Scientific research project knowledge base construction method and intelligent management system

Abstract

The invention discloses a scientific research project knowledge base construction method and an intelligent management system, and belongs to the technical field of knowledge management. The construction method comprises the following steps: S1, obtaining scientific research knowledge: obtaining objects of the scientific research knowledge comprise scientific research documents, paper data, scientific research reports, research results and experience teaching and training, and obtaining ways comprise collection literatures, network files and electronic publications; s2, scientific research knowledge classification: the scientific research knowledge is classified by establishing a classification system of a knowledge base, the classification system is designed according to the purpose and range of the knowledge base, and the classification system comprises themes, categories and keywords; s3, building a knowledge graph model: building an attribute relation graph of various knowledge points around the features and functions of the corresponding knowledge points, displaying the incidence relation among the knowledge points, representing the scientific research knowledge through a knowledge graph and a semantic network knowledge representation model, and then storing the scientific research knowledge in a database; s4, visual display: utilizing a data visualization technology to convert complex data into charts and graphs, and displaying and analyzing achievement data of the scientific research project; and S5, project information management: collecting and storing basic information of the project. According to the scientific research project knowledge base construction method and the intelligent management system provided by the invention, scientific research project knowledge data are classified, mined and analyzed, so that scientific research personnel can be helped to quickly understand and analyze data.

Description

Technical Field

[0001] The present invention belongs to the technical field of knowledge management, and in particular relates to a scientific research project knowledge base construction method and an intelligent management system. Background Art

[0002] In today's scientific research field, knowledge management is crucial to promoting scientific research progress and stimulating innovation. It is a process of using intelligent means to obtain valuable data and information, store them in a structured manner, and guide the solution of new problems through reuse and reasoning to achieve knowledge innovation. Scientific research activities are highly dependent on knowledge. From experimental design to paper writing, each link involves the generation and application of knowledge, and is highly dependent on personal and team experience. However, due to the frequent turnover of scientific researchers, valuable experience and knowledge are easily lost, and coupled with the limitations of personal knowledge and thinking, there is an urgent need for collaborative sharing of knowledge between disciplines. However, an ideal scientific research knowledge management system has not yet appeared. A large amount of scientific research knowledge is tacit knowledge, hidden in the problem-solving process, and difficult to capture and express. Scientific research knowledge is complex and changeable, involving multiple fields, which makes knowledge reuse and reasoning extremely difficult. Summary of the invention

[0003] In view of the deficiencies existing in the related art, the purpose of the present invention is to provide a method for constructing a scientific research project knowledge base and an intelligent management system to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A method for constructing a scientific research project knowledge base comprises the following steps:

[0006] S1. Scientific research knowledge acquisition

[0007] The objects of scientific research knowledge acquisition include: scientific research documents, paper materials, scientific research reports, research results and lessons learned, and the acquisition channels include library documents, network files and electronic publications;

[0008] S2. Classification of scientific research knowledge

[0009] Classify scientific research knowledge by establishing a classification system for the knowledge base. The classification system is designed according to the purpose and scope of the knowledge base. The classification system includes topics, categories and keywords.

[0010] S3. Build a knowledge graph model

[0011] Focusing on the characteristics and functions of the corresponding knowledge points, we build attribute relationship diagrams for various knowledge points, show the associations between knowledge points, represent scientific research knowledge through knowledge graphs and semantic network knowledge representation models, and then store scientific research knowledge in the database;

[0012] S4. Visualization

[0013] Use data visualization technology to convert complex data into charts and graphs to display and analyze the results of scientific research projects;

[0014] S5. Project Information Management

[0015] Collect and store basic information of the project, including project foundation information, project team information, project research content information, project results information and project related information.

[0016] In some of the embodiments, in step S2, natural language processing and text mining techniques are used to extract key knowledge and information from the document, and scientific research knowledge is automatically classified to provide intelligent retrieval functions and support keyword search and semantic search.

[0017] In some of the embodiments, after the classification system is established, knowledge is collected, organized and archived. The knowledge comes from employees' experience, project materials and customer feedback. The knowledge is collected through face-to-face communication, online collaboration and file sharing. When organizing and archiving knowledge, the accuracy, completeness and readability of the information are ensured, and the classification system is followed for archiving.

[0018] In some of the embodiments, the method for constructing a scientific research project knowledge base further includes step S6 of establishing a platform and tools for the knowledge base: establishing a platform and tools for the knowledge base based on user needs, security, ease of use, and scalability.

[0019] In some of the embodiments, the method for constructing a scientific research project knowledge base also includes step S7 of operating and maintaining the knowledge base: regularly updating the knowledge base by adding new content, cleaning out expired content, and optimizing the classification system to maintain the accuracy, completeness, and timeliness of the knowledge base.

[0020] A scientific research project knowledge base intelligent management system adopts a scientific research project knowledge base construction method, and the scientific research project knowledge base intelligent management system includes:

[0021] Initialization module, which is used to build a basic database of scientific research project data;

[0022] An input module, which is used to receive information input by a user, including display point information and multiple scientific research information corresponding to different fields;

[0023] A data processing module, which is used to process scientific research information;

[0024] Knowledge base construction module: The knowledge base construction module is used to integrate and expand scientific research knowledge from different data sources and data types to build a scientific research project knowledge base;

[0025] Classification module: The classification module is used to integrate all scientific research project knowledge data, classify according to different projects, and classify and store scientific research knowledge according to project categories, subject areas and research stages;

[0026] The knowledge search module includes a query unit, a search unit and an output unit. The query unit is used to obtain keywords matching the search terms according to the search terms input by the user. The search unit is used to obtain data matching the keywords through the knowledge base. The output unit is used to send the data to the user.

[0027] Visualization module, which is used to convert complex data into charts and graphs, and to display and analyze the results data of scientific research projects.

[0028] In some embodiments, the data processing module includes:

[0029] A processing unit, the processing unit is used to process the multiple scientific research information received by the input module into multiple scientific research information in the same format;

[0030] A cleaning unit, which is used to analyze the correlations between multiple scientific research information, and based on these correlations, eliminate ambiguities between the multiple scientific research information and remove erroneous information;

[0031] The information combination unit is used to combine multiple scientific research information corresponding to each different field to obtain multiple different scientific research knowledge graphs, and combine multiple different scientific research knowledge graphs to obtain a complete scientific research knowledge graph.

[0032] In some embodiments, the knowledge base building module includes:

[0033] Construction unit: The construction unit constructs different ontology libraries for different data sources and data types. Each ontology library describes scientific research knowledge from different angles and dimensions.

[0034] Mapping unit, which maps each ontology library into a global ontology library so that data from different sources can be integrated under a unified framework;

[0035] A construction unit, which performs entity alignment and entity linking on the global ontology library as the knowledge base from various sources, improves and expands the constructed multi-data fusion scientific research knowledge graph, and associates the same or similar entities in the data from different sources through entity alignment and linking;

[0036] The knowledge base expansion unit expands the basic database based on scientific research knowledge data and monitoring data to form a scientific research project knowledge base.

[0037] In some of the embodiments, the knowledge base expansion unit is also used to automatically extract structured rules from the self-defined sample data, and store the structured rules in the structured rule base, so as to provide guarantee for the continuous updating and improvement of the knowledge base.

[0038] In some of the embodiments, the intelligent management system of scientific research project knowledge base also includes an evaluation module, a management module, an extraction module and an acquisition module. The evaluation module is used to score the scientific research knowledge graph, the management module is used to establish a digital index for the scientific research knowledge graph, the extraction module is used to extract scientific research information features in the scientific research knowledge graph and generate feature vector text, and the acquisition module is used to use D2R tools, wrappers and information extraction methods to obtain multiple scientific research information corresponding to different fields.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] 1. The scientific research project knowledge base construction method and intelligent management system provided by the present invention obtain scientific research knowledge from multiple channels, and then integrate various scientific research information in an orderly manner through classification, construction of knowledge graphs, data processing and other links. By establishing a unified knowledge base, long-term storage and efficient management of knowledge are achieved. Users can quickly locate the required knowledge based on the classification system and search modules. The modules work together to greatly improve the utilization efficiency of scientific research knowledge and reduce the time for knowledge search and sorting.

[0041] 2. The scientific research project knowledge base construction method and intelligent management system provided by the present invention can not only store and retrieve knowledge, but also display scientific research results and key project data through a visualization module, assisting scientific researchers to intuitively grasp the progress of the project. At the same time, the data analysis module mines the data value, and the evaluation module evaluates the quality of the knowledge graph to provide direction for optimizing the knowledge base. In addition, the knowledge base is regularly updated and maintained to ensure the timeliness of knowledge, helping scientific researchers to make scientific decisions in all aspects and promoting the continuous development of scientific research projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0043] Figure 1 A flow chart of a scientific research project knowledge base construction method according to an embodiment of the scientific research project knowledge base construction method and intelligent management system of the present invention;

[0044] Figure 2 A schematic diagram of a scientific research project knowledge base management system according to an embodiment of the scientific research project knowledge base construction method and intelligent management system of the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0046] In the description of the present invention, it should be understood that the terms "center", "lateral", "longitudinal", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0047] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0048] Embodiment 1:

[0049] See attached Figure 1 to Figure 2 , an illustrative embodiment of the method for constructing a scientific research project knowledge base proposed by the present invention is given, and the method comprises the following steps:

[0050] S1. Scientific research knowledge acquisition

[0051] The objects of scientific research knowledge acquisition include: scientific research documents, paper materials, scientific research reports, research results and lessons learned, and the acquisition channels include library documents, network files, and electronic publications; scientific research knowledge comes from a wide range of sources and contains rich information, which helps to form the core content of the knowledge base, and the acquisition channels are diversified, which can ensure that a wide range of scientific research knowledge is collected from different channels, providing a sufficient data basis for subsequent processing and utilization.

[0052] S2. Classification of scientific research knowledge

[0053] Scientific research knowledge can be classified by establishing a classification system for the knowledge base. The classification system should be designed according to the purpose and scope of the knowledge base. The classification system should include topics, categories and keywords. The classification system should be clear, simple and easy to understand, which will help to organize the massive amount of scientific research knowledge and enable users to quickly locate the required information based on different topics, categories or keywords.

[0054] S3. Build a knowledge graph model

[0055] Based on the characteristics and functions of the corresponding knowledge points, an attribute relationship diagram of each knowledge point is established to show the correlation between the knowledge points. The scientific research knowledge is represented by the knowledge graph and the semantic network knowledge representation model respectively, and then the scientific research knowledge is stored in the database; it helps to sort out the internal connections between knowledge and present the structured characteristics of knowledge.

[0056] S4. Visualization

[0057] Using data visualization technology, complex data can be converted into charts and graphs to display and analyze the results of scientific research projects; it can help users intuitively understand data from different angles and discover patterns and trends in the data.

[0058] S5. Project Information Management

[0059] Collect and store basic information of the project, including basic information of the project, project team information, project research content information, project results information and project related information. Comprehensive project information management can provide an overall information framework for the entire scientific research project, which is conducive to the overall planning and coordination of scientific research work.

[0060] In step S2, natural language processing and text mining techniques are used to extract key knowledge and information from documents. Automatic classification of scientific research knowledge provides intelligent retrieval functions and supports keyword search and semantic search. The original scientific research data is converted into classifiable and searchable key information, providing a basis for subsequent intelligent retrieval functions. Users can find the required scientific research knowledge more flexibly and efficiently to meet different information needs.

[0061] Collecting, organizing and archiving knowledge is the core of building a knowledge base. After establishing the classification system, continue to collect, organize and archive knowledge. Knowledge comes from employee experience, project information and customer feedback. The way of knowledge collection is face-to-face communication, online collaboration and file sharing. When organizing and archiving knowledge, ensure the accuracy, completeness and readability of the information, and follow the classification system for archiving.

[0062] In step S5, the basic information of the project includes the project name, project number, project source and project start and end time. The project name succinctly and accurately summarizes the core content of the project and is the primary identifier for identifying and retrieving the project. The project number is a unique identifier for each project, which facilitates accurate positioning and management in the system. The project source records the funding or commissioning agency of the project, which helps to understand the background and financial support of the project. The project start and end time clarifies the start and end time of the project, which can help users understand the time span of the project, which is of great significance for analyzing the progress of the project and the timeliness of the results.

[0063] Project team information includes the project leader and team members. The project leader information includes name, contact information, affiliation, research field, etc., which is convenient for understanding the core figures of the project and conducting relevant communications. Listing all members involved in the project, as well as their roles and responsibilities in the project, helps to understand the composition and professional background of the project team. Recording the research directions and professional expertise of each team member makes it easier to quickly find people with relevant professional knowledge when needed, and also helps to evaluate the overall research capabilities of the team.

[0064] Project research content information includes project summary, research objectives, research questions, research methods and technical routes. The project summary is a brief summary of the project research content, objectives, methods, main results, etc., which allows users to quickly understand the core points of the project. Clarifying the specific goals of the project can serve as an important basis for evaluating project results, and is also key information for retrieving whether the project meets specific needs. Elaborate on the specific scientific or practical problems targeted by the project to help users understand the research focus and significance of the project. Recording the research methods and technical means used in the project, such as experimental methods, survey methods, modeling methods, etc., will help other researchers understand the scientific nature and reliability of the project, and can also provide method references for similar projects. Describe the technical process and steps of the project research in the form of charts or text, and show the technical implementation path of the project from the starting point to the end point, so that users can understand the research process and logic of the project.

[0065] Project achievement information includes academic papers, research reports, patent achievements, software copyrights and other forms of achievements. Listing academic papers published during the project, including the title of the paper, author, journal published, publication time and other information, is an important indicator to measure the academic contribution of the project. Various research reports generated by the project, such as mid-term reports and final reports, record the detailed process and results of the project research. The patent information obtained by the project includes patent name, patent number, patent type, application time, etc., which reflects the technological innovation achievements of the project. If the project develops related software, the name, registration number, development time and other information of the software copyright should be recorded to protect the intellectual property rights of the project's software achievements. Other forms of achievements, such as data sets, models, samples, prototypes, etc., record their names, descriptions, acquisition methods and other information in detail to fully demonstrate the diversity of the project's achievements.

[0066] Project association information includes related projects, cited literature, and application cases. If the project is related to other projects, such as the relationship between a sub-project and a parent project, or a cooperative project, record the name and number of the related project to help users understand the overall structure and association of the project. The list of references cited during the project research reflects the theoretical basis and research basis of the project, and also provides users with clues for further in-depth research. Record the application scenarios and cases of project results to demonstrate the actual value and social influence of the project, so that other users can understand the scalability and application prospects of the project results.

[0067] The method for constructing a scientific research project knowledge base also includes step S6 of establishing a platform and tools for the knowledge base: establishing a platform and tools for the knowledge base according to user needs, security, ease of use, and scalability. The platform and tools for the knowledge base are established to better manage and pass on knowledge. Selecting appropriate platforms and tools can improve the efficiency and sustainability of the knowledge base.

[0068] Establishing a knowledge base is not just a one-time job, but also requires operating and maintaining the knowledge base. In this embodiment, the method for constructing a scientific research project knowledge base also includes step S7 of operating and maintaining the knowledge base: regularly updating the knowledge base by adding new content, cleaning out expired content, and optimizing the classification system to maintain the accuracy, completeness, and timeliness of the knowledge base.

[0069] In the above exemplary embodiments, the method for constructing the scientific research project knowledge base is scientific and comprehensive. Knowledge is acquired from multiple channels, and processed through a classification system and advanced technologies to achieve efficient knowledge retrieval. A knowledge graph is constructed to sort out the knowledge context, and visual display assists decision-making. Project information management coordinates the overall situation. Through continuous operation and maintenance, the knowledge base is always in line with scientific research development and provides solid knowledge support for scientific research activities.

[0070] Embodiment 2:

[0071] This embodiment provides an intelligent management system for a scientific research project knowledge base, which adopts the scientific research project knowledge base construction method of Embodiment 1. The intelligent management system includes an initialization module, an input module, a data processing module, a knowledge base construction module, a classification module, a knowledge search module and a visualization module.

[0072] The initialization module is used to build a basic database of scientific research project data; the input module is used to receive information input by users, including display point information and multiple scientific research information corresponding to different fields; the data processing module is used to process scientific research information; the knowledge base construction module is used to integrate and expand scientific research knowledge from different data sources and data types to build a scientific research project knowledge base; the classification module is used to integrate all scientific research project knowledge data, classify according to different projects, and classify and store scientific research knowledge according to the project category, subject field and research stage, so as to facilitate user search and management. The knowledge search module includes a query unit, a search unit and an output unit. The query unit is used to obtain keywords matching the search terms according to the search terms input by the user, the search unit is used to obtain data matching the keywords through the knowledge base, and the output unit is used to send data to the user; the visualization module is used to convert complex data into charts and graphs to display and analyze the results data of scientific research projects. When constructing the scientific research knowledge database, the visualization module provides a scientific research knowledge input interface to facilitate users to input information.

[0073] The data processing module includes a processing unit, a cleaning unit and an information combination unit. The processing unit is used to process the multiple scientific research information received by the input module into multiple scientific research information of the same format; the cleaning unit is used to analyze the correlation between the multiple scientific research information, and based on these correlations, eliminate the ambiguity between the multiple scientific research information and remove the erroneous information, improve the quality and accuracy of the data, and ensure that the subsequent construction and analysis of the knowledge graph are based on reliable data. The information combination unit is used to combine the multiple scientific research information corresponding to each different field to obtain multiple different scientific research knowledge graphs, and combine the multiple different scientific research knowledge graphs to obtain a complete scientific research knowledge graph.

[0074] The knowledge base construction module includes construction units, mapping units, construction units and knowledge base extension units. The construction unit constructs different ontology libraries for different data sources and data types. Each ontology library describes scientific research knowledge from different angles and dimensions, laying the foundation for knowledge fusion. The mapping unit maps each ontology library into a global ontology library so that data from different sources can be integrated under a unified framework, which is convenient for subsequent knowledge fusion and graph construction. The construction unit performs entity alignment and entity linking on the global ontology library as a knowledge base from each source, improves and expands the constructed multi-data fusion scientific research knowledge graph, and associates the same or similar entities in data from different sources through entity alignment and linking, thereby enhancing the integrity and coherence of the knowledge graph. The knowledge base extension unit expands the basic database based on scientific research knowledge data and monitoring data to form a scientific research project knowledge base. The knowledge base extension unit is also used to automatically extract structured rules from custom sample data and save the structured rules in the structured rule library to provide guarantee for the continuous updating and improvement of the knowledge base.

[0075] The intelligent management system for the scientific research project knowledge base also includes an evaluation module, a management module, an extraction module and an acquisition module. The evaluation module is used to score the scientific research knowledge graph and evaluate its quality and completeness. The management module is used to establish a digital index for the scientific research knowledge graph to facilitate the search for scientific research information. The extraction module is used to extract the scientific research information features in the scientific research knowledge graph and generate feature vector texts for retrieval based on the feature vector texts. The acquisition module is used to use D2R tools, wrappers and information extraction methods to obtain multiple scientific research information corresponding to different fields, providing continuous data input for the system.

[0076] In this embodiment, the scientific research project knowledge base intelligent management system also includes a task allocation and scheduling module. The task allocation and scheduling module automatically allocates tasks and generates an optimal work plan based on current project requirements and the professional capabilities of team members. This module uses a mixed integer linear programming model to optimize task allocation, enabling the system to automatically execute multiple project management processes, reducing manual operations and errors. Using data analysis and machine learning algorithms, the system can provide predictions and decision support based on historical data and real-time information, thereby enhancing the accuracy of project management.

[0077] In the above exemplary embodiments, the intelligent management system for the scientific research project knowledge base is fully functional and highly collaborative. The modules work closely together, the input and acquisition modules ensure continuous data inflow, the data processing module optimizes data quality, and the knowledge base construction module creates a comprehensive knowledge graph. Visualization helps intuitive understanding, the classification and search modules facilitate knowledge management and search, and the data analysis and evaluation modules mine value and control quality. It fully meets the needs of scientific research knowledge management and greatly improves the efficiency of scientific research work.

[0078] Finally, it should be noted that: the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0079] The above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or some technical features can be replaced by equivalents without departing from the spirit of the technical solution of the present invention, which should be included in the scope of the technical solution for protection of the present invention.

Claims

1. A method for constructing a scientific research project knowledge base, characterized in that: The steps include: S1. Scientific research knowledge acquisition The objects of scientific research knowledge acquisition include: scientific research documents, paper materials, scientific research reports, research results and lessons learned, and the acquisition channels include library documents, network files and electronic publications; S2. Classification of scientific research knowledge Classify scientific research knowledge by establishing a classification system for the knowledge base. The classification system is designed according to the purpose and scope of the knowledge base. The classification system includes topics, categories and keywords. S3. Build a knowledge graph model Focusing on the characteristics and functions of the corresponding knowledge points, we build attribute relationship diagrams for various knowledge points, show the associations between knowledge points, represent scientific research knowledge through knowledge graphs and semantic network knowledge representation models, and then store scientific research knowledge in the database; S4. Visualization Use data visualization technology to convert complex data into charts and graphs to display and analyze the results of scientific research projects; S5. Project Information Management Collect and store basic information of the project, including project foundation information, project team information, project research content information, project results information and project related information.

2. The method for constructing a scientific research project knowledge base according to claim 1, characterized in that: In step S2, natural language processing and text mining techniques are used to extract key knowledge and information from documents, and scientific research knowledge is automatically classified to provide intelligent retrieval functions, supporting keyword search and semantic search.

3. The method for constructing a scientific research project knowledge base according to claim 2, characterized in that: After establishing the classification system, continue to collect, organize and archive knowledge. Knowledge comes from employee experience, project materials and customer feedback. Knowledge is collected through face-to-face communication, online collaboration and file sharing. When organizing and archiving knowledge, ensure the accuracy, completeness and readability of the information, and archive it in accordance with the classification system.

4. The method for constructing a scientific research project knowledge base according to claim 1, characterized in that: The process also includes step S6 of establishing a platform and tools for a knowledge base: establishing a platform and tools for a knowledge base based on user needs, security, ease of use, and scalability.

5. The method for constructing a scientific research project knowledge base according to claim 4, characterized in that: It also includes step S7 of operating and maintaining the knowledge base: regularly updating by adding new content, cleaning out expired content and optimizing the classification system to maintain the accuracy, completeness and timeliness of the knowledge base.

6. A scientific research project knowledge base intelligent management system, characterized in that: A scientific research project knowledge base construction method is adopted, and the scientific research project knowledge base intelligent management system includes: An initialization module, which is used to construct a basic database of scientific research project data; An input module, the input module is used to receive information input by a user, including display point information and a plurality of scientific research information corresponding to different fields; A data processing module, wherein the data processing module is used to process scientific research information; A knowledge base construction module, which is used to integrate and expand scientific research knowledge from different data sources and data types to build a scientific research project knowledge base; A classification module is used to integrate all scientific research project knowledge data, classify them according to different projects, and store scientific research knowledge according to project categories, subject areas and research stages; A knowledge search module, the knowledge search module comprising a query unit, a search unit and an output unit, the query unit is used to obtain keywords matching the search terms according to the search terms input by the user, the search unit is used to obtain data matching the keywords through the knowledge base, and the output unit is used to send the data to the user; The visualization module is used to convert complex data into charts and graphs, and to display and analyze the results data of scientific research projects.

7. The scientific research project knowledge base intelligent management system according to claim 6 is characterized in that: The data processing module comprises: A processing unit, the processing unit is used to process the multiple scientific research information received by the input module into multiple scientific research information in the same format; A cleaning unit, the cleaning unit is used to analyze the associations between the multiple scientific research information, and based on the associations, eliminate ambiguities between the multiple scientific research information and remove erroneous information; An information combination unit is used to combine multiple scientific research information corresponding to each different field to obtain multiple different scientific research knowledge graphs, and to combine multiple different scientific research knowledge graphs to obtain a complete scientific research knowledge graph.

8. The scientific research project knowledge base intelligent management system according to claim 7, characterized in that: The knowledge base building module includes: A construction unit, wherein the construction unit constructs different ontology libraries for different data sources and data types, and each ontology library describes scientific research knowledge from different angles and dimensions; A mapping unit, which maps each ontology library into a global ontology library so that data from different sources can be integrated under a unified framework; A construction unit, wherein the construction unit performs entity alignment and entity linking on the global ontology library as the knowledge base of each source, improves and expands the constructed multi-data fusion scientific research knowledge map, and associates the same or similar entities in the data from different sources through entity alignment and linking; A knowledge base expansion unit, wherein the knowledge base expansion unit expands the basic database based on scientific research knowledge data and monitoring data to form a scientific research project knowledge base.

9. The scientific research project knowledge base intelligent management system according to claim 8, characterized in that: The knowledge base expansion unit is also used to automatically extract structured rules from the self-defined sample data and store the structured rules in the structured rule base, thus providing guarantee for the continuous updating and improvement of the knowledge base.

10. The scientific research project knowledge base intelligent management system according to claim 7, characterized in that: It also includes an evaluation module, a management module, an extraction module and an acquisition module. The evaluation module is used to score the scientific research knowledge graph, the management module is used to establish a digital index for the scientific research knowledge graph, the extraction module is used to extract scientific research information features in the scientific research knowledge graph and generate feature vector text, and the acquisition module is used to use D2R tools, wrappers and information extraction methods to obtain multiple scientific research information corresponding to different fields.

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