the boundary line. Then, points are selected along the boundary line according to a preset density ρ to obtain frame line points. The preset density ρ can be one value for every 10-100 pixels, but other cases are not excluded. Then, the straightness of the boundary line is calculated. In the formula, i is the number of the frame point on the same dividing line, and g i The slope of the frame point numbered i is represented by g; i The straightness is the average slope of the n frame line points preceding the i-th number. When the number is less than n, the maximum value is used. The value of n can be 3-10, but other values ​​are not excluded. I is the total number of frame line points currently evaluated on the same boundary line. i = 1, 2, ..., I; α is the device parameter factor, the specific value of which is related to the camera's capabilities or can be obtained through settings. Generally, the higher the resolution of the camera, the smaller the device parameter factor. Without considering camera differences, the device parameter factor can be set to 1, which will not be elaborated here. The straightness calculated by this method can effectively evaluate each boundary line and distinguish whether each boundary line is a frame line. Then, the straightness Sn is determined. I Is it greater than a preset straightness standard Sn? 标 If yes, calculate I+1; otherwise, determine if I is greater than a pre-set standard width frame point count I. 标 If not, the boundary line is determined not to be a frame line and discarded; if it is, the boundary line is defined as a frame line, and the area divided by each frame line is defined as the information coverage area. This allows for targeted analysis. The number of standard width frame line points is I. 标 The specific number of standard width frame points can be determined based on the actual table width and the preset density. Where A is the minimum table width, and ρ is the preset density, which is generally calculated based on the number of pixels. For example, if the minimum table width A is 100 pixels, and the preset density ρ is one border point for every 10 pixels, then the standard width border point count I is... 标The quantity is 10. If it is less than 10, it means that the dividing line is a short straight line segment in font or other form, not a table border. Of course, this is just a simple example and may not be universal. Other situations will not be elaborated here. This method can accurately and clearly obtain each border, avoiding interference from other similar borders, and can greatly reduce the information coverage recognition error caused by non-closed straight lines, thus ensuring accurate positioning. On-site inquiries to staff can be recorded on-site, and then the voice information can be converted into text data, which can then be processed according to the online data retrieval method. This is existing technology and will not be elaborated here. Manual input can be used for error correction or supplementation to avoid typos and information omissions. The details will not be elaborated here. As mentioned above, enterprise qualification information includes historical data and predictive data. Historical data can be obtained directly from the enterprise's historical background information from previous years, and this data is real. Predictive data needs to be predicted based on historical data. Predictive data can be financial data or planning data. Planning data can include listing plans, intellectual property plans, cooperation plans, financing plans, etc., which can be obtained directly from the company's relevant information and do not require forecasting. Financial data mainly includes financial data for the past three years, the current year, and the next two years. Since there is no actual data available for the current year and the next two years, forecasting is necessary. Financial data mainly includes operating revenue, main business revenue, total profit, total net profit, taxes payable, total R&D expenses, etc. Among these, operating revenue is the main calculation subject, and other data can be obtained by calculating their proportions to this main data. Operating revenue O j Where j is the year number, and its value range is j = 1, 2, ..., J; generally, three years of existing data are needed. j = 1 basically represents the annual operating revenue of the past three years, while O4 represents the current year's data. This provides a basis for predicting operating revenue. The value of J is generally 6, but this is only a general case and does not exclude other possibilities, which will not be elaborated here. The aforementioned operating revenue... Where k is the number of each business transaction of the enterprise, K is the total number of business transactions of the enterprise, and k = 1, 2, ..., K; k This represents the annual operating revenue of the business segment numbered k. When j is T, T represents the current year number, i.e., operating revenue o. kFor the current year's revenue of business number k, when j is T, the annual revenue calculation method can include: constructing a revenue curve for the year j and an annual revenue curve. The year-to-date revenue curve has the horizontal axis representing the time points within the year, with the unit of time point coordinates being month, ten-day period, week, or day, preferably month. The vertical axis represents the revenue amount. This involves embedding the revenue at each time point of the year into the coordinate system to obtain each revenue point, and then connecting these revenue points sequentially to obtain the year-to-date revenue curve. The annual revenue curve has the horizontal axis representing each year and the vertical axis representing the revenue amount. This involves embedding the revenue at this time point of each year into the coordinate system to obtain each revenue point, and then connecting these revenue points sequentially to obtain the annual revenue curve. Calculate the year-on-year growth rate Yg for each year. j and month-on-month growth rate Mg m Year-on-year growth rate Yg j The slope of the revenue curve at each annual time point, and the year-on-year growth rate Mg m Let Y be the slope of the revenue curve at time point m within the year. Then, when j = T, the revenue Y at the current year's time point... j,m =ε Y Y j-1,m (1+Yg j )+ε M Y j,m-1 (1+Mg m ), where m is the time unit number within year j, preferably in month format, Y j，m It is the operating revenue for the m-th time unit in year j, ε Y As a year-on-year weighting, ε M The weighting is based on year-on-year changes, and its value can be determined according to the impact of changes within the year or year. ε Y +ε M =1, and its value can be between 0.2 and 0.8, which will not be elaborated here. This allows us to fit and obtain the current year's operating revenue curve, and then, based on Y... j+s =ε Y Y j+s-1,m (1+Yg j+s-1 ), where s is a natural number. Fit the revenue curves for subsequent years. Then integrate the revenue curves for each year to obtain the revenue o. k Other financial data can be calculated based on operating revenue, which will not be elaborated here. This method fully considers both month-on-month and year-on-year changes, and by summarizing and calculating various operating revenues, it can fully take into account the impact of the current year, avoiding judgment based on only one factor, thus making the budget more accurate.

[0040] The enterprise information comparison module is used to determine if there are any empty enterprise qualification information entries. If so, a level one alert signal is sent; otherwise, no alert signal is sent. In actual work, the documents related to enterprise qualification evaluation include a project directory and corresponding data standards, while the enterprise qualification information contains a project directory and corresponding enterprise qualification information entries, all of which are one-to-one. If the enterprise qualification information entry corresponding to a project directory is empty, it means that no information has been collected for that project directory, and a level one alert signal needs to be sent. Through real-time alerts, the level one alert signal includes empty project directories. Specifically, if there are empty entries, a general alert is issued, which can be displayed in a highlighted color on the display page, such as red. Empty locations can be highlighted individually. If there are no empty entries, the corresponding locations on the display page are displayed in a normal color, such as green. This highlighting on the display page facilitates on-site voice inquiries or manual input by staff, avoiding the tedious work caused by repeated manual checks and handovers. The system compares the enterprise qualification information bar with the data standard and determines whether it meets the standard. If it does, no alert signal is sent; otherwise, a secondary alert signal is sent. The secondary alert signal includes a list of items that do not meet the data standard. Meeting the standard can be determined through numerical comparison or keyword overlap. Generally, the enterprise qualification information bar's value is greater than the data standard. For example, if the real-time total number of employees is 120, and the data standard is 100 or more, then 120 is greater than 100, meaning the enterprise qualification information bar meets the standard. Of course, there are also cases where the value is less, which will not be elaborated here. Keyword overlap is determined by whether the number of keywords in the enterprise qualification information bar that overlap with the data standard is equal to the number of keywords in the data standard. If they are equal, the enterprise qualification information bar meets the standard; otherwise, it does not. Specifically, if an enterprise qualification information bar does not meet the standard, a general alert is issued, perhaps by highlighting it in a color (e.g., red) in the corresponding location on the display page. Individual color highlights are also used for each enterprise qualification information bar that does not meet the standard. If all enterprise qualification information entries meet the data standards, they will be displayed in a normal color, such as green, in the corresponding position on the display page. This method allows for the quick identification of projects that do not meet the data standards, facilitating the optimization and supplementation of enterprise qualification information entries for each project category, thereby improving the enterprise's qualifications.

[0041] The evaluation and analysis module is used to calculate the evaluation value q for each project directory. lAnd the total evaluation value F for this evaluation type, where l is the item catalog number for this evaluation type. The evaluation values ​​for each item catalog can be calculated through numerical comparison or keyword overlap. Alternatively, a tiered standard comparison can be used to divide them into excellent, satisfactory, and unsatisfactory levels. Methods for obtaining evaluation values ​​can include: even if an evaluation score is obtained... Where A l V represents the actual value corresponding to the enterprise qualification information bar. l This refers to the standard numerical value in the data standard. Then, the evaluation value q corresponding to its level is determined based on the evaluation score. l This method provides a more intuitive and clear understanding of the information for each project category. For example, it shows the total number of employees in real-time is 120, the data standard is 100 or more employees, and the evaluation score. A score of 1.2 greater than 1 is considered excellent, corresponding to a rating value q. l The value is 1. This is just a simple example and may not be universally applicable; other cases will not be elaborated upon here. Keyword overlap is the ratio of the number of keywords in the enterprise qualification information entries to the number of keywords in the data standard, relative to the number of keywords in the data standard. Evaluation value q l The score should be controlled between 0 and 1, with 1 being the maximum score. Other details will not be elaborated here. The total evaluation value for this evaluation type... Where l is the item number of this evaluation type, L is the total number of items in this evaluation type, and W l This refers to the weight of the project directory numbered l, which can be either workload or evaluation ratio weight. This weight can be prepared in advance based on each project directory. It is not the subject matter of this application and will not be elaborated upon here. Then, the project directory, corresponding data standards, and evaluation value q for each project directory, contained in the documents related to the evaluation of enterprise qualifications, will be included. l The evaluation report is constructed by combining the total evaluation value F for this evaluation type with the enterprise qualification information entries contained in the enterprise qualification information. This facilitates review and analysis.

[0042] Example 2

[0043] refer to Figure 5 A method for evaluating enterprise qualifications includes the following steps:

[0044] S1. Extract relevant documents based on the evaluation type, and interpret these documents to obtain information related to the enterprise's qualifications. This information includes a project directory and corresponding data standards.

[0045] S2. Collect relevant information about the company and obtain its qualification information.

[0046] S3. Determine if there are any empty enterprise qualification information bars in the enterprise qualification information. If so, send a level 1 reminder signal; otherwise, do not send a reminder signal.

[0047] S4. Compare the enterprise qualification information bar with the data standard, and determine whether the enterprise qualification information bar in the same project directory meets the data standard. If it does, do not send a secondary reminder signal; otherwise, send a secondary reminder signal.

[0048] S5. Calculate the evaluation value q for each item in the catalog. l And the total evaluation value F for this evaluation type, where l is the item catalog number for this evaluation type.

[0049] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0050] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A business qualification evaluation system, characterized by, The enterprise qualification evaluation system comprises: A file interpretation module for extracting relevant files according to the evaluation type and interpreting the relevant files to obtain file information related to the evaluation of enterprise qualification, wherein the file information related to the evaluation of enterprise qualification comprises project directories and corresponding data standards; An enterprise information acquisition module for collecting relevant information of the enterprise and obtaining enterprise qualification information, wherein the enterprise qualification information comprises project directories and enterprise qualification information items; An enterprise information comparison module for determining whether the enterprise qualification information items in the enterprise qualification information are empty, and if so, sending a first warning signal, and if not, not sending a warning signal; comparing the enterprise qualification information items with the data standards and determining whether the enterprise qualification information items of the same project directory meet the data standards, and if so, not sending a warning signal, and if not, sending a second warning signal; an evaluation analysis module for calculating an evaluation value q of each item category l and a total evaluation value F of the evaluation type, wherein l is the number of the item category corresponding to the evaluation type; The method for obtaining enterprise qualification information comprises network data retrieval, paper information extraction, on-site inquiry of staff and / or manual input; The paper information extraction method comprises: scanning the paper file, and then converting the paper file into electronic information data; the electronic information data obtaining method comprises: scanning the paper file, obtaining a file scanning picture, implanting the file scanning picture into a preset plane coordinate system, then obtaining a gray value G of each coordinate point, and taking a neighboring two neighboring coordinate point gray value difference ΔG greater than a preset standard gray value difference ΔG 标 as a neighboring coordinate midpoint as a demarcation point, sequentially connecting the neighboring demarcation points to form a demarcation line, taking a point on the demarcation line according to a preset density ρ to obtain a frame line point, then calculating a straightness Sn I of the demarcation line, then judging whether the straightness Sn I is greater than a preset straightness standard Sn 标 , if yes, calculating I+1, if no, judging whether I is greater than a preset standard width frame line point number I 标 , if no, determining that the demarcation line is not a frame line and discarding, if yes, defining the demarcation line as a frame line, and defining a region divided by each frame line as an information coverage range.

2. The enterprise qualification evaluation system of claim 1, wherein, The method for obtaining file information related to the evaluation of enterprise qualification comprises scanning information on the relevant files to obtain text data information, then comparing and identifying the text data information with a pre-set keyword library related to qualification information to obtain qualification keywords, and obtaining the corresponding project directories and data standards according to the pre-set relevance keywords, wherein the project directories and data standards jointly constitute the file information related to the evaluation of enterprise qualification.

3. The enterprise qualification evaluation system of claim 1, wherein, The method for network data retrieval comprises obtaining webpage information data, then extracting pre-set key information groups from the webpage information data to obtain enterprise qualification information items, then arranging and combining the enterprise qualification information items according to the pre-set key information groups to form the required enterprise qualification information.

4. The enterprise qualification evaluation system of claim 3, wherein, The pre-set key information groups comprise project directories and corresponding keyword groups, information coverage range, enterprise qualification information item extraction method and enterprise qualification information item combination method.

5. The enterprise qualification evaluation system of claim 1, wherein, The enterprise qualification information includes historical data and predictive data, the predictive data is the annual operating income O j j is the annual number, j = 1, 2, …, J; the annual operating income O k is the number of each business of the enterprise, K is the total number of business of the enterprise, k = 1, 2, …, K; o k is the annual operating income of the business numbered k.

6. The enterprise qualification evaluation system of claim 5, wherein, Annual operating revenue k The forecasting method includes: constructing an annual revenue curve and a yearly revenue curve. The annual revenue curve is plotted with the year's time points on the x-axis and the revenue amount on the y-axis. Revenue at each time point of the year is plotted into the coordinate system to obtain revenue points, and then these points are connected sequentially to obtain the annual revenue curve. The yearly revenue curve has each year on the x-axis and the revenue amount on the y-axis. Revenue at each time point of each year is plotted into the coordinate system to obtain revenue points, and then these points are connected sequentially to obtain the yearly revenue curve. The year-on-year growth rate Yg is calculated for each year. j and month-on-month growth rate Mg m Year-on-year growth rate Yg j The slope of the revenue curve at each annual time point, and the year-on-year growth rate Mg m Let Y be the slope of the revenue curve at time point m within the year. Then, when j = T, T represents the current year number, and Y represents the revenue at time point m within the current year. j,m =ε Y Y j-1,m (1+Yg j )+ε M Y j,m-1 (1+Mg m ), where m is the time unit number within year j, Y j , m is the operating revenue for the m-th time unit in year j, ε Y As a year-on-year weighting, ε M Using year-on-year weighting, a current year-on-year revenue curve is fitted, and then based on Y... j+s =ε Y Y j+s-1,m (1+Yg j+s-1 ), where s is a natural number, fit the operating revenue curve for subsequent years, and then integrate the operating revenue curves for each year to obtain the operating revenue o. k .

7. The enterprise qualification evaluation system of claim 1, wherein, Whether the enterprise qualification information items meet the data standards is determined by comparing numerical values or keyword coincidence degrees.

8. A method for evaluating the qualification of an enterprise, using the system for evaluating the qualification of an enterprise according to any one of claims 1 to 7, characterized by, The method comprises the following steps: S1. Extracting relevant files according to the evaluation type and interpreting the relevant files to obtain file information related to the evaluation of enterprise qualification, wherein the file information related to the evaluation of enterprise qualification comprises project directories and corresponding data standards; S2. Collecting relevant information of the enterprise and obtaining enterprise qualification information, wherein the enterprise qualification information comprises project directories and enterprise qualification information items; S3. Determining whether the enterprise qualification information items in the enterprise qualification information are empty, and if so, sending a first warning signal, and if not, not sending a warning signal; S4. Comparing the enterprise qualification information items with the data standards and determining whether the enterprise qualification information items of the same project directory meet the data standards, and if so, not sending a warning signal, and if not, sending a second warning signal; S5, calculating the evaluation value q of each item category l and the total evaluation value F of the evaluation type, wherein l is the number of the item category corresponding to the evaluation type.

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