Airport machine room supervision agent data storage method and system

Abstract

The invention belongs to the technical field of data storage, and discloses an airport machine room supervision agent data storage method and system. The method comprises the steps that structured data and unstructured data form a ternary entity relation group to be integrated, a unified knowledge graphical data structure is constructed, and a Neo4J graph database is selected as back-end storage; and a unified knowledge graphical data structure is stored in a Neo4J graph database, so that the query speed of the great relational supervision data of the airport machine room is improved, and subsequent supervision data analysis and function extension are facilitated. Besides, the method provides a unified query interface for the graphical data of the machine room, so that a user can conveniently retrieve and query the data, and meanwhile, powerful support is provided for fine management and intelligent development of the airport machine room.

Description

Technical Field

[0001] The present invention belongs to the technical field of data storage, and in particular to a data storage method and system for an airport computer room supervision intelligent body. Background Art

[0002] With the increasing application of information and intelligent technology in airport computer room management, various types of information in airport computer rooms have exploded. However, traditional data storage methods have limitations in processing structured and unstructured data, which makes it difficult to unify the front-end data query method and inefficiency, making it difficult to meet the needs of efficient supervision and intelligent management of airport computer rooms. Therefore, it is of great significance to develop an intelligent data storage method and system that can efficiently integrate, store and query airport computer room information to improve the management level of airport computer rooms.

[0003] Invention patent 1, a TCM gynecological nursing decision-making assistance system based on clinical knowledge graph (publication number CN117476218A, publication date 20240130) discloses a TCM gynecological nursing decision-making assistance system based on clinical knowledge graph, which relates to the field of gynecological nursing technology, a construction module for obtaining gynecological nursing information, a matching module connected to the construction module, a selection module connected to the matching module, and used to recommend multiple reference gynecological problem information based on a preset similarity, a comparison module connected to the selection module, and used to determine the actual gynecological problem information based on the management end, a nursing module connected to the comparison module, and used if there is a difference problem information, an update module connected to the nursing module. The invention can better assist medical staff in making decisions, reduce the workload of medical staff, and ensure accuracy. The solution of the present invention focuses on providing a data storage method and system based on a knowledge graph airport computer room supervision intelligent body, realizing the integration of structured data and unstructured data, improving the rapid query and retrieval of data, and being able to expand and customize the query and answer according to the actual needs of the airport computer room, providing strong support for the refined management and intelligent development of the airport computer room.

[0004] Invention Patent 2, a computer room visualization supervision system (publication number CN116743804A, publication date 20230913), discloses a computer room visualization supervision system, including a dynamic environment collection subsystem, a security monitoring subsystem, an alarm performance configuration collection subsystem, an Internet of Things management platform, an alarm processing platform and a visualization computer room supervision platform. Through multiple subsystems and platforms, automatic data collection and processing, personnel management, alarm analysis and closed-loop management of operation and maintenance inspections are realized, bringing new ideas to the operation and maintenance management of the computer room, and improving the digitalization and intelligence level of the operation and maintenance of the computer room. The system breaks the barriers of the various monitoring subsystems in the computer room, realizes the fusion processing of heterogeneous data of various systems, and lays the foundation for integrated management; through the visualization computer room supervision platform, the problems of low efficiency of traditional inspections, delayed inspection results, inability to detect problems in time, and hidden dangers are solved; through the integration and connection of multiple scenarios, the traditional extensive computer room management method is transformed into a lean management mode, realizing the security of computer room management, digital monitoring, and unmanned operation and maintenance. The key point of this solution is to provide a computer room visual supervision system, which breaks down the barriers of the various monitoring subsystems in the computer room, realizes the fusion processing of heterogeneous data of each system, and builds a visual supervision function to improve the security of computer room management and realize the digitalization of lean management and paperless operation and maintenance. The focus of the present invention is on the data storage method of the airport computer room supervision intelligent body, realizing the integration of structured data and unstructured data, which can greatly improve the rapid query and retrieval of data, and can be expanded and customized according to the actual needs of the airport computer room for query and answer.

[0005] Through the above analysis, the problems and defects of the existing technology are as follows: in the storage scenarios constructed for the computer room supervision system and intelligent body in the existing technology, there is no flow storage for the structured data and unstructured data of the airport computer room supervision intelligent body, the data query and retrieval speed is slow, and the query application cannot be expanded and customized according to the actual needs of the airport computer room, and cannot provide a theoretical basis for the decision-making of the computer room maintenance personnel. Summary of the invention

[0006] In order to overcome the problems existing in the related art, the disclosed embodiments of the present invention provide an airport computer room supervision intelligent body data storage method and system, specifically relating to an airport computer room supervision intelligent body data storage method and system based on a knowledge graph, aiming to achieve efficient integration, rapid query and intelligent management of airport computer room information. Airport computer room supervision involves structured and unstructured data from multiple data sources. Structured data is generally stored through relational databases such as MySQL, Oracle, and SqlServer, and unstructured data is generally stored and queried through document databases such as MongoDB, HDFS, and Elasticsearch. However, when encountering a scenario where two types of data need to be retrieved and queried uniformly, separate processing is often required, resulting in low query efficiency and unsatisfactory data integration and display. Moreover, in the face of new demands for computer room supervision, data integration processing needs to be performed again, and it cannot be expanded quickly.

[0007] The purpose of the present invention is to connect structured data and unstructured data from multiple data sources, and after processing, construct a knowledge graph for the airport computer room, store the adjusted graphical data structure in Neo4J graph data, and provide a high-performance unified query and question-answering interface to the outside world, so as to facilitate later functional expansion according to application scenarios.

[0008] The technical solution is as follows: a method for storing data of an airport computer room supervision agent, comprising: S1, integrate structured data and unstructured data into ternary entity relationship groups, build a knowledge graph, and optimize to form a unified knowledge graphical data structure; S2, stores the unified knowledge graphical data structure in a graph database to provide data representation and query for subsequent data analysis and function expansion; S3, calls the data stored in the graph database through a unified query and answer interface, and expands external application functions according to specific airport computer room application scenarios.

[0009] In step S1, before integrating the structured data and unstructured data into a ternary entity relationship group, data collection is performed. Through sensors and monitoring system data collection equipment, the temperature and humidity monitoring, software monitoring alarms, equipment maintenance, and inspection structured data of the airport computer room are collected in real time. At the same time, the unstructured document data of the airport computer room emergency response manual, system installation and deployment records, line adjustment records, and database common problem handling manual are obtained by scanning and entering.

[0010] In step S1, the unified knowledge graphical data structure is optimized by pulling the collected structured data from the third-party database through the system, and mapping and dividing the original data attribute fields into entities and relationships according to semantics; specifically, it includes: The attribute field alarm device is taken as a node, and other attribute fields are taken as information nodes. The corresponding relationships are divided into four categories: belongs to, alarm time, alarm level, and included alarm content. The above four types of relationships are used to judge the relationship between entities in the knowledge graph. The corresponding relationship triples are: <alarm device, belongs to, business group>, <alarm device, of, alarm time>, <alarm device, of, severity level>, <alarm device, includes, alarm content>.

[0011] In step S1, the unstructured data is formed into a triple entity relationship group, including: (2.1) Keyword extraction: Clean the unstructured text data, remove stop words, punctuation marks, and special characters; split the cleaned text into individual words or phrases; use the TextRank algorithm to extract keywords from the text, the expression is: In the formula, For a word node In the The weight at the iteration, is the damping coefficient, which is 0.85; For Node and nodes The correlation between For the node All connected nodes, For slave nodes Starting from all the nodes that can be reached, For a word node In the The weight at the iteration, is the number of iterations; (2.2) Entity recognition: Remove duplicates from the extracted keywords and annotate their parts of speech; use rule-based named entity recognition (NER) to identify entities in the document, including names of people, system names, and device types, as nodes in the graph relationship; (2.3) Relationship extraction: After identifying all entities in the document, set the rule template through the system visual interface; (2.4) The identified entities are combined in pairs, the specific relationships between the entities are determined and classified, and the triples with entity relationships are output; the expression of the triples of entity relationships is: , Represent two entities respectively. A relationship between two entities.

[0012] In step (2.3), the rule template includes: Email is in the form of xxxx@xxx.com; Use ^\w+([-+.]\w+)@\w+([-.]\w+).\w+([-.]\w+)*$ to match email addresses.

[0013] In step S1, a knowledge graph is constructed, including: Data integration: Integrate the data entities and relationships after structured and unstructured processing to form a unified entity-relationship triple processing pool; Graph construction: Based on the identified entities and relationships, define the nodes and edges in the graph structure; the nodes contain the entity's name, type, attributes, and document information; the edges annotate the relationship's type, direction, and weight information; Graph structure optimization: Perform a quality assessment based on the knowledge graph relationships constructed and displayed on the visual interface of the operation and maintenance system to determine whether further adjustments are needed. If adjustments are needed, adjust the parameters, delete duplicate or redundant nodes and edges, merge similar entities or relationships, and optimize the layout and links of the graph structure. If no adjustments are needed, directly output the graphical data.

[0014] In step S2, the unified knowledge graphical data structure is stored in the Neo4J graph database. By utilizing the graphical storage characteristics of the Neo4J graph database, various types of information of the airport computer room are stored in the form of nodes and relationships to form an airport computer room information database.

[0015] In step S3, the external application functions are expanded to include: intelligent question and answer, knowledge graph display, and troubleshooting.

[0016] Another object of the present invention is to provide an airport computer room supervision agent data storage system, which implements the airport computer room supervision agent data storage method, and the system comprises: The backend service module is used to connect structured and unstructured data from multiple data sources, build a unified new data structure after different processing, and expand functions according to application scenarios through a unified query and answer interface; System visual configuration module, used to provide manual input interface, parameter adjustment, quality assessment data analysis, adjustment, result display and operation for the background service module; The data storage module is used to save the structured parameter information of the system visualization configuration module, including the link address of the docked third-party database and the update frequency of the knowledge graph, into the relational database Mysql. It is also used to save the complete knowledge graph data constructed by the background service module into the Neo4J graph database to realize graphical storage of data.

[0017] Furthermore, the background service module includes a data collection module, a knowledge graph construction module and a query service module; The data acquisition module is responsible for real-time collection of various information of the airport computer room, including using interfaces to connect to various monitoring systems and sensors to obtain structured temperature and humidity monitoring, software monitoring alarms, equipment maintenance, and inspection data; through the system visualization configuration module input method, the data of the airport computer room emergency response manual, system installation and deployment records, line adjustment records, and database common problem handling manual are obtained. The knowledge graph construction module is responsible for cleaning and integrating the collected data to build a complete computer room knowledge graph data relationship; The query service module is responsible for providing a unified query API interface to the outside world, and supports functional applications to call the interface to quickly query various types of information in the airport computer room.

[0018] In combination with all the above technical solutions, the beneficial effects of the present invention are as follows: The present invention selects the Neo4J graph database as the backend storage, which improves the query speed of the airport computer room's extremely large relational regulatory data, and facilitates subsequent regulatory data analysis and function expansion; the unified query interface of the computer room's graphical data in the present invention allows users to easily retrieve and query data, and also provides strong support for the refined management and intelligent development of the airport computer room. The present invention integrates the multi-source structured and unstructured data of the airport computer room, converts it into a unified knowledge graph, and selects the Neo4J graph database as the backend storage, which improves the query speed of the airport computer room's extremely large relational regulatory data, and facilitates subsequent regulatory data analysis and function expansion; the unified query interface of the computer room's graphical data allows users to easily retrieve and query data. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings herein are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description, serve to explain the principles of the present disclosure; Figure 1 It is a flow chart of the data storage method of the airport computer room supervision agent provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of the data storage method of the airport computer room supervision agent provided by an embodiment of the present invention; Figure 3 It is a knowledge graph construction flow chart provided by an embodiment of the present invention; Figure 4 It is a schematic diagram of an airport computer room supervision agent data storage system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific implementation disclosed below.

[0021] The innovation of the present invention lies in: the present invention integrates the multi-source structured and unstructured data of the airport computer room, transforms them into a unified knowledge graphical data structure, selects the Neo4J graph database as the backend storage, improves the query speed of the airport computer room's extremely large relational regulatory data, and facilitates subsequent regulatory data analysis and function expansion; the unified query interface of the computer room graphical data in the present invention enables users to easily retrieve and query data, and also provides strong support for the refined management and intelligent development of the airport computer room.

[0022] Embodiment 1, as Figure 1 As shown, the airport computer room supervision agent data storage method provided by the embodiment of the present invention includes: S1, integrate structured data and unstructured data into ternary entity relationship groups, build a knowledge graph, and optimize to form a unified knowledge graphical data structure; S2, stores the unified knowledge graphical data structure in a graph database to provide data representation and query for subsequent data analysis and function expansion; S3, calls the data stored in the graph database through a unified query and answer interface, and expands external application functions according to specific airport computer room application scenarios.

[0023] Example 2, as another possible implementation method of the embodiment of the present invention, provides an airport computer room supervision intelligent body data storage method, which collects various types of information of the airport computer room, saves the information to the back-end Neo4J graph database after data cleaning and integration, and realizes the construction of a refined information database of the airport computer room, thereby improving the graphical query speed of the airport computer room supervision data.

[0024] By analyzing the current status of airport computer room operation and maintenance, the characteristics of the current scenario are summarized: 1. It is necessary to connect structured data and unstructured data from multiple data sources, and build a unified new data structure after different processing; 2. The processed new data structure is stored in a unified way; 3. A high-performance unified query and question-and-answer interface is provided to facilitate the subsequent functional expansion according to the application scenario. Based on the above characteristics, this solution will perform entity field mapping on structured data, perform keyword extraction, entity recognition, and relationship extraction on unstructured data, and then integrate it with the data mapped with structured data to build a knowledge graph, form a unified graphical data structure, store it in the Neo4J graph database, and provide a unified query interface and interface to the outside world, which will improve the query and retrieval speed of data while making it more convenient for airports to expand and customize functional applications such as query and question-and-answer according to actual needs.

[0025] like Figure 2 As shown in the figure, structured data is stored in a third-party database, and after data entity mapping, a unified new data structure ternary entity relationship group is formed; after keyword extraction, entity recognition, relationship extraction and other processing, unstructured data also forms a ternary entity relationship group; the system integrates the ternary entity relationship groups of structured data and unstructured data to build a knowledge graph, and stores the optimized unified knowledge graphical data structure in the Neo4J graph database, and the system provides a unified query and answer interface for external use; according to the specific application scenarios of the airport computer room, such as intelligent question and answer, knowledge graph display, troubleshooting, etc., the functional application is expanded. Example 3, as another possible implementation of the present invention, provides an airport computer room supervision agent data storage method, specifically including: (1) Data collection: Through sensors, monitoring systems and other data collection equipment, real-time collection of structured data such as temperature and humidity monitoring, software monitoring alarms, equipment maintenance, and inspections in the airport computer room; At the same time, through scanning and inputting, unstructured document data such as the airport computer room emergency response manual, system installation and deployment records, line adjustment records, and database common problem handling manuals are obtained.

[0026] (2) Data processing: The collected structured data is pulled out from the third-party database through the system, and then the original data attribute fields are mapped and divided into entities and relationships according to semantics. The structured alarm data is shown in Table 1.

[0027] Table 1 Structured alarm data Take the attribute field "alarm device" as a node and other attribute fields as information nodes. The corresponding relationships are divided into four categories: belonging to, alarm time, alarm level, and alarm content included. The above four types of relationships are used to determine the relationship between entities in the knowledge graph, and the corresponding relationship triples are listed: <alarm device, belongs to, business group>, <alarm device, of, alarm time>, <alarm device, of, severity level>, <alarm device, includes, alarm content>. Unstructured data, such as emergency response manuals, line adjustment records, installation manuals and other documents, are converted into a new data structure of graph relationships through a series of processing steps in the system. The specific steps are as follows: (2.1) Keyword extraction: Clean the unstructured text data, including removing stop words, punctuation marks, special characters, etc.; then divide the cleaned text into individual words or phrases; use the TextRank algorithm to extract keywords from the text, the expression is: In the formula, For a word node In the The weight at the iteration, is the damping coefficient, which is 0.85; For Node and nodes The correlation between For the node All connected nodes, For slave nodes Starting from all the nodes that can be reached, For a word node In the The weight at the iteration, is the number of iterations; (2.2) Entity Recognition: Remove duplicates from the extracted keywords and label their parts of speech; use rule-based NER (Named Entity Recongnition) to identify entities in the document, such as names, system names, device types, etc., as nodes in the graph relationship.

[0028] (2.3) Relationship extraction: After identifying all entities in the document, the operation and maintenance expert sets the rule template through the operation and maintenance system visual interface, for example: Emails are usually in the form of xxxx@xxx.com; use “^\w+([-+.]\w+)@\w+([-.]\w+).\w+([-.]\w+)*$” to match email addresses.

[0029] (2.4) The identified entities are combined in pairs, the specific relationships between the entities are determined and classified, and finally the triples with entity relationships are output, for example: , Represent two entities respectively. A relationship between two entities.

[0030] (3) Knowledge graph construction, such as Figure 3 As shown, including: Data integration: After structured and unstructured processing, the data entities and relationships are integrated to form a unified entity-relationship triple processing pool.

[0031] Constructing a knowledge graph: Based on the identified entities and relationships, define the nodes and edges in the graph structure. The nodes contain the entity’s name, type, attributes, and documents it belongs to; the edges label the relationship’s type, direction, weight, and other information.

[0032] Graph structure optimization: Operation and maintenance personnel can evaluate the quality of the knowledge graph relationships formed by the operation and maintenance system visualization interface to determine whether further adjustments are needed. If adjustments are needed, the operation and maintenance personnel can adjust the parameters, delete duplicate or redundant nodes and edges, merge similar entities or relationships, and optimize the layout and links of the graph structure; if adjustments are not needed, the graphical data can be directly output.

[0033] (4) Data storage: The optimized unified knowledge graphical data structure is stored in the Neo4J graph database. By utilizing the graphical storage characteristics of the Neo4J graph database, various types of information of the airport computer room are stored in the form of nodes and relationships to form an airport computer room information database.

[0034] (5) Data query and application: The system builds a unified query API interface for the airport computer room. Computer room maintenance personnel can call this API interface through different visual function interfaces to quickly query various types of information in the airport computer room. Based on the query results, the system can provide the computer room maintenance personnel with the best solution suggestions to assist them in making decisions.

[0035] Embodiment 4, as Figure 4 As shown, an embodiment of the present invention provides an airport computer room supervision agent data storage system, including a system visualization configuration module, a background service module and a data storage module.

[0036] The backend service module is used to connect structured and unstructured data from multiple data sources, build a unified new data structure after different processing, and expand functions according to application scenarios through a unified query and answer interface; The system visualization configuration module is used to provide a manual input interface for the data acquisition module, parameter adjustment for the knowledge graph construction module, data analysis, adjustment, and result display for model quality assessment, as well as visualization and operation of other configuration content required by the system; The data storage module is used to save the structured parameter information of the system visualization configuration module, including the link address of the docked third-party database and the update frequency of the knowledge graph, into the relational database Mysql. It is also used to save the complete knowledge graph data constructed by the background service module into the Neo4J graph database to realize graphical storage of data.

[0037] Exemplarily, the background service module further includes a data collection module, a knowledge graph construction module and a query service module.

[0038] The data acquisition module is responsible for real-time collection of various information of the airport computer room, including using interfaces to connect to various monitoring systems and sensors to obtain structured temperature and humidity monitoring, software monitoring alarms, equipment maintenance, inspection and other data; through the input method of the system visualization configuration module, unstructured document data such as the airport computer room emergency response manual, system installation and deployment records, line adjustment records, and database common problem handling manuals are obtained.

[0039] The knowledge graph construction module is responsible for cleaning and integrating the collected data and constructing a complete computer room knowledge graph data relationship.

[0040] The query service module is responsible for providing a unified query API interface to the outside world, and supports functional applications to call the interface to quickly query various types of information in the airport computer room.

[0041] It can be seen from the above embodiments that the present invention collects various structured and unstructured data of the airport computer room, forms a unified graphical data structure through data mapping, automatic text classification and data integration, and stores it in a Neo4J graph database that is more convenient for retrieval and use. It provides a unified query interface and knowledge graph display to the outside world, greatly improving the query and retrieval speed of data, and can expand and customize the query application according to the actual needs of the airport computer room, assisting the computer room maintenance personnel in decision-making.

[0042] Specifically, the present invention proposes a method for processing and storing structured and unstructured data from multiple data sources: including unifying the data into a ternary entity relationship group and then integrating it, constructing a knowledge graph, and storing it in a Neo4J graph database to ensure the query efficiency of the graphical data in the computer room. The airport computer room supervision intelligent body has a unified query and question-answer interface for graphical data, which is convenient for later functional expansion according to application scenarios. Through this method, the integration of structured and unstructured data from multiple sources in the airport computer room is realized, and the convenience of converting them into a unified knowledge graph is achieved. Selecting the Neo4J graph database as the backend storage fully utilizes the advantages of the graph database in providing great relational data representation and query for further use and query of data, which not only improves the query speed, but also facilitates subsequent data analysis and functional expansion. The solution provides a unified query interface for graphical data in the computer room, allowing users to easily retrieve and query data, and also provides strong support for the refined management and intelligent development of the airport computer room.

[0043] This invention has been verified in the intelligent question-and-answer module of a certain airport's smart operation and maintenance management platform for rapid data query, providing strong support for the refined management and intelligent development of the airport's computer room.

[0044] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principles of the present invention should be covered within the protection scope of the present invention.

Claims

1. A data storage method for an airport computer room supervision agent, characterized in that: The method comprises the following steps: S1, integrate structured data and unstructured data into ternary entity relationship groups, build a knowledge graph, and optimize to form a unified knowledge graphical data structure; S2, stores the unified knowledge graphical data structure in a graph database to provide data representation and query for subsequent data analysis and function expansion; S3, calls the data stored in the graph database through a unified query and answer interface, and expands external application functions according to specific airport computer room application scenarios.

2. The data storage method for airport computer room supervision agent according to claim 1 is characterized in that: In step S1, before integrating the structured data and unstructured data into a ternary entity relationship group, data collection is performed. Through sensors and monitoring system data collection equipment, the temperature and humidity monitoring, software monitoring alarms, equipment maintenance, and inspection structured data of the airport computer room are collected in real time. At the same time, the unstructured document data of the airport computer room emergency response manual, system installation and deployment records, line adjustment records, and database common problem handling manual are obtained by scanning and entering.

3. The data storage method for airport computer room supervision agent according to claim 2 is characterized in that: In step S1, the unified knowledge graphical data structure is optimized by pulling the collected structured data from the third-party database through the system, and mapping and dividing the original data attribute fields into entities and relationships according to semantics; specifically, it includes: The attribute field alarm device is taken as a node, and other attribute fields are taken as information nodes. The corresponding relationships are divided into four categories: belongs to, alarm time, alarm level, and included alarm content. The above four types of relationships are used to judge the relationship between entities in the knowledge graph. The corresponding relationship triples are: <alarm device, belongs to, business group>, <alarm device, of, alarm time>, <alarm device, of, severity level>, <alarm device, includes, alarm content>.

4. The data storage method for an airport computer room supervision agent according to claim 1, characterized in that: In step S1, the unstructured data is formed into a triple entity relationship group, including: (2.1) Keyword extraction: Clean the unstructured text data, remove stop words, punctuation marks, and special characters; split the cleaned text into individual words or phrases; use the TextRank algorithm to extract keywords from the text, the expression is: In the formula, For a word node In the The weight at the iteration, is the damping coefficient, which is 0.85; For Node and nodes The correlation between For the node All connected nodes, For slave nodes Starting from all the nodes that can be reached, For a word node In the The weight at the iteration, is the number of iterations; (2.2) Entity recognition: Remove duplicates from the extracted keywords and annotate their parts of speech; use rule-based named entity recognition (NER) to identify entities in the document, including names of people, system names, and device types, as nodes in the graph relationship; (2.3) Relationship extraction: After identifying all entities in the document, set the rule template through the system visual interface; (2.4) The identified entities are combined in pairs, the specific relationships between the entities are determined and classified, and the triples with entity relationships are output; the expression of the triples of entity relationships is: , Represent two entities respectively. A relationship between two entities.

5. The data storage method for an airport computer room supervision agent according to claim 4 is characterized in that: In step (2.3), the rule template includes: Email is in the form of xxxx@xxx.com; Use ^\w+([-+.]\w+)@\w+([-.]\w+).\w+([-.]\w+)*$ to match email addresses.

6. The data storage method for an airport computer room supervision agent according to claim 1, characterized in that: In step S1, a knowledge graph is constructed, including: Data integration: Integrate the data entities and relationships after structured and unstructured processing to form a unified entity-relationship triple processing pool; Graph construction: Based on the identified entities and relationships, define the nodes and edges in the graph structure; the nodes contain the entity's name, type, attributes, and document information; the edges annotate the relationship's type, direction, and weight information; Graph structure optimization: Perform a quality assessment based on the knowledge graph relationships constructed and displayed on the visual interface of the operation and maintenance system to determine whether further adjustments are needed. If adjustments are needed, adjust the parameters, delete duplicate or redundant nodes and edges, merge similar entities or relationships, and optimize the layout and links of the graph structure. If no adjustments are needed, directly output the graphical data.

7. The data storage method for an airport computer room supervision agent according to claim 1, characterized in that: In step S2, the unified knowledge graphical data structure is stored in the Neo4J graph database. By utilizing the graphical storage characteristics of the Neo4J graph database, various types of information of the airport computer room are stored in the form of nodes and relationships to form an airport computer room information database.

8. The data storage method for an airport computer room supervision agent according to claim 1, characterized in that: In step S3, the external application functions are expanded to include: intelligent question and answer, knowledge graph display, and troubleshooting.

9. An airport computer room supervision agent data storage system, characterized in that: The system implements the data storage method for an airport computer room supervision agent as claimed in any one of claims 1 to 8, and the system comprises: The backend service module is used to connect structured and unstructured data from multiple data sources, build a unified new data structure after different processing, and expand functions according to application scenarios through a unified query and answer interface; System visual configuration module, used to provide manual input interface, parameter adjustment, quality assessment data analysis, adjustment, result display and operation for the background service module; The data storage module is used to save the structured parameter information of the system visualization configuration module, including the link address of the docked third-party database and the update frequency of the knowledge graph, into the relational database Mysql. It is also used to save the complete knowledge graph data constructed by the background service module into the Neo4J graph database to realize graphical storage of data.

10. The airport computer room supervision agent data storage system according to claim 9, characterized in that: The backend service module includes a data collection module, a knowledge graph construction module and a query service module; The data acquisition module is responsible for real-time collection of various information from the airport computer room, including using interfaces to connect to various monitoring systems, sensors to obtain structured temperature and humidity monitoring, software monitoring alarms, equipment maintenance, and inspection data; Through the system visual configuration module input method, obtain the airport room emergency response manual, system installation and deployment records, line adjustment records, and database common problem handling manual unstructured document data; The knowledge graph construction module is responsible for cleaning and integrating the collected data to build a complete computer room knowledge graph data relationship; The query service module is responsible for providing a unified query API interface to the outside world, and supports functional applications to call the interface to quickly query various types of information in the airport computer room.

Images