Nationality scoring system based on PEMSTIC model and construction method of PEMSTIC model

Abstract

The invention relates to the technical field of big data analysis, and provides a country scoring system based on a PEMSTIC model and a construction method of the PEMSTIC model.A data collection and integration module in the system is used for real-time collection of multi-source data and integration processing of PEMSTIC dimensions, structured and unstructured data are captured from multiple data sources, and the data are stored in a database; the data are converted into a unified analysis format, and the PEMSTIC dimensions comprise politics, economy, military, safety, science and technology, industry and competition; the model construction module is used for realizing construction and management of a PEMSTIC model based on the PEMSTIC dimension; the judge scoring module is used for scoring based on the unified PEMSTIC model; and the result display module is used for performing visual display and statistical analysis. The technical problem of how to carry out more scientific scoring is solved, and national scoring is more accurate, comprehensive and dynamic. Through the scoring process constructed by the system, the working efficiency of expert scoring personnel is improved, and the speed and accuracy of score calculation and visual presentation are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis, and proposes a country scoring system based on the PEMSTIC (Politics, Economy, Military, Security, Technology, Industry, and Competition) model and a construction method of the PEMSTIC model. Background Art

[0002] In market expansion, scoring target countries is an important tool to help enterprises make scientific decisions. However, traditional scoring methods have many limitations in terms of technology and data application, making it difficult for the scoring results to comprehensively reflect the complex market environment. Specifically, there are the following defects.

[0003] 1. Subjectivity of traditional expert scoring

[0004] Traditional country scoring methods usually rely on experts' experience and subjective judgment, and the process has certain limitations. Experts may assign higher weights to certain factors based on their own fields or past experiences, but these judgments may not fully conform to the actual market situation. Due to strong subjectivity, expert opinions are prone to fluctuate due to time and environmental changes, resulting in large differences in scores for the same target country in different analyses.

[0005] 2. Difficulty of traditional models in covering complex market environments

[0006] Although the traditional PEST model (Politics, Economy, Society, Technology) provides a basic analysis framework, it appears too simplistic in the modern complex market environment. Although the PESTEL model adds environmental and legal factors on the basis of the PEST model, it still cannot meet the market analysis needs of specific fields. Because in recent years, security, geopolitical dynamics, etc. have become important factors affecting the market, but these dimensions are often ignored in traditional models.

[0007] 3. Limited data collection and integration capabilities

[0008] In the era of globalization and informatization, data has become the core resource for decision-making, but traditional methods have great limitations in data collection and integration. First, traditional methods usually rely on a single data source, such as government statistical bureaus or industry reports, and ignore non-traditional data sources such as local news in a certain country. Second, modern data comes in various forms, including structured data (such as trade volume) and unstructured data (such as news reports), and traditional methods lack technical means to effectively integrate these data. Summary of the Invention

[0009] In order to solve the above technical problems existing in the prior art, the present invention proposes a country scoring system based on the PEMSTIC model, including a data collection and integration module, a model construction module, a jury scoring module, and a result display module, wherein,

[0010] A data collection and integration module for real-time collection of multi-source data and integration processing in the PEMSTIC dimension, scraping structured and unstructured data from multiple data sources and converting this data into a unified analysis format, where the PEMSTIC dimension includes politics, economy, military, security, technology, industry, and competition;

[0011] A model construction module for constructing and managing a PEMSTIC model based on the PEMSTIC dimension;

[0012] A judge scoring module for scoring based on a unified PEMSTIC model;

[0013] A result display module for visual display and statistical analysis.

[0014] Furthermore, the data collection and integration module includes:

[0015] A news information sub-module for real-time scraping of text data from a target news platform and integrating and classifying news content through a classification algorithm in the NLP field;

[0016] A national conditions zone sub-module for real-time scraping of data on national conditions statistical indicators, basic national conditions descriptions, organizations, and personnel through pre-configured PEMSTIC categories and collection links corresponding to the PEMSTIC categories, and also for regularly extracting unstructured data collected through a large language model and outputting structured information extraction results according to prompts, and also for processing national conditions statistical indicators and basic national conditions description data through a regular matching algorithm;

[0017] A domain graph sub-module for extracting graph attribute data or relationship data in a specific domain through pre-configured PEMSTIC categories, using PDF text extraction technology to integrate services to construct a domain graph, and organizing the node and relationship tables of the domain graph.

[0018] Furthermore, the model construction module includes:

[0019] A model configuration sub-module for creating independent data tables or collections for the seven domains of the PEMSTIC model using database design methods, defining domain names, domain analysis dimensions, and dimension description fields, and setting a standardized index template for each domain;

[0020] An analysis model sub-module for calling a data API service interface through a front-end component and saving and publishing a model configuration file by calling a back-end API.

[0021] The present invention also proposes a method for constructing a PEMSTIC model, including the following steps:

[0022] Step S-1: Collect data of the PEMSTIC dimension in real time;

[0023] Step S-2: Perform knowledge linking on the PEMSTIC private domain;

[0024] Step S-3: Clean and process the collected data;

[0025] Step S-4: Integrate the data after cleaning and processing;

[0026] Step S-5: Build the framework of the PEMSTIC model;

[0027] Step S-6: Associate the scoring basis of the PEMSTIC model;

[0028] Step S-7: Publish the PEMSTIC model.

[0029] Further, Step S-1 includes:

[0030] Use web crawler technology to scrape text data from local news platforms in the target country in real time. The text data includes news titles, news texts, and news release times;

[0031] Use web crawler technology to scrape target international national condition statistical indicator data, basic national condition data, organizational data, and key personnel data from international databases and think tanks.

[0032] Further, Step S-2 includes:

[0033] Upload the country reports, industry analysis reports, and field analysis reports of the local private domain, and classify and label these reports according to the PEMSTIC field;

[0034] Link to the specific field atlas database and build an interaction atlas between the country and a certain field.

[0035] Further, Step S-3 includes:

[0036] Deduplicate the data collected in real time and clean the noise information in the data;

[0037] Perform unified language translation on the processed data to unify the display language of the system data;

[0038] Based on the NLP field classification technology, classify and label the collected news. The labeling tags include politics, economy, military, security, science and technology, industry, and competition;

[0039] Based on regular matching or large language model extraction technology, convert the cleaned data into a unified standard format.

[0040] Further, step S-4 includes:

[0041] Group the data with unified formats by country, field, and type;

[0042] After that, store it in the database table corresponding to the country.

[0043] Further, step S-5 includes:

[0044] Create independent data tables or collections for each PEMSTIC field, and the table structure includes fields such as field name, analysis dimension, and dimension description;

[0045] Design a standardized index template associated with the PEMSTIC field.

[0046] Further, step S-6 includes:

[0047] Use the specific data content in news and information, national conditions section, and field analysis as the data source for the evaluation basis, select specific content from real-time news data, national conditions statistical data, basic national conditions description, organizations, personnel, analysis reports, and knowledge graphs, and associate it with the corresponding evaluation basis;

[0048] Formulate scoring rules to subdivide the evaluation basis for each field.

[0049] The present invention solves the technical problem of how to conduct more scientific scoring, making the national scoring more accurate, comprehensive, and dynamic. In terms of the scoring dimension, through the PEMSTIC model, the present invention provides political, economic, security, military, technological, industrial, and new competition-based analysis dimensions for country environment scoring, and also supports the expansion of custom dimensions; in terms of the objective scoring basis, through the association of the PEMSTIC model with real-time big data, the present invention provides an objective scoring basis, facilitating experts to unify the scoring criteria and increasing the objectivity, scientificity, and timeliness of country scoring; in terms of improving the scoring efficiency, through the scoring process constructed by the system, the present invention improves the work efficiency of expert scorers, significantly increasing the speed and accuracy of score calculation and visualization presentation. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is the system composition diagram of the present invention;

[0051] Figure 2 It is the method flow diagram of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0052] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described below through specific embodiments and the accompanying drawings.

[0053] As Figure 1As shown in the figure, a country scoring system based on the PEMSTIC model proposed by the present invention mainly includes four modules: a data collection and integration module, a model construction module, a judge scoring module, and a result display module. PEMSTIC is an abbreviation of the capitalized English initials of Political, Economic, Military, Security, Technological, Industry, and Competitive. The detailed description is as follows:

[0054] G-1: Data Collection and Integration Module

[0055] The main task of this module is the real-time collection of multi-source data and the integration and processing of the PEMSTIC (Political, Economic, Military, Security, Technological, Industry, and Competitive) dimension, including scraping structured and unstructured data from multiple data sources and converting them into a unified analysis format to provide basic data support for subsequent PEMSTIC country scoring. This module includes the following sub-modules:

[0056] News and Information Sub-module: Real-time scrape the text data of the target news platform, support multiple site sources; support the collection and integration of unstructured data. Based on the classification algorithm in the NLP field, the system automatically integrates and classifies the news based on the news text content according to PEMSTIC (Political, Economic, Military, Security, Technological, Industry, and Competitive).

[0057] National Conditions Zone Sub-module: By pre-configuring the PEMSTIC (Political, Economic, Military, Security, Technological, Industry, and Competitive) categories and the corresponding collection links, real-time scrape the data of national conditions statistical indicators, basic national conditions descriptions, organizations, and personnel. Based on the large language model, regularly extract the unstructured data collected from organizations and personnel, and output the structured information extraction results according to the prompts; based on the regular matching algorithm, regularly process the national conditions statistical indicators and basic national conditions data and store them; in addition, by pre-configuring the PEMSTIC (Political, Economic, Military, Security, Technological, Industry, and Competitive) categories, support the upload and integration of document data of local country reports and industry reports.

[0058] Domain Atlas Sub-module: By pre-configuring the PEMSTIC (Political, Economic, Military, Security, Technological, Industry, and Competitive) categories, based on the PDF text extraction technology, extract the atlas attribute data or relationship data of a specific domain, integrate the business to build a domain atlas, and sort out the node and relationship table of the domain atlas, and realize the integration of the specific domain atlas database after uploading to the system.

[0059] The above three major sub-modules store the processed data integrated based on PEMSTIC using storage tools such as MySQL, Elasticsearch, NEO4J, and MINIO, and provide an API service call interface for PEMSTIC data under classification.

[0060] G-2: Model Construction Module

[0061] This module is mainly used to construct and manage a scoring model based on the analysis dimensions (politics, economy, security, military, technology, industry, competition) of the PEMSTIC model, supporting custom extensions in multiple fields and unified management of scoring bases. This module includes the following sub-modules:

[0062] Model Configuration Sub-module: By pre-defining the seven basic fields (politics, economy, security, military, technology, industry, competition) of the PEMSTIC model, using database design methods, create independent data tables or collections for each field, and define fields such as field names, field analysis dimensions, and dimension descriptions. Support setting standardized index templates for each field. For example, the economic field can include indicators such as GDP and CPI. Realize field extension configuration, association between indicators and PEMSTIC field data, and dynamic loading of new fields through JSON format.

[0063] Analysis Model Sub-module: Through Vue 3 + Ant Design Vue front-end components, call the data API service interface under PEMSTIC data classification, support dynamic binding, addition, and deletion of scoring bases, and the sources can be selected from specific contents in news and information, national conditions sections, and field analysis. Save and publish the model configuration file by calling the back-end API.

[0064] G-3: Judge Scoring Module

[0065] The main task of this module is to achieve collaborative scoring by different experts based on the unified PEMSTIC model, ensure the scientific rigor of the scoring process, and support archiving and real-time sharing of scoring results.

[0066] For the published PEMSTIC analysis model, support different judges to log in to the system and score each field of the country.

[0067] G-4: Result Display Module

[0068] The main task of this module is to enable users to intuitively grasp the country's performance in politics, economy, security, military, technology, industry, and competition through multi-dimensional visual display and statistical analysis, identify the trend changes of field scores and international competitiveness, and further support the formulation of strategic decisions.

[0069] Visualize the scoring results to show the domain scores of the country over the years. Provide statistical information such as the trend changes of scores in each domain, the comparison of national scores, and the scoring records of each expert.

[0070] The two parts of the judge scoring module and the result display module are the business operations of specific scoring evaluations.

[0071] Such as Figure 2 As shown, the entire process of constructing the PEMSTIC model proposed in the present invention (mainly the detailed description of G-1 and G-2) includes the following steps:

[0072] Step S-1: Real-time collection of PEMSTIC big data

[0073] 1. News and information scraping: Use customized web crawler technology to scrape text data from local mainstream news platforms in the target country in real time, including news titles, news texts, and news release times.

[0074] 2. Data scraping in the national conditions section: Use customized web crawler technology to scrape target international national conditions statistical indicator data (covering key indicators in the fields of politics, economy, military, science and technology, etc.), basic national conditions data (including descriptions such as international overview, historical evolution, administrative divisions, geographical environment, population and ethnicity, political system, economic situation, military strength, foreign relations, etc.), organizational data (organization type, structure, basic information, personnel, etc., and the organization type covers government, parliament, judiciary, military, security), and key personnel data (basic information, personal resume, social relations, attribute tags, social accounts, etc.) from international databases and well-known think tanks.

[0075] Step S-2: Knowledge link in the PEMSTIC private domain

[0076] 1. Link to private domain analysis reports: The system supports users to upload files such as country reports, industry analysis reports, and domain analysis reports in the local private domain, and supports classifying and tagging the reports according to the PEMSTIC domain. The system provides a clear file display function.

[0077] 2. Link to private domain atlas data: The system supports linking to a specific domain atlas database to construct an interactive atlas between the country and a certain domain. The atlas domains include content such as military, competition, and industry.

[0078] Step S-3: Data cleaning and processing

[0079] 1. Data deduplication and noise cleaning: Deduplicate the raw data collected in real time and clean the noise information in the data (such as format errors, irrelevant content, etc.) to improve the data quality.

[0080] 2. Language translation: Perform unified language translation on the processed data to unify the display language of system data.

[0081] 3. PEMSTIC domain classification: Based on NLP domain classification technology, classify and label the collected news by domain. The labels include politics, economy, military, security, technology, industry, and competition.

[0082] 4. Data format unification and conversion: Based on regular expression matching or large model information extraction technology, convert the cleaned data into a unified standard format to ensure the effective integration of structured and unstructured data.

[0083] Step S-4: Data integration

[0084] Group the data with unified formats by country, domain (politics, economy, military, security, technology, industry, competition), and type (news and information, national conditions section, domain spectrum), and then uniformly store them in the database tables corresponding to the countries (including MYSQL, Elasticsearch, NEO4J, MINIO) to provide reliable data support for the subsequent scoring model.

[0085] In a specific embodiment of the present invention, it may further include Step S-5: System data presentation

[0086] The system respectively displays various types of integrated and real-time updated data content based on multiple sub-modules such as news and information, national conditions section, and domain map, including news details, organization information, person information, knowledge graph information, statistical indicators, national conditions description, and private domain report. The system has a real-time update function to ensure that the data display always reflects the latest analysis results and dynamic changes.

[0087] Step S-6: Construction of PEMSTIC model framework

[0088] 1. Database design and initialization

[0089] 1) Creation of domain table

[0090] Create independent data tables or collections for each PEMSTIC domain. The table structure includes the following fields:

[0091] (1) Domain name: Field name (the standard framework includes: politics, economy, military, security, technology, industry, and competition). Support expanding existing domains according to requirements to ensure that the model can flexibly adapt to the market expansion needs of different countries.

[0092] (2) Analysis Dimensions: Define the analysis dimensions included in each domain. For example, the political domain may include "government stability", "policy transparency", etc.; the economic domain may include "GDP growth rate", "inflation rate", etc.; the military domain may include "number of military personnel", "military expenditure", "military structure", etc.; the security domain may include "number of terrorist event news", etc.; the technology domain may include "R & D investment", "number of patent inventions", "science and technology investment funds", etc.; the industrial domain may include "development of the primary industry", "development of the secondary industry", "development of the tertiary industry", etc.; the competition domain may include "market share of competitors", etc.

[0093] (3) Dimension Description: Provide specific descriptions and scopes of application for each analysis dimension. For example, the description corresponding to "government stability" is "Within one year, measure the stability of the government system, including the frequency of government changes, the continuity of major policy changes, and the ability to manage social unrest".

[0094] 2) Standardized Template Initialization

[0095] For the PEMSTIC domain, design a standardized indicator template associated with it. For example: Economic domain: Preset common indicator templates such as GDP growth rate and inflation rate; Technology domain: Preset indicator templates such as R & D investment and number of patent inventions.

[0096] 2. Dynamic Configuration Expansion Support

[0097] Use a JSON file as the core tool for domain configuration, define and maintain the extensibility requirements of each domain, where the weight initialization calculation method is 1 / number of indicators. The JSON structure is as follows:

[0098] {

[0099] "Domain Name": "Economic",

[0100] "Indicators":

[0101] {"Name": "GDP Growth Rate", "Type": "Percentage", "Weight": 0.5},

[0102] {"Name": "Inflation Rate", "Type": "Percentage", "Weight": 0.5}

[0104] }

[0105] The system supports dynamically loading new domains and indicators according to the definition of the JSON file.

[0106] 3. Front - end and Back - end Interaction and Model Binding

[0107] ​The front end uses technologies such as Vue 3 and Ant Design Vue to create a visual interface for users to select or define the model framework and domain metrics.

[0108] The back end provides API interface services, receives the model configuration passed from the front end, stores the configuration in the database, and returns a response indicating successful binding.

[0109] Step S-7: Association of PEMSTIC model scoring basis

[0110] 1. Data source selection and association: It supports using the specific data content in news and information, national conditions section, and domain analysis as the data source for evaluation basis. The front end calls the data API interface provided by the back end, and can select specific content from real-time news data, national conditions statistical data, basic national conditions descriptions, organizations, personnel, analysis reports, and knowledge graphs and associate it with the corresponding evaluation basis to ensure that the data source used in model construction is authoritative and reliable. For example, for the key indicator of inflation rate, the following can be associated: ① The latest inflation news report; ② National conditions statistical data on inflation over the years; ③ The latest inflation analysis report; ④ Economic situation description under basic national conditions; ⑤ Analysis posts of a professional's social account, etc.

[0111] 2. Scoring rule formulation: It supports subdividing the evaluation basis for each domain and allows adjusting the evaluation criteria according to different analysis purposes. For example, in the economic domain, the maximum and minimum score ranges can be formulated, as well as what the key indicators to focus on in scoring are, the method standards for evaluation, and the weight allocation standards for indicators.

[0112] Step S-8: PEMSTIC model release and management

[0113] 1. Model release

[0114] After the model construction is completed, select the version of the PEMSTIC model to be released on the system interface and click the release button. The back-end service uploads the model configuration file to the centralized repository (such as a relational database) through the API. After successful release, a unique version identification code is generated for tracking and management, enabling the released model to be used and shared by multiple users and experts through the management interface.

[0115] 2. Version control

[0116] Maintain the release history record in the database, including version number, release time, release person, updated content, etc. Provide a version rollback function that allows users to restore the model to a previous version.

[0117] 3. Model update and maintenance

[0118] The released model supports users in performing regular maintenance and optimization to ensure that it can reflect the latest data and market conditions. The specific implementation methods are as follows:

[0119] 1) Data update:

[0120] The system regularly obtains the latest data from data sources such as news APIs and national conditions databases, and imports it into the system using the ETL process (Extract, Transform, Load).

[0121] Among them, the data supporting the PEMSTIC model associated under the national conditions section and the domain spectrum map is automatically updated to ensure the timeliness of the data; for news and information data, the model can be modified, and after retrieving and associating the latest news information, the model can be republished for update.

[0122] 2) Indicator adjustment:

[0123] According to the latest requirements, the evaluation scope of the indicators can be adjusted or new indicators can be added in the management interface, and then the model can be republished. The backend provides a configuration update interface to synchronize the adjustment results in real time.

[0124] 3) Message push:

[0125] After the model is republished, the system can, through the message push function, notify relevant experts of the model update content so that the experts can adjust the scores according to the newly released model.

[0126] The present invention provides a country scoring system based on the PEMSTIC model and a construction method of the PEMSTIC model. By introducing real-time data collection, intelligent analysis algorithms, and a dimension dynamic adjustment mechanism, the accuracy, comprehensiveness, and timeliness of country scoring are significantly improved to meet the scientific and adaptable requirements of enterprise market expansion decisions in a complex market environment.

[0127] 1. The present invention uses the innovative PEMSTIC model to replace the existing traditional models (PEST model or PESTEL model). Besides the traditional political, economic, and technological fields, combined with existing market experience, new analysis fields of military, security, industry, and competition are added to construct a more comprehensive country scoring system.

[0128] 2. The PEMSTIC model, by introducing a real-time big data collection and update mechanism, through integrating structured data (such as macroeconomic indicators) and unstructured data (such as real-time news, etc.), can quickly reflect key factors such as policy changes, market dynamics, and economic fluctuations, making up for the lag problem caused by traditional models relying on static data, and more accurately reflecting the multi-level market potential and risks of the target country.

[0129] 3. The system of the present invention provides an operation interface for score visualization, which has significant advantages in realizing multi-country score comparison, display of score trends over the years, formulation of a unified scoring model, multi-expert multi-dimensional collaborative scoring and visual presentation through diversified interaction functions, and is applicable to a wider range of application scenarios.

[0130] The present invention combines the big data collected with real-time updates and uses the PEMSTIC model to comprehensively score and scientifically evaluate the market conditions of target countries, significantly improving the accuracy, comprehensiveness, real-time nature and dynamic adaptation ability of the scoring. Through an automated system design, the whole process from data collection, model construction to result display is realized, reducing human subjective intervention and ensuring the objectivity of the scoring results and the fairness of the evaluation results, providing an intelligent decision-making support tool for enterprises in global market expansion. This technological breakthrough not only reduces the risks brought by data lag or model limitations in traditional analysis methods, but also provides a stronger adaptation ability to cope with the complex and changeable market environment. The construction of the PEMSTIC model and the combination of this model with the big data evaluation basis become the optimal choice for solving the problems of the existing technology.

[0131] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art of this technology, without departing from the technical principle of the present invention, several improvements and deformations can still be made, and these improvements and deformations should also be regarded as the protection scope of the present invention.

Claims

1. A country scoring system based on the PEMSTIC model, characterized in that: It includes data collection and integration module, model building module, judge scoring module and result display module, among which, Data collection and integration module, which is used for real-time data collection from multiple sources and integrated processing of PEMSTIC dimensions, capturing structured and unstructured data from multiple data sources and converting these data into a unified analysis format. The PEMSTIC dimensions include politics, economy, military, security, technology, industry and competition; A model building module, used for building and managing a PEMSTIC model based on the PEMSTIC dimension; The judge scoring module is used to score based on the unified PEMSTIC model; The result display module is used for visual display and statistical analysis.

2. The system according to claim 1, characterized in that The data collection and integration module includes: The news information submodule is used to capture text data from the target news platform in real time and integrate and classify news content through the NLP field classification algorithm; The national conditions submodule is used to capture national conditions statistical indicators, basic national conditions descriptions, organizations, and personnel data in real time through pre-configured PEMSTIC categories and collection links corresponding to PEMSTIC categories. It is also used to regularly extract the collected unstructured data through the large language model and output structured information extraction results based on prompts. It is also used to process national conditions statistical indicators and basic national conditions description data through regular matching algorithms; The domain graph submodule is used to extract graph attribute data or relationship data in a specific domain through pre-configured PEMSTIC categories and PDF text extraction technology, integrate business to build a domain graph, and organize the nodes and relationship tables of the domain graph.

3. The system according to claim 1, characterized in that The model building module includes: A model configuration submodule is used to create independent data tables or collections for the seven domains of the PEMSTIC model using a database design method, define domain names, domain analysis dimensions, and dimension description fields, and set standardized indicator templates for each domain; The analysis model submodule is used to call the data API service interface through the front-end component and save and publish the model configuration file by calling the back-end API.

4. A method for constructing a PEMSTIC model, characterized in that: The following steps are involved: Step S-1: real-time collection of PEMSTIC dimension data; Step S-2: knowledge linking of PEMSTIC private domain; Step S-3: cleaning and processing the collected data; Step S-4: Integrate the cleaned and processed data; Step S-5: construct the framework of the PEMSTIC model; Step S-6: Correlate the scoring basis of the PEMSTIC model; Step S-7: Publish the PEMSTIC model.

5. The method according to claim 4, characterized in that Step S-1 includes: Using web crawler technology to crawl text data from local news platforms in the target country in real time, the text data including news titles, news texts and news release times; Use web crawler technology to capture target international national conditions statistical indicator data, basic national conditions data, organizational data and key personnel data from international databases and think tanks.

6. The method according to claim 5, characterized in that Step S-2 includes: Upload country reports, industry analysis reports, and field analysis reports from local private domains, and classify and label these reports according to PEMSTIC fields; Link to the specific field map database to build an interaction map between the country and a certain field.

7. The method according to claim 6, characterized in that Step S-3 includes: De-duplicate the data collected in real time and clean up the noise information in the data; Perform a unified language translation on the processed data and unify the display language of system data; Based on NLP domain classification technology, the collected news is categorized and labeled into fields including politics, economy, military, security, science and technology, industry and competition; Based on regular matching or large language model extraction technology, the cleaned data is converted into a unified standard format.

8. The method according to claim 7, characterized in that Step S-4 includes: Group the data in a unified format by country, field, and type; Afterwards, it is stored in the database table of the corresponding country.

9. The method according to claim 8, characterized in that Step S-5 includes: Create a separate data table or collection for each PEMSTIC domain. The table structure includes fields such as domain name, analysis dimension, and dimension description. Design of standardized indicator templates linked to PEMSTIC domains.

10. The method according to claim 9, characterized in that Step S-6 includes: Use the specific data content in news information, national conditions special area and field analysis as the data source for evaluation, select specific content from real-time news data, national conditions statistics, basic national conditions description, organization, personnel, analysis reports, knowledge graphs, and associate them with the corresponding evaluation basis; Establish scoring rules and break down the evaluation basis for each area.

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