Standard development contribution degree analysis method and system based on standard bibliography library

Abstract

The invention provides a standard development contribution degree analysis method and system based on a standard bibliography library, and relates to the field of aviation standard analysis, and the method comprises the steps: S1, constructing a database; s2, performing multi-dimensional cleaning on the acquired original standard bibliography data, and complementing standard labels; s3, quantitative evaluation is carried out on contribution values of all regions and grass drawing units in standard development activities; and S4, carrying out visual presentation on a statistical analysis result. The system comprises a database generation module, a data cleaning module, a custom label creation module, a standard information retrieval module, a standard development contribution analysis module and a result demonstration module. According to the method, missing ICS / CCS classification tags are automatically complemented through the conditional probability model and the semantic similarity matching algorithm, the problem that the statistical dimension is limited due to missing of traditional tags is solved, and the analysis integrity and accuracy are improved.

Description

Technical Field

[0001] This invention relates to the field of standards analysis, and specifically to a method and system for analyzing the contribution of standards development based on a standard bibliographic database. Background Technology

[0002] Against the backdrop of globalization and collaborative development in standardization, standards development has become a core component supporting industrial upgrading, technological innovation, and market regulation. Participants include diverse organizations and individuals such as enterprises, research institutions, universities, and industry associations. During the standards development process, the contributions of each participant in stages such as technology research and development, opinion gathering, testing and verification, and text drafting directly impact the quality, applicability, and promotional effectiveness of the standards. Therefore, accurately identifying and quantifying the contributions of each participant is not only crucial for ensuring fairness in standards development and incentivizing participation, but also an important basis for standardization management departments to conduct resource allocation, results evaluation, and credit system construction.

[0003] Currently, contribution analysis in standard development mainly relies on traditional manual statistics or simple data aggregation methods, which have significant technical limitations: First, the data foundation is scattered and inconsistent, lacking the support of a standardized bibliographic database. Existing standard-related data (such as drafting units, publication dates, implementation dates, classification numbers, etc.) are mostly stored in the internal systems, documents, or offline records of various units. The data formats are inconsistent and the correlation is low, making it difficult to achieve large-scale data integration and reuse across standards, fields, and cycles.

[0004] Second, contribution analysis is inefficient and prone to errors. Manual statistical methods require a lot of manpower to sort out participation records and calculate contribution percentages, which is not only inefficient, but also prone to distortion of analysis results due to subjective judgment and data omissions, and cannot meet the rapid analysis needs of massive standard development projects.

[0005] Third, the contribution evaluation dimensions are too singular, lacking comprehensiveness and objectivity. When comparing the number of standards and their contribution indices within their respective fields, the analysis can only rely on existing ICS and CCS classification numbers. On the one hand, some standards lack ICS and CCS classification numbers, affecting the accuracy of the analysis results; on the other hand, ICS and CCS classifications are relatively general and cannot cover the detailed analysis needs of users, resulting in poor usability of the analysis results.

[0006] Finally, the analysis results lack visualization and traceability. Existing technologies cannot generate structured contribution analysis reports, nor can they trace the source and calculation process of contribution data, making it difficult for the analysis results to support standardized management decisions and dispute resolution.

[0007] In summary, existing technologies cannot solve the core problems of "data dispersion, low efficiency, single dimension, and difficulty in traceability" in the contribution analysis of standard development. There is an urgent need to build a systematic and intelligent analysis scheme based on a unified standard bibliographic database to achieve the integration, quantification, multi-dimensional evaluation, and visualization of contribution data, and to provide technical support for the scientific management of standardization work. Summary of the Invention

[0008] To address the shortcomings of the existing technologies, the present invention aims to provide a method and system for analyzing the contribution of standard development based on a standard bibliographic database. This method and system can integrate, quantify, evaluate in multiple dimensions, and visualize contribution data, providing technical support for the scientific management of standardization work. Furthermore, by automatically completing missing ICS / CCS classification labels using a conditional probability model and semantic similarity matching algorithm, the method solves the problem of limited statistical dimensions caused by missing labels in traditional methods, thereby improving the completeness and accuracy of the analysis.

[0009] On the one hand, this invention provides a method for analyzing the contribution of standard development based on a standard bibliographic database, which includes the following steps: S1. Construct the database, which includes a standard bibliographical sub-database, a drafting unit information sub-database, a regional coding sub-database, and a label mapping sub-database; S2. Clean the original standard bibliographic data in the standard bibliographic sub-database and complete the standard labels; S3. Based on the completed standard bibliographical sub-database, an analysis is conducted on the contributions of various regions and drafting units to the development of standards, specifically including: S31. The contribution is quantified using a position-weighted attenuation model. For the k-th drafting unit in a given standard t within the standard range, the contribution weight is calculated. Contribution weight The calculation formula is: ; in, The benchmark weighting coefficient of the editor-in-chief's unit. The position attenuation factor, The drafting units are numbered sequentially, with the first unit being the chief editor's unit. ; S32. Calculate the standard contribution index of a drafting unit within a given standard range. The standard contribution index is the sum of the contribution weights of the drafting unit in each standard. The calculation formula is: ; Where n is the number of standards that the drafting unit participated in drafting within the given standard range; S33. Calculate the standard development contribution value of a certain region within the given standard scope. The standard development contribution value of a certain region is the sum of the standard contribution indices of all drafting units within that administrative region. Calculate the regional standard development contribution value. : ; S4. Visualize the standard contribution index of the drafting unit and the contribution value of regional standard development.

[0010] Preferably, step S2, which involves completing the standard label, specifically includes the following sub-steps: S21. Perform statistical analysis on all complete standard records in the standard bibliographical sub-database; S22. When the standard bibliographical sub-database lacks CCS classification numbers but contains ICS classification numbers, a conditional probability model is used to establish a one-to-one mapping relationship between ICS and CCS classification numbers, and the probability value is calculated. : ; in, This indicates the number of times the ICS classification number and the CCS classification number appear together. The total number of times the ICS classification number appears alone; The complete CCS classification number is obtained based on the probability value of the target ICS classification number query. As a supplementary value for the CCS classification number: ; S23. When the standard bibliographic database lacks an ICS classification number or an ICS classification number corresponds to multiple CCS classification numbers, a semantic similarity matching algorithm is introduced to extract the standard description text of the ICS and CCS classification numbers. Natural language processing tools are then used to segment and word-segment the text, and TF-IDF vectorization is employed to generate text feature vectors. and And calculate the cosine similarity between the two: ; When the calculated cosine similarity When the value exceeds the preset threshold, a one-to-one mapping relationship between the corresponding ICS classification number and CCS classification number is established, and the ICS classification number and CCS classification number are completed.

[0011] Preferably, in step S33, the drafting unit registration address field is retrieved from the drafting unit information sub-database, and semantic matching is performed based on the regional coding sub-database to generate a mapping table between the unit and the administrative division code.

[0012] Preferably, the probability value obtained in step S22 is... The one-to-one mapping relationship between ICS classification numbers and CCS classification numbers, as well as the one-to-one mapping relationship between ICS classification numbers and CCS classification numbers obtained in step S23, are stored in the relationship table of the label mapping sub-database.

[0013] Secondly, the present invention provides a standard development contribution analysis system based on a standard bibliographic database for the above-mentioned standard development contribution analysis method based on a standard bibliographic database, which includes a database generation module, a data cleaning module, a custom label creation module, a standard information retrieval module, a standard development contribution analysis module, and a result demonstration module. The database generation module is used to generate a database, which includes a standard bibliographical sub-database, a drafting unit information sub-database, a regional coding sub-database, and a label mapping sub-database. The data cleaning module is used to clean the collected raw standard bibliographic data in multiple dimensions; the data cleaning module includes a standard label completion submodule, a drafting unit cleaning submodule, and a regional code cleaning submodule; The custom tag creation module is used to select relevant standards from the search results and add tags on the standard information retrieval page. The standard information retrieval module is used to implement the retrieval function based on standard bibliographic information. The standard bibliographic information includes standard number, standard name, standard status, responsible unit, drafting unit, publication date, implementation date, ICS classification, CCS classification, and custom tags. The Standard Development Contribution Analysis Module is based on a multi-dimensional data fusion architecture to achieve a quantitative assessment of the contribution value of various regions and drafting units in the development of standards. The Standard Development Contribution Analysis Module includes a standard quantity statistics sub-module and a standard contribution index statistics sub-module. The results demonstration module is used to visualize the standard contribution index of the drafting unit and the contribution value of regional standard development.

[0014] Preferably, the standard label completion submodule constructs a one-to-one mapping relationship between ICS and CCS classification numbers based on existing ICS and CCS classification number data in national and industry standards, stores the mapping relationship in the label mapping sub-database, and automatically completes the standard data with missing ICS or CCS classification numbers based on the mapping relationship.

[0015] Preferably, the drafting unit cleaning submodule is used to establish a three-level mapping rule library for standard drafting units, standardize and clean the names of drafting units and associate them with credit codes to eliminate naming ambiguities of drafting units; the regional code cleaning submodule converts regional text descriptions into 6-digit standard numerical codes according to the national administrative division coding standard.

[0016] Preferably, the standard quantity statistics submodule constructs a multi-dimensional matrix of the number of national and industry standards drafted based on the standard bibliography sub-database and the drafting unit information sub-database, including the fields of standard release time, drafting unit registration location, and entity name. This matrix is ​​used to statistically analyze the number of national and industry standards drafted by year, region, industry sector, and drafting unit.

[0017] Preferably, the standard contribution index statistics submodule is used to calculate the standard contribution index of the drafting unit and the contribution value of regional standard development based on the order of the standard drafting units in the standard bibliography sub-database and the position weight decay algorithm.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The standard development contribution analysis method based on the standard bibliographic database of the present invention achieves automatic and intelligent completion of missing ICS / CCS classification labels through the synergistic application of conditional probability model and semantic similarity matching algorithm. It effectively solves the problems of limited statistical dimensions and biased analysis results caused by traditional label missing or manual completion methods, significantly improves the completeness, accuracy and processing efficiency of standard data statistical analysis, and provides reliable data support for subsequent multi-dimensional analysis.

[0019] (2) The standard development contribution analysis method based on the standard bibliographic database of the present invention relies on the standardized administrative division coding database to accurately analyze the unit's registered address, establish a one-to-one mapping relationship between the drafting unit and its administrative region, realize the quantitative calculation and accurate evaluation of the regional contribution index, support the automated analysis of multiple dimensions such as standard regional distribution, regional R&D strength, and regional cooperation network, and provide data decision-making basis for policy formulation, resource allocation and regional industrial planning.

[0020] (3) The method and system of the present invention, while being compatible with ICS / CCS standard classification labels, innovatively support the flexible configuration and extended application of up to three levels of custom labels. Based on custom labels, it can realize customized needs such as standard quantity statistics, standard development contribution index calculation, and subdivided field trend analysis, which greatly improves the flexibility, pertinence and adaptability of standard analysis, meets the personalized analysis needs in different scenarios, and further expands the application scope of the technical solution. Attached Figure Description

[0021] Figure 1 This is a flowchart of the standard development contribution analysis method based on a standard bibliographic database of the present invention; Figure 2 This is a flowchart of the standard development contribution analysis system based on a standard bibliographic database of the present invention; Figure 3 This is a schematic diagram of the ICS / CCS classification label mapping of the present invention; Figure 4This is a schematic diagram of the standard custom tag management interface of the present invention; Figure 5 This is a schematic diagram of the standard information retrieval module of the present invention. Detailed Implementation

[0022] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings.

[0023] On the one hand, this invention provides a method for analyzing the contribution of standard development based on a standard bibliographic database, such as... Figure 1 As shown, it includes the following steps: S1. Construct the database, which includes a standard bibliographical database, a drafting unit information database, a regional coding database, and a label mapping database. These databases are constructed by collecting raw data.

[0024] S2. Perform multi-dimensional cleaning on the collected raw standard bibliographic data and complete the standard labels. The completion of standard labels specifically includes the following sub-steps: S21. Perform statistical analysis on all complete standard records in the standard bibliographical sub-database, establish the mapping relationship between ICS classification numbers and CCS classification numbers using a conditional probability model, and calculate the probability values. and the calculated probability value The formula for calculating the value is as follows: (Stored in the relational table of the tag mapping sub-database) ; in, This indicates the frequency of the co-occurrence of ICS and CCS classification numbers. Total frequency of occurrence of ICS classification number alone.

[0025] S22. When the standard lacks a CCS classification number but an ICS classification number exists, the complete CCS classification number can be obtained by querying the probability value based on the target ICS classification number. As a supplementary value for the CCS classification number: .

[0026] S23. When the ICS classification number is missing or multi-level verification is required, a semantic similarity matching algorithm is introduced to extract the standard description text of the ICS and CCS classification numbers. Natural language processing tools are then used to segment the text into sentences and words, and TF-IDF vectorization is used to generate text feature vectors. and And calculate the cosine similarity between the two: .

[0027] When the calculated cosine similarity When the value exceeds a preset threshold, a mapping relationship between ICS classification numbers and CCS classification numbers is established and completed. The default threshold is set to 0.7. In a specific embodiment, the ICS / CCS classification label mapping is as follows: Figure 3 As shown.

[0028] S3. Quantitatively evaluate the contribution value of each region and drafting unit in the standard development activities. In a specific embodiment, step S3 includes the following sub-steps: S31. The contribution is quantified using a position-weighted attenuation model. For the k-th drafting unit in a given standard t within the standard range, the contribution weight is calculated. Contribution weight The calculation formula is: ; in, The baseline weighting coefficient for the chief editor's unit is set to 0.5 by default. This value reflects the core contribution weight of the primary drafting unit. This is the location attenuation factor, whose value can be determined manually based on the standard type or calculated using a formula. The first unit is the sequential number of the drafting unit in the standard text. , in ascending order.

[0029] Specifically, the formula for calculating the position attenuation factor is as follows: ; Where d is the ranking difference between the k-th drafting unit and the chief editor unit. These are the distance attenuation coefficients obtained from the fitting process. Let k be the weight of the k-th drafting unit among all drafting units. Let be the degree of correlation between the k-th drafting unit and a certain standard t. In a specific embodiment, .

[0030] S32. Calculate the standard contribution index of a drafting unit within a given standard range. The standard contribution index is the sum of the contribution weights of the drafting unit in each standard. The calculation formula is: ; Where n is the number of standards that the drafting unit participated in drafting within the given standard range.

[0031] S33. Calculate the standard development contribution value of a certain region within the given standard scope. The standard development contribution value of a certain region is the sum of the standard contribution indices of all drafting units within that administrative region. Calculate the regional standard development contribution value. : .

[0032] S4. Visualize the standard contribution index of the drafting unit and the contribution value of regional standard development.

[0033] Secondly, this invention provides a standard development contribution analysis system based on a standard bibliographic database, such as... Figure 2 As shown, it includes a database generation module 1, a data cleaning module 2, a custom tag creation module 3, a standard information retrieval module 4, a standard development contribution analysis module 5, and a results demonstration module 6.

[0034] The database generation module is used to generate a database, which includes a standard bibliographical sub-database 11, a drafting unit information sub-database 12, a regional coding sub-database 13, and a label mapping sub-database 14.

[0035] The standard bibliographic data sub-database 11 stores raw standard bibliographic data collected from official channels. Fields include at least the standard number, standard name, drafting unit (including sorting information), publication date, ICS classification number, and CCS classification number.

[0036] The drafting unit information sub-database 12 stores the cleaned standardized names, unified social credit codes, and registered addresses of the drafting units.

[0037] The regional coding sub-database 13 stores the national standard administrative division coding table, which includes at least the regional name and its corresponding 6-digit code.

[0038] The tag mapping sub-database 14 not only stores user-created custom tags, but also stores the mapping probability relationship table between ICS and CCS classification numbers. The table fields include ICS (primary key), CCS (foreign key), and Prob (probability value, DECIMAL type).

[0039] The data cleaning module 2 is used to perform multi-dimensional cleaning on the collected raw standard bibliographic data; the data cleaning module 2 includes a standard label completion sub-module 21, a drafting unit cleaning sub-module 22, and a regional code cleaning sub-module 23.

[0040] The standard label completion submodule 21 is used to automatically complete missing ICS or CCS classification numbers.

[0041] The drafting unit cleaning submodule 22 is used to eliminate ambiguity caused by changes in the name of the drafting unit or inconsistencies in abbreviations. This submodule achieves this by establishing a three-level mapping rule base of "former name - current name - unified social credit code". In specific implementation, firstly, the unified social credit code of each drafting unit is matched through the enterprise information query API or the local enterprise name database, and the standardized "current name" and "credit code" are associated and stored in the drafting unit information sub-database 12. In subsequent processing, the system will automatically map variant names such as "XX Co., Ltd." and "XX Limited Liability Company" to standardized names. The area code cleaning submodule 23 is used to convert the text registration address of the drafting unit into a standardized administrative division code. Based on the area code sub-database 13, this submodule uses a string matching algorithm (such as the longest common subsequence algorithm) to match the province, city, and district information in the address text with the standard administrative division name. After a successful match, the corresponding 6-digit code is associated with the drafting unit and stored in the drafting unit information sub-database 12.

[0042] The custom tag creation module 3 allows users to add flexible tags to standards according to their own analytical needs. On the search results page of the standard information retrieval module 4, users can select one or more standards and click the "Add Tag" button. The system will then display a tag management interface, where users can create a tag structure of up to three levels (e.g., first-level tag "Key Technologies", second-level tag "Artificial Intelligence", and third-level tag "Machine Learning"). After creation, the association between the tag and the selected standard is recorded in the tag mapping sub-database 14. Users can subsequently use these custom tags as filtering and grouping dimensions during retrieval and analysis. The standard custom tag management interface is shown below. Figure 4 As shown.

[0043] like Figure 5 As shown, the standard information retrieval module 4 is used to achieve efficient, multi-condition querying of standard bibliographic information. This module provides a combined query interface, allowing users to search based on multiple fields such as standard number, standard name, drafting unit, publication date, ICS / CCS classification number, and user-created custom tags. For example, a user can search for "all national standards whose drafting unit includes 'Tsinghua University' and whose custom tag is 'Artificial Intelligence'". After a search request is submitted, the module uses an SQL query or search engine to jointly query the standard bibliographic sub-database 11 and the tag mapping sub-database 14, and returns the results to the user in list form.

[0044] The Standards Development Contribution Analysis Module 5 is the core of this system. Based on cleaned, multi-dimensional data, it enables a quantitative assessment of contribution value. This module includes at least a Standards Quantity Statistics Submodule 51 and a Standards Contribution Index Statistics Submodule 52.

[0045] The standard quantity statistics submodule 51 constructs a multi-dimensional matrix of "year-region-industry-drafting unit" based on the standard bibliographic information sub-database 11 and the drafting unit information sub-database 12. Through database aggregation queries, it counts the number of participating national and industry standards that meet the criteria.

[0046] The Results Demonstration Module 6 is used to visualize the statistical analysis results. This module is divided into four tabs in the user interface: "Standard Quantity Analysis," "Standard Contribution Index Analysis," "Industry Sector Analysis," and "Drafting Unit Analysis." The system generates bar charts, line charts, and pie charts using a chart library (such as ECharts). Importantly, it can render the C_region data calculated by the Standard Contribution Index Statistics Submodule 52 as a heat map of China, visually demonstrating the contribution of each province and city to standard development. All charts support interactive filtering and drill-down analysis.

[0047] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for analyzing the contribution of standard development based on a standard bibliographic database, characterized in that: It includes the following steps: S1. Construct the database, which includes a standard bibliographical sub-database, a drafting unit information sub-database, a regional coding sub-database, and a label mapping sub-database; S2. Clean the original standard bibliographic data in the standard bibliographic sub-database and complete the standard labels; S3. Based on the completed standard bibliographical sub-database, an analysis is conducted on the contributions of various regions and drafting units to the development of standards, specifically including: S31. The contribution is quantified using a position-weighted attenuation model. For the k-th drafting unit in a given standard t within the standard range, the contribution weight is calculated. Contribution weight The calculation formula is: ； in, The benchmark weighting coefficient of the editor-in-chief's unit. The position attenuation factor, The drafting units are numbered sequentially, with the first unit being the chief editor's unit. ; S32. Calculate the standard contribution index of a drafting unit within a given standard range. The standard contribution index is the sum of the contribution weights of the drafting unit in each standard. The calculation formula is: ； Where n is the number of standards that the drafting unit participated in drafting within the given standard range; S33. Calculate the standard development contribution value of a certain region within the given standard range. The standard development contribution value of a certain region is the sum of the standard contribution indices of all drafting units within the administrative division of that region. Calculate the regional standard development contribution value. : ； S4. Visualize the standard contribution index of the drafting unit and the contribution value of regional standard development.

2. The method for analyzing the contribution of standard development based on a standard bibliographic database according to claim 1, characterized in that: Step S2, which involves completing the standard label, specifically includes the following sub-steps: S21. Perform statistical analysis on all complete standard records in the standard bibliographical sub-database; S22. When the standard bibliographical sub-database lacks CCS classification numbers but contains ICS classification numbers, a conditional probability model is used to establish a one-to-one mapping relationship between ICS and CCS classification numbers, and the probability value is calculated. : ； in, This indicates the number of times the ICS classification number and the CCS classification number appear together. The total number of times the ICS classification number appears alone; The complete CCS classification number is obtained based on the probability value of the target ICS classification number query. As a supplementary value for the CCS classification number: ； S23. When the standard bibliographic database lacks an ICS classification number or an ICS classification number corresponds to multiple CCS classification numbers, a semantic similarity matching algorithm is introduced to extract the standard description text of the ICS and CCS classification numbers. Natural language processing tools are then used to segment and word-segment the text, and TF-IDF vectorization is employed to generate text feature vectors. and And calculate the cosine similarity between the two: ； When the calculated cosine similarity When the value exceeds the preset threshold, a one-to-one mapping relationship between the corresponding ICS classification number and CCS classification number is established, and the ICS classification number and CCS classification number are completed.

3. The method for analyzing the contribution of standard development based on a standard bibliographic database according to claim 1, characterized in that: In step S33, the drafting unit registration address field is retrieved from the drafting unit information sub-database, and semantic matching is performed based on the regional code sub-database to generate a mapping table between the unit and the administrative division code.

4. The method for analyzing the contribution of standard development based on a standard bibliographic database according to claim 2, characterized in that: The probability value obtained in step S22 The one-to-one mapping relationship between ICS classification numbers and CCS classification numbers, as well as the one-to-one mapping relationship between ICS classification numbers and CCS classification numbers obtained in step S23, are stored in the relationship table of the label mapping sub-database.

5. A standard development contribution analysis system based on a standard bibliographic database for use in the standard development contribution analysis method based on a standard bibliographic database as described in claim 1, characterized in that: It includes a database generation module, a data cleaning module, a custom tag creation module, a standard information retrieval module, a standard development contribution analysis module, and a results demonstration module; The database generation module is used to generate a database, which includes a standard bibliographical sub-database, a drafting unit information sub-database, a regional coding sub-database, and a label mapping sub-database. The data cleaning module is used to clean the collected raw standard bibliographic data in multiple dimensions; the data cleaning module includes a standard label completion submodule, a drafting unit cleaning submodule, and a regional code cleaning submodule; The custom tag creation module is used to select relevant standards from the search results and add tags on the standard information retrieval page. The standard information retrieval module is used to implement the retrieval function based on standard bibliographic information. The standard bibliographic information includes standard number, standard name, standard status, responsible unit, drafting unit, publication date, implementation date, ICS classification, CCS classification, and custom tags. The Standard Development Contribution Analysis Module is based on a multi-dimensional data fusion architecture to achieve a quantitative assessment of the contribution value of various regions and drafting units in the development of standards. The Standard Development Contribution Analysis Module includes a standard quantity statistics sub-module and a standard contribution index statistics sub-module. The results demonstration module is used to visualize the standard contribution index of the drafting unit and the contribution value of regional standard development.

6. The standard development contribution analysis system based on a standard bibliographic database according to claim 5, characterized in that: The standard label completion submodule constructs a one-to-one mapping relationship between ICS and CCS classification numbers based on existing ICS and CCS classification number data in national and industry standards, and stores the mapping relationship in the label mapping sub-database. Based on the mapping relationship, it automatically completes the standard data with missing ICS or CCS classification numbers.

7. The standard development contribution analysis system based on a standard bibliographic database according to claim 5, characterized in that: The drafting unit cleaning submodule is used to establish a three-level mapping rule library for standard drafting units, standardize and clean the names of drafting units and associate them with credit codes to eliminate naming ambiguity of drafting units; The regional code cleaning submodule converts regional text descriptions into 6-digit standard numerical codes based on the national administrative division coding standards.

8. The standard development contribution analysis system based on a standard bibliographic database according to claim 5, characterized in that: The standard quantity statistics submodule constructs a multi-dimensional matrix of the number of national and industry standards drafted based on the standard bibliography sub-database and the drafting unit information sub-database, including the fields of standard release time, drafting unit registration location, and entity name. This matrix is ​​used to statistically analyze the number of national and industry standards drafted by year, region, industry sector, and drafting unit.

9. The standard development contribution analysis system based on a standard bibliographic database according to claim 5, characterized in that: The Standard Contribution Index Statistics Submodule is used to calculate the standard contribution index of the drafting unit and the contribution value of regional standard development based on the order of the standard drafting units in the standard bibliography sub-database and the position weight decay algorithm.

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