Electronic official document intelligent search method, system and equipment and storage medium

Abstract

The invention discloses an electronic official document intelligent search method, system and device and a storage medium, belongs to the technical field of electronic official document management, and solves the technical problems of low search efficiency and non-fine authority control. The method comprises a data aggregation process, a data consumption process and a search process. According to the data aggregation process, data of a plurality of service systems are pulled to a database of a data middle table, and the data are respectively loaded to a standard document table, a standard file table and a standard permission table in a unified search library after data processing and conversion; in the data consumption process, high-level data information is stored through a parent index, detailed and fine-grained data information is stored through a child index, and data of a standard document table, a standard file table and a standard permission table are assembled and inserted into an ES; the search process comprises the steps of generating a search result according to the search information of the user, comparing the user information with a preset permission in the standard permission table, and allowing the user to search a document of the search result if the requirement is met.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic document management, and more specifically, to an electronic document intelligent search method, system, device and storage medium. Background Art

[0002] With the continuous improvement of enterprise informatization, electronic documents are increasingly used in enterprises. However, traditional electronic document management systems have many deficiencies in search and authority management, such as low search efficiency and imprecise authority control, which seriously affect the office efficiency and information security of enterprises. Summary of the invention

[0003] The technical problem to be solved by the present invention is to address the above-mentioned deficiencies in the prior art. One purpose of the present invention is to provide an intelligent search method for electronic documents, which can effectively solve the problems of low search efficiency and imprecise authority control.

[0004] The second objective of the present invention is to provide an intelligent search system for electronic documents.

[0005] A third object of the present invention is to provide a computer device.

[0006] A fourth objective of the present invention is to provide a computer storage medium.

[0007] In order to achieve the above-mentioned first objective, the present invention provides an electronic document intelligent search method, including a data aggregation process, a data consumption process, and a search process:

[0008] The data aggregation process includes the following steps:

[0009] Step 11. Data source extraction: from the databases of multiple business systems, through the real-time synchronization function of the DAMO database, data is efficiently and accurately pulled into the database of the data center, ensuring the real-time and consistency of the data;

[0010] Step 12. Data processing and conversion: In the data center, use ETL tools to process the pulled data. ETL tools can clean, convert and integrate data to ensure that the quality and structure of the data meet the requirements of subsequent processing;

[0011] Step 13. Data loading: Load the data processed by the ETL tool into the three core standard tables in the unified search library. The three core standard tables are as follows:

[0012] Standard document table, used to store metadata information of various documents, supporting fast retrieval and management;

[0013] Standard file table, used to store detailed information of files, including file path, size, and creation time, to ensure orderly management and access of files;

[0014] Standard permission tables are used to define and manage user access rights to documents and files to ensure data security and compliance.

[0015] As a further improvement, the data consumption process includes the following steps:

[0016] Step 21. Use a parent-child index structure design to divide the data into two parts: a parent index and a child index. The parent index is used to store high-level data information, and the child index is used to store detailed and fine-grained data information.

[0017] Step 22. Assemble and insert the data of the standard document table, standard file table and standard authority table into ES.

[0018] Furthermore, the search process includes the following steps:

[0019] Step 31. During the search process, first obtain the search keyword entered by the user in the search box; then obtain the trigger information of the user clicking the search button; finally generate the final search results based on the search keyword entered by the user and the screening conditions of the query type, system, department, and organizer;

[0020] Step 32. Permission filtering, obtaining user information, the user information including at least one of user ID, role ID, unit ID, and department ID; comparing the user information with the permissions preset in the standard permission table; if the user information meets the permission requirements preset in the standard permission table, allowing the user to search for documents in the search results.

[0021] Furthermore, the high-level data information includes document title and document file.

[0022] Furthermore, the detailed and fine-grained data information includes file content and permission information.

[0023] Furthermore, in step 22, when processing the data in the standard file table, the following steps need to be performed:

[0024] File download, download files from the data center;

[0025] File parsing, use file parsing tools to obtain the specific content of the file;

[0026] Data insertion: insert the parsed content into ES together with other related data.

[0027] Furthermore, in step 22, when processing the data of the standard permission table, the following two permission filtering methods are supported:

[0028] Single permission filtering supports query filtering based on four dimensions: user ID, role ID, unit ID, and department ID. Users only need to meet any one permission type among the user ID, role ID, unit ID, and department ID to access the target document.

[0029] Combined permission filtering supports any combination of user ID, role ID, unit ID, and department ID for permission filtering; users need to meet the specified permission combination at the same time to access the target document.

[0030] In order to achieve the above-mentioned second objective, the present invention provides an electronic document intelligent search system, comprising:

[0031] The extraction module is used to extract data sources. It efficiently and accurately pulls data from the databases of multiple business systems to the database of the data center through the real-time synchronization function of the DAMO database, ensuring the real-time and consistency of the data.

[0032] The data processing module is used for data processing and conversion. In the data center, the ETL tool is used to process the pulled data. The ETL tool can clean, convert and integrate the data to ensure that the quality and structure of the data meet the requirements of subsequent processing;

[0033] The loading module is used for data loading. It loads the data processed by the ETL tool into the three core standard tables in the unified search library. The three core standard tables are as follows: Standard document table, which is used to store metadata information of various documents to support fast retrieval and management; Standard file table, which is used to store detailed information of files, including file path, size, creation time, to ensure orderly management and access of files; Standard permission table, which is used to define and manage user access rights to documents and files to ensure data security and compliance;

[0034] An index module is used to adopt a parent-child index structure design to divide data into two parts: a parent index and a child index. The parent index is used to store high-level data information, and the child index is used to store detailed and fine-grained data information.

[0035] An assembly module, used to assemble and insert the data of the standard document table, the standard file table and the standard permission table into ES;

[0036] The search module is used in the search process. It first obtains the search keywords entered by the user in the search box; then obtains the trigger information when the user clicks the search button; and finally generates the final search results based on the search keywords entered by the user and the screening conditions of the query type, system, department, and organizer.

[0037] The permission filtering module is used for permission filtering, obtaining user information, the user information including at least one of user ID, role ID, unit ID, and department ID; comparing the user information with the permissions preset in the standard permission table; if the user information meets the permission requirements preset in the standard permission table, the user is allowed to search for documents in the search results.

[0038] In order to achieve the third objective above, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned method for intelligent search of electronic documents when executing the computer program.

[0039] In order to achieve the fourth objective above, the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the computer program implements the above-mentioned method for intelligent search of electronic documents.

[0040] Beneficial Effects

[0041] Compared with the prior art, the present invention has the following advantages:

[0042] 1. The present invention can improve work efficiency: through efficient search technology and fine-grained authority management, the office efficiency of the enterprise can be significantly improved.

[0043] 2. The present invention can ensure information security: through a security audit mechanism with strict standard authority, the security and confidentiality of electronic documents can be ensured.

[0044] 3. The present invention can improve user experience: based on search keywords and screening conditions of query type, system, department, and organizer, it can better meet user needs and provide a more personalized search experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 Gather flow chart for data;

[0046] Figure 2 It is a data consumption flow chart;

[0047] Figure 3 For the search page map. DETAILED DESCRIPTION

[0048] The present invention will be further described below with reference to the specific embodiments in the accompanying drawings.

[0049] See also Figure 1 to Figure 3 , an intelligent search method for electronic documents, including a data aggregation process, a data consumption process, and a search process.

[0050] like Figure 1 As shown, the data aggregation process includes the following steps 11 to 13:

[0051] Step 11. Data source extraction: From the databases of multiple business systems, through the real-time synchronization function of the DAMO database (the DAMO database management system is a high-performance database management system with completely independent intellectual property rights launched by DAMO), data can be efficiently and accurately pulled into the database of the data middle platform, ensuring the real-time and consistency of the data.

[0052] Step 12. Data processing and conversion: In the data center, use ETL tools to process the pulled data. ETL tools can clean, convert and integrate data to ensure that the quality and structure of the data meet the requirements of subsequent processing. ETL tool processing includes three main steps: data extraction (Extract), data transformation (Transform) and data loading (Load).

[0053] Step 13. Data loading: Load the data processed by the ETL tool into the three core standard tables in the unified search library. The three core standard tables are as follows:

[0054] Standard document table, used to store metadata information of various documents, supporting fast retrieval and management;

[0055] Standard file table, used to store detailed information of files, including file path, size, and creation time, to ensure orderly management and access of files;

[0056] Standard permission tables are used to define and manage user access rights to documents and files to ensure data security and compliance.

[0057] like Figure 2 As shown, the data consumption process includes the following steps 21 to 22:

[0058] Step 21. Use a parent-child index structure design to divide the data into two parts: a parent index and a child index. The parent index is used to store high-level data information, including document titles and document files. The child index is used to store detailed, fine-grained data information, including file content and permission information.

[0059] Step 22. Assemble and insert the data of the standard document table, standard file table, and standard permission table into ES (Elasticsearch).

[0060] When processing data in a standard file table, the following steps need to be performed:

[0061] 1) File download: download files from the data center.

[0062] 2) File parsing: Use file parsing tools to obtain the specific content of the file.

[0063] 3) Data insertion: insert the parsed content into ES together with other related data.

[0064] When processing data in the standard permission table, the following two permission filtering methods are supported:

[0065] 1) Single permission filtering, supports query filtering based on four dimensions: user ID, role ID, unit ID, and department ID; users only need to meet any one permission type among user ID, role ID, unit ID, and department ID to access the target document.

[0066] 2) Combined permission filtering supports any combination of user ID, role ID, unit ID, and department ID for permission filtering; users need to meet the specified permission combination at the same time to access the target document.

[0067] like Figure 3 As shown, the search process includes the following steps 31 to 32:

[0068] Step 31. In the search process, first obtain the search keywords entered by the user in the search box; then obtain the trigger information of the user clicking the search button; finally generate the final search results based on the search keywords entered by the user and the screening conditions of the query type, system, department, and organizer.

[0069] Step 32. Permission filtering, obtaining user information, the user information includes at least one of user ID, role ID, unit ID, and department ID; comparing the user information with the permissions preset in the standard permission table; if the user information meets the permission requirements preset in the standard permission table, the user is allowed to search for documents in the search results.

[0070] An electronic document intelligent search system, comprising:

[0071] The extraction module is used to extract data sources. It efficiently and accurately pulls data from the databases of multiple business systems to the database of the data center through the real-time synchronization function of the DAMO database, ensuring the real-time and consistency of the data.

[0072] The data processing module is used for data processing and conversion. In the data center, the ETL tool is used to process the pulled data. The ETL tool can clean, convert and integrate the data to ensure that the quality and structure of the data meet the requirements of subsequent processing;

[0073] The loading module is used for data loading. It loads the data processed by the ETL tool into the three core standard tables in the unified search library. The three core standard tables are as follows: Standard document table, which is used to store metadata information of various documents to support fast retrieval and management; Standard file table, which is used to store detailed information of files, including file path, size, creation time, to ensure orderly management and access of files; Standard permission table, which is used to define and manage user access rights to documents and files to ensure data security and compliance;

[0074] The index module is used to adopt a parent-child index structure design to divide data into two parts: a parent index and a child index. The parent index is used to store high-level data information, and the child index is used to store detailed and fine-grained data information.

[0075] The assembly module is used to assemble and insert the data of the standard document table, standard file table, and standard permission table into ES;

[0076] The search module is used in the search process. It first obtains the search keywords entered by the user in the search box; then obtains the trigger information when the user clicks the search button; and finally generates the final search results based on the search keywords entered by the user and the screening conditions of the query type, system, department, and organizer.

[0077] The permission filtering module is used for permission filtering and obtaining user information, which includes at least one of user ID, role ID, unit ID and department ID; comparing the user information with the permissions preset in the standard permission table; if the user information meets the permission requirements preset in the standard permission table, the user is allowed to search for the documents of the search results.

[0078] A computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the above-mentioned electronic document intelligent search method is implemented.

[0079] A computer-readable storage medium stores a computer program, which implements the above-mentioned electronic document intelligent search method when executed by a processor.

[0080] Practical Application

[0081] The following is a specific embodiment, which shows how to use the method of the present invention to implement the release, search and authority control of departmental documents.

[0082] 1. Release of departmental documents:

[0083] Use a specific account to log in to the business system.

[0084] Publish a departmental document, including the document title, document attachments and other information.

[0085] For example, a document titled "Notice on the 2023 Year-End Summary" is issued with an attachment named "Year-End Summary Report.docx".

[0086] 2. Data consumption and indexing:

[0087] Wait for a while until the data consumption is completed.

[0088] After data consumption is completed, the system will automatically assemble and insert the relevant information of the published documents and their attachments into ES.

[0089] The specific steps are as follows:

[0090] File download: Download the document attachment "Year-end summary report.docx" from the data center.

[0091] File parsing: Use file parsing tools to obtain the specific content of the attachment.

[0092] Data insertion: Insert the parsed content and other relevant information (such as document title, attachment name, etc.) into ES.

[0093] 3. Search official documents:

[0094] Log in to the search page using the specific account that published the document.

[0095] Enter the keyword "2023 Year-end Summary" to search.

[0096] The search results should show the published document "Notice on the 2023 Year-end Summary".

[0097] 4. Permission control verification:

[0098] Log in to the search page using an account from another department.

[0099] Enter the same keyword "2023 Year-end Summary" to search.

[0100] The published document "Notice on the 2023 Year-end Summary" should not be displayed in the search results, thereby verifying the effectiveness of permission control.

[0101] The above are only preferred embodiments of the present invention. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the structure of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. An intelligent search method for electronic documents, characterized in that: Including data aggregation process, data consumption process, and search process: The data aggregation process includes the following steps: Step 11. Data source extraction: from the databases of multiple business systems, through the real-time synchronization function of the DAMO database, data is efficiently and accurately pulled into the database of the data center, ensuring the real-time and consistency of the data; Step 12. Data processing and conversion: In the data center, use ETL tools to process the pulled data. ETL tools can clean, convert and integrate data to ensure that the quality and structure of the data meet the requirements of subsequent processing; Step 13. Data loading: Load the data processed by the ETL tool into the three core standard tables in the unified search library. The three core standard tables are as follows: Standard document table, used to store metadata information of various documents, supporting fast retrieval and management; Standard file table, used to store detailed information of files, including file path, size, and creation time, to ensure orderly management and access of files; Standard permission tables are used to define and manage user access rights to documents and files to ensure data security and compliance.

2. The method for intelligent search of electronic documents according to claim 1, characterized in that: The data consumption process includes the following steps: Step 21. Use a parent-child index structure design to divide the data into two parts: a parent index and a child index. The parent index is used to store high-level data information, and the child index is used to store detailed and fine-grained data information. Step 22. Assemble and insert the data of the standard document table, standard file table and standard authority table into ES.

3. The method for intelligent search of electronic documents according to claim 2, characterized in that: The search process includes the following steps: Step 31. During the search process, first obtain the search keyword entered by the user in the search box; then obtain the trigger information of the user clicking the search button; finally generate the final search results based on the search keyword entered by the user and the screening conditions of the query type, system, department, and organizer; Step 32. Permission filtering, obtaining user information, the user information including at least one of user ID, role ID, unit ID, and department ID; comparing the user information with the permissions preset in the standard permission table; if the user information meets the permission requirements preset in the standard permission table, allowing the user to search for documents in the search results.

4. The method for intelligent search of electronic documents according to claim 2, characterized in that: The high-level data information includes document title and document file.

5. The method for intelligent search of electronic documents according to claim 2, characterized in that: The detailed and fine-grained data information includes file content and permission information.

6. The method for intelligent search of electronic documents according to claim 2, characterized in that: In step 22, when processing the data in the standard file table, the following steps need to be performed: File download, download files from the data center; File parsing, use file parsing tools to obtain the specific content of the file; Data insertion: insert the parsed content into ES together with other related data.

7. The method for intelligent search of electronic documents according to claim 2, characterized in that: In step 22, when processing the data in the standard permission table, the following two permission filtering methods are supported: Single permission filtering, supporting query filtering based on four dimensions: user ID, role ID, unit ID, and department ID; Users only need to meet any one of the permission types of user ID, role ID, unit ID, and department ID to access the target document; Combined permission filtering supports any combination of user ID, role ID, unit ID, and department ID for permission filtering; users need to meet the specified permission combination at the same time to access the target document.

8. An electronic document intelligent search system, characterized in that: include: The extraction module is used to extract data sources. It efficiently and accurately pulls data from the databases of multiple business systems to the database of the data center through the real-time synchronization function of the DAMO database, ensuring the real-time and consistency of the data. The data processing module is used for data processing and conversion. In the data center, the ETL tool is used to process the pulled data. The ETL tool can clean, convert and integrate the data to ensure that the quality and structure of the data meet the requirements of subsequent processing; The loading module is used for data loading. It loads the data processed by the ETL tool into the three core standard tables in the unified search library. The three core standard tables are as follows: Standard document table, which is used to store metadata information of various documents to support fast retrieval and management; Standard file table, which is used to store detailed information of files, including file path, size, and creation time, to ensure orderly management and access of files; Standard permission table, used to define and manage user access rights to documents and files, ensuring data security and compliance; An index module is used to adopt a parent-child index structure design to divide data into two parts: a parent index and a child index. The parent index is used to store high-level data information, and the child index is used to store detailed and fine-grained data information. An assembly module, used to assemble and insert the data of the standard document table, the standard file table and the standard permission table into ES; The search module is used in the search process. It first obtains the search keywords entered by the user in the search box; then obtains the trigger information when the user clicks the search button; and finally generates the final search results based on the search keywords entered by the user and the screening conditions of the query type, system, department, and organizer. The permission filtering module is used for permission filtering and obtaining user information, wherein the user information includes at least one of user ID, role ID, unit ID and department ID; Comparing the user information with the permissions preset in the standard permission table; If the user information meets the authority requirements preset in the standard authority table, the user is allowed to search for the documents of the search results.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method for intelligent search of electronic documents described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, an intelligent search method for electronic documents as described in any one of claims 1 to 7 is implemented.

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