Intelligent management method and device for enterprise asset data, equipment and storage medium

Abstract

The invention relates to an asset data management technology, and discloses an intelligent management method and device based on enterprise asset data, equipment and a storage medium. The method comprises the following steps: identifying a file type of to-be-uploaded transaction data to call a file content identification service to perform content extraction on the to-be-uploaded transaction data to obtain transaction content text information; performing file classification operation based on preset keyword table matching on the transaction content text information to obtain a transaction data classification result, and querying a file storage table corresponding to the transaction data classification result; querying a file management field corresponding to the transaction data classification result according to a data management parameter rule of the file storage table, and performing recognition and extraction operation based on the file management field on the transaction content text information to obtain a management field parameter set; and constructing a data storage item according to the management field parameter set, and storing the data storage item according to a preset data storage rule. The intelligent management efficiency of enterprise asset data can be improved.

Description

Technical Field

[0001] The present invention relates to the field of asset data management technology, and in particular to an intelligent management method, device, equipment and computer-readable storage medium based on enterprise asset data. Background Art

[0002] As enterprises accelerate their digital transformation, the demand for data management is growing, especially in the field of enterprise asset data management. Traditional data management systems often face problems such as low data processing efficiency and insufficient data security. These challenges severely limit enterprises' capabilities in asset optimization and decision support.

[0003] Under the traditional asset data management model, data is usually uploaded in batches and stored uniformly after processing, but there is a lack of effective mechanisms to distinguish the relationship between new data and existing historical data, especially when historical records need to be supplemented or corrected. Summary of the invention

[0004] The present invention provides an intelligent management method, device, equipment and storage medium based on enterprise asset data. Its main purpose is to provide an intelligent management method for enterprise asset data that can automatically classify transaction data and automatically supplement or correct related historical data records according to specific keywords in the transaction content.

[0005] To achieve the above objectives, the present invention provides an intelligent management method based on enterprise asset data, comprising:

[0006] Identify the file type of the pre-built transaction data to be uploaded, call the pre-built file content recognition service according to the file type, and use the file content recognition service to extract the content of the transaction data to be uploaded to obtain the transaction content text information;

[0007] Performing a file classification operation on the transaction content text information based on matching of a preset keyword table to obtain a transaction data classification result, and querying a file storage table corresponding to the transaction data classification result;

[0008] According to the data management parameter rule of the file storage table, query the file management field corresponding to the transaction data classification result, and perform identification and extraction operations based on the file management field on the transaction content text information to obtain a management field parameter set;

[0009] A data storage item is constructed according to the management field parameter set, and the data storage item is stored in the file storage table according to a preset data storage rule.

[0010] Optionally, the performing a file classification operation on the transaction content text information based on matching of a preset keyword table to obtain a transaction data classification result includes:

[0011] Performing a string matching operation based on a preset keyword table on the transaction content text information to obtain the first keyword score set, and performing a text feature extraction operation on the transaction content text information, and performing a relevance matching operation based on the preset keyword table on the extracted text features to obtain a second keyword score set;

[0012] Performing positional addition and average calculation on the first keyword score set and the second keyword score set to obtain a keyword score set corresponding to the transaction content text information, and performing score sum calculation based on a preset target type on the keyword score set to obtain a total score of each target type, where the target type is a grouping type of each keyword in the preset keyword table;

[0013] The target type corresponding to the highest total score is extracted as the transaction data classification result of the transaction content text information.

[0014] Optionally, storing the data storage item in the file storage table according to a preset data storage rule includes:

[0015] Identify an identification field in the data storage item and obtain a timestamp;

[0016] Determining whether the identification field appears in the file storage table;

[0017] When the identification field does not appear in the file storage table, sequentially storing the data storage items in the file storage table according to the timestamp;

[0018] When the identification field appears in the file storage table, historical storage data related to the identification field in the file storage table is extracted, and the historical storage data is updated and stored using the data storage item, and the timestamp is recorded.

[0019] Optionally, before identifying the file type of the pre-built transaction data to be uploaded, the method further includes:

[0020] Get real-time upload status;

[0021] When the upload status is to be uploaded, receiving the transaction data to be uploaded sent by the user and the preset timing service, wherein the transaction data to be uploaded may be a compressed file of multiple data;

[0022] When the upload status is parsing, new transaction data to be uploaded cannot be uploaded;

[0023] When the upload status is uploaded, the upload status is changed to pending upload according to a preset time interval.

[0024] Optionally, after storing the data storage item in the file storage table according to a preset data storage rule, the method further includes:

[0025] Encrypting the sensitive fields in the data storage item to obtain encrypted fields;

[0026] When the user queries the encrypted field, the role information of the user is identified, and when the role information belongs to a preset advanced role, the encrypted field is decrypted and displayed.

[0027] Optionally, calling a pre-built file content identification service according to the file type includes:

[0028] Perform binary classification judgment on the file type based on image category and text category;

[0029] When the file type is a picture, a text content recognition service based on OCR scanning is called;

[0030] When the file type is text, a text content recognition service based on text extraction is called.

[0031] In order to solve the above problems, the present invention also provides an intelligent management device based on enterprise asset data, the device comprising:

[0032] A data text recognition module is used to identify the file type of the pre-built transaction data to be uploaded, call the pre-built file content recognition service according to the file type, and use the file content recognition service to extract the content of the transaction data to be uploaded to obtain the transaction content text information;

[0033] A data matching and classification module is used to perform a file classification operation on the transaction content text information based on a preset keyword table matching, obtain a transaction data classification result, and query a file storage table corresponding to the transaction data classification result;

[0034] A management field extraction module, used to query the file management field corresponding to the transaction data classification result according to the data management parameter rule of the file storage table, and perform an identification and extraction operation based on the file management field on the transaction content text information to obtain a management field parameter set;

[0035] The data storage module is used to construct a data storage item according to the management field parameter set, and store the data storage item in the file storage table according to a preset data storage rule.

[0036] Optionally, the performing a file classification operation on the transaction content text information based on matching of a preset keyword table to obtain a transaction data classification result includes:

[0037] Performing a string matching operation based on a preset keyword table on the transaction content text information to obtain the first keyword score set, and performing a text feature extraction operation on the transaction content text information, and performing a relevance matching operation based on the preset keyword table on the extracted text features to obtain a second keyword score set;

[0038] Performing positional addition and average calculation on the first keyword score set and the second keyword score set to obtain a keyword score set corresponding to the transaction content text information, and performing score sum calculation based on a preset target type on the keyword score set to obtain a total score of each target type, where the target type is a grouping type of each keyword in the preset keyword table;

[0039] The target type corresponding to the highest total score is extracted as the transaction data classification result of the transaction content text information.

[0040] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0041] at least one processor; and,

[0042] a memory communicatively connected to the at least one processor; wherein,

[0043] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned intelligent management method based on enterprise asset data.

[0044] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one computer program is stored. The at least one computer program is executed by a processor in an electronic device to implement the above-mentioned intelligent management method based on enterprise asset data.

[0045] The method of the embodiment of the present invention first identifies the file type of the transaction data to be uploaded, and then calls the corresponding content recognition service, such as OCR scanning for image files and text extraction services for text files. This automated processing significantly improves the efficiency and accuracy of data entry; then automatically classifies the transaction data, and can automatically update or correct related historical data records based on specific keywords in the transaction content. This mechanism effectively solves the need for data update, reduces the storage of duplicate data, and improves the overall quality and availability of data. Therefore, the embodiment of the present invention provides an intelligent management method, device, equipment and storage medium based on enterprise asset data, which can automatically classify transaction data and automatically supplement or correct related historical data records based on specific keywords in the transaction content. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A schematic diagram of a process flow of an intelligent management method based on enterprise asset data provided by an embodiment of the present invention;

[0047] Figure 2 A detailed flow chart of a step in an intelligent management method based on enterprise asset data provided by an embodiment of the present invention;

[0048] Figure 3 A functional module diagram of an intelligent management device based on enterprise asset data provided by an embodiment of the present invention;

[0049] Figure 4 A schematic diagram of the structure of an electronic device for implementing the intelligent management method based on enterprise asset data provided by one embodiment of the present invention.

[0050] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0052] The embodiment of the present application provides an intelligent management method based on enterprise asset data. In the embodiment of the present application, the execution subject of the intelligent management method based on enterprise asset data includes but is not limited to at least one of the electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the intelligent management method based on enterprise asset data can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0053] Reference Figure 1 FIG. 1 is a flow chart of an intelligent management method based on enterprise asset data provided by an embodiment of the present invention. In this embodiment, the intelligent management method based on enterprise asset data includes:

[0054] S1. Identify the file type of pre-built transaction data to be uploaded, call a pre-built file content recognition service according to the file type, and use the file content recognition service to extract content from the transaction data to be uploaded to obtain transaction content text information.

[0055] In the embodiment of the present invention, the file types can be divided into picture type and text type. The picture type includes file types with text suffixes such as pdf, jpg and png, while the text type includes file types with file suffixes such as word and excel.

[0056] In detail, in the embodiment of the present invention, calling a pre-built file content identification service according to the file type includes:

[0057] Perform binary classification judgment on the file type based on image category and text category;

[0058] When the file type is a picture, a text content recognition service based on OCR scanning is called;

[0059] When the file type is text, a text content recognition service based on text extraction is called.

[0060] The file content recognition service is a service for extracting text from a file, and the extraction method varies according to the file type. For example, OCR scanning technology can be used to extract text from images, while direct text extraction can be used to extract text from text files.

[0061] The OCR scanning technology refers to analyzing optical characters in image files (such as scanned documents, photos, or frames obtained from image capture devices), recognizing and converting them into corresponding electronic text forms.

[0062] Furthermore, in the embodiment of the present invention, before identifying the file type of the pre-built transaction data to be uploaded, the method further includes:

[0063] Get real-time upload status;

[0064] When the upload status is to be uploaded, receiving the transaction data to be uploaded sent by the user and the preset timing service, wherein the transaction data to be uploaded may be a compressed file of multiple data;

[0065] When the upload status is parsing, new transaction data to be uploaded cannot be uploaded;

[0066] When the upload status is uploaded, the upload status is changed to pending upload according to a preset time interval.

[0067] The present invention sets an upload status, and the upload status includes to be uploaded, being parsed, and uploaded. Specifically, the embodiment of the present invention can package the transaction data to be uploaded through a preset timing service (for example, a service that uploads data once a week) or manually, and then perform intelligent management. During the intelligent management process, the upload status will be displayed as being parsed. In order to avoid data dislocation, new transaction data to be uploaded is not allowed to be uploaded at this time; and when the intelligent management of the transaction data to be uploaded is completed, it will be displayed as uploaded, and after a preset time interval, such as 5s, it will be converted to the state of to be uploaded.

[0068] S2. Perform a file classification operation on the transaction content text information based on matching of a preset keyword table to obtain a transaction data classification result, and query a file storage table corresponding to the transaction data classification result.

[0069] Among them, the preset keyword table includes invoice keywords and contract keywords; the invoice keywords include invoice, ordinary invoice, invoice code, invoice number, invoice date, and verification code; the contract keywords include contract, principal, trustee, contract amount, and service fee.

[0070] For details, refer to Figure 2 As shown, in the embodiment of the present invention, the file classification operation based on matching of a preset keyword table is performed on the transaction content text information to obtain the transaction data classification result, including:

[0071] S21, performing a string matching operation based on a preset keyword table on the transaction content text information to obtain the first keyword score set, performing a text feature extraction operation on the transaction content text information, and performing a relevance matching operation based on the preset keyword table on the extracted text features to obtain a second keyword score set;

[0072] S22, performing positional addition and average calculation on the first keyword score set and the second keyword score set to obtain a keyword score set corresponding to the transaction content text information, and performing score sum calculation based on a preset target type on the keyword score set to obtain a total score of each target type, where the target type is a grouping type of each keyword in the preset keyword table;

[0073] S23: extracting the target type corresponding to the highest total score as the transaction data classification result of the transaction content text information.

[0074] In the embodiment of the present invention, the keywords belonging to the keyword table are searched by string matching to obtain a first keyword score set [where each keyword has a score of 1]; then the relevance distance between each word and the words in each keyword table is calculated by a cluster distance algorithm, and a second keyword score set is obtained by normalization operation [the relevance score of each keyword may be less than 1]. Then, the keyword score set is obtained by summing and averaging.

[0075] In the embodiment of the present invention, the keyword table is divided into three categories: contracts, invoices, and others. The highest score type corresponding to the transaction content text information can be calculated as the transaction data classification result. Among them, the classification in the keyword table can change according to the increase or change of the enterprise business type.

[0076] It should be known that different data storage items contain different key information. Different key information is suitable for management in different ways to improve data management and update efficiency. For example, the field types, contents and management methods of product transaction order data and financing orders are definitely different.

[0077] Therefore, the present invention needs to query the file storage table corresponding to the transaction data classification result.

[0078] S3. According to the data management parameter rules of the file storage table, query the file management field corresponding to the transaction data classification result, and perform identification and extraction operations on the transaction content text information based on the file management field to obtain a management field parameter set.

[0079] In the embodiment of the present invention, the data management parameter rules include value configuration rules for various fields such as order number, buyer name, financing amount, financing due date, and receiving bank account.

[0080] The present invention can perform keyword query and filling through a pre-trained artificial intelligence model, such as a neural network model based on natural language processing, to obtain a management field parameter set.

[0081] S4. Construct a data storage item according to the management field parameter set, and store the data storage item in the file storage table according to a preset data storage rule.

[0082] In the embodiment of the present invention, each file management field in the management field parameter set is arranged according to the format of the file storage table rule to construct data storage items [serial number, order number, buyer's name, seller's name, financing amount...receiving bank account].

[0083] Furthermore, the data storage rule means that when the new data storage item is new data, it is directly stored in sequence, and when the data storage item is supplementary data of old data, the new data storage item is used to update the old data.

[0084] In detail, in an embodiment of the present invention, storing the data storage item in the file storage table according to a preset data storage rule includes:

[0085] Identify an identification field in the data storage item and obtain a timestamp;

[0086] Determining whether the identification field appears in the file storage table;

[0087] When the identification field does not appear in the file storage table, sequentially storing the data storage items in the file storage table according to the timestamp;

[0088] When the identification field appears in the file storage table, historical storage data related to the identification field in the file storage table is extracted, and the historical storage data is updated and stored using the data storage item, and the timestamp is recorded.

[0089] The timestamp is a coded information, indicating the exact date and time when a specific event or data record occurs. The present invention records the time when data is uploaded or updated through the timestamp.

[0090] In the embodiment of the present invention, the identification field refers to [Order Number].

[0091] Specifically, the present invention constructs a hash value corresponding to each [order number] (time complexity o(1)) to obtain a hash table, thereby realizing a quick query on whether the order number is repeated.

[0092] When the order number is repeated, the old data storage item can be updated according to the new data storage item, wherein the fields in the data storage item can be added or not added. When a field is not added, when the data is updated, the data in the old data storage item is directly updated with the data in the new data storage item; when a field is added, the data in the new data storage item can be added to the old data storage item, and the field can be automatically sorted.

[0093] In addition, in another embodiment of the present invention, after storing the data storage item in the file storage table according to the preset data storage rule, the method further includes:

[0094] Encrypting the sensitive fields in the data storage item to obtain encrypted fields;

[0095] When the user queries the encrypted field, the role information of the user is identified, and when the role information belongs to a preset advanced role, the encrypted field is decrypted and displayed.

[0096] In the embodiment of the present invention, sensitive information monitoring (generally several pre-set fields), such as [receiving bank account number, financing amount, seller company name, etc.], can be used to implement incomplete display of user operations and increase data security.

[0097] The method of the embodiment of the present invention first identifies the file type of the transaction data to be uploaded, and then calls the corresponding content recognition service, such as OCR scanning for image files and text extraction services for text files. This automated processing significantly improves the efficiency and accuracy of data entry; then automatically classifies the transaction data, and can automatically update or correct related historical data records based on specific keywords in the transaction content. This mechanism effectively solves the need for data update, reduces the storage of duplicate data, and improves the overall quality and availability of data. Therefore, the embodiment of the present invention provides an intelligent management method based on enterprise asset data, which can automatically classify transaction data and automatically supplement or correct related historical data records based on specific keywords in the transaction content.

[0098] like Figure 3 1 is a functional module diagram of an intelligent management device based on enterprise asset data provided by an embodiment of the present invention.

[0099] The intelligent management device 100 based on enterprise asset data of the present invention can be installed in an electronic device. According to the functions to be implemented, the intelligent management device 100 based on enterprise asset data can include a data text recognition module 101, a data matching classification module 102, a management field extraction module 103 and a data storage module 104. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0100] In this embodiment, the functions of each module / unit are as follows:

[0101] The data text recognition module 101 is used to identify the file type of the pre-built transaction data to be uploaded, call the pre-built file content recognition service according to the file type, and use the file content recognition service to extract the content of the transaction data to be uploaded to obtain the transaction content text information;

[0102] The data matching and classification module 102 is used to perform a file classification operation on the transaction content text information based on matching of a preset keyword table, obtain a transaction data classification result, and query a file storage table corresponding to the transaction data classification result;

[0103] The management field extraction module 103 is used to query the file management field corresponding to the transaction data classification result according to the data management parameter rule of the file storage table, and perform an identification and extraction operation based on the file management field on the transaction content text information to obtain a management field parameter set;

[0104] The data storage module 104 is used to construct a data storage item according to the management field parameter set, and store the data storage item in the file storage table according to a preset data storage rule.

[0105] In detail, each module described in the intelligent management device 100 based on enterprise asset data in the embodiment of the present application is used in the same manner as described above. Figure 1 to Figure 2 The intelligent management method based on enterprise asset data described in the above is similar to the technical means and can produce the same technical effects, so I will not go into details here.

[0106] like Figure 4 , which is a schematic diagram of the structure of an electronic device 1 for implementing an intelligent management method based on enterprise asset data provided by an embodiment of the present invention.

[0107] The electronic device 1 may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as an intelligent management program based on enterprise asset data.

[0108] In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 10 is the control core (ControlUnit) of the electronic device 1, and uses various interfaces and lines to connect various components of the entire electronic device, and executes various functions of the electronic device and processes data by running or executing programs or modules stored in the memory 11 (for example, executing intelligent management programs based on enterprise asset data, etc.), and calling data stored in the memory 11.

[0109] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (for example, SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 may also be an external storage device of an electronic device, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the memory 11 may also include both an internal storage unit of the electronic device and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device, such as the code of the intelligent management program based on enterprise asset data, but also can be used to temporarily store data that has been output or is to be output.

[0110] The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0111] The communication interface 13 is used for communication between the above-mentioned electronic device 1 and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0112] Figure 4 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 4 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0113] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0114] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0115] The intelligent management program based on enterprise asset data stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0116] Identify the file type of the pre-built transaction data to be uploaded, call the pre-built file content recognition service according to the file type, and use the file content recognition service to extract the content of the transaction data to be uploaded to obtain the transaction content text information;

[0117] Performing a file classification operation on the transaction content text information based on matching of a preset keyword table to obtain a transaction data classification result, and querying a file storage table corresponding to the transaction data classification result;

[0118] According to the data management parameter rule of the file storage table, query the file management field corresponding to the transaction data classification result, and perform identification and extraction operations based on the file management field on the transaction content text information to obtain a management field parameter set;

[0119] A data storage item is constructed according to the management field parameter set, and the data storage item is stored in the file storage table according to a preset data storage rule.

[0120] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0121] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0122] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0123] Identify the file type of the pre-built transaction data to be uploaded, call the pre-built file content recognition service according to the file type, and use the file content recognition service to extract the content of the transaction data to be uploaded to obtain the transaction content text information;

[0124] Performing a file classification operation on the transaction content text information based on matching of a preset keyword table to obtain a transaction data classification result, and querying a file storage table corresponding to the transaction data classification result;

[0125] According to the data management parameter rule of the file storage table, query the file management field corresponding to the transaction data classification result, and perform identification and extraction operations based on the file management field on the transaction content text information to obtain a management field parameter set;

[0126] A data storage item is constructed according to the management field parameter set, and the data storage item is stored in the file storage table according to a preset data storage rule.

[0127] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0128] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0129] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0130] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0131] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any attached figure mark in the claims should not be regarded as limiting the claims involved.

[0132] The blockchain referred to in this invention is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0133] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0134] In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the system claim can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0135] Finally, it should be noted that 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, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. An intelligent management method based on enterprise asset data, characterized in that: The method comprises: Identify the file type of the pre-built transaction data to be uploaded, call the pre-built file content recognition service according to the file type, and use the file content recognition service to extract the content of the transaction data to be uploaded to obtain the transaction content text information; Performing a file classification operation on the transaction content text information based on matching of a preset keyword table to obtain a transaction data classification result, and querying a file storage table corresponding to the transaction data classification result; According to the data management parameter rule of the file storage table, query the file management field corresponding to the transaction data classification result, and perform identification and extraction operations based on the file management field on the transaction content text information to obtain a management field parameter set; A data storage item is constructed according to the management field parameter set, and the data storage item is stored in the file storage table according to a preset data storage rule.

2. The intelligent management method based on enterprise asset data according to claim 1, characterized in that: The file classification operation based on matching of a preset keyword table is performed on the transaction content text information to obtain a transaction data classification result, including: Performing a string matching operation based on a preset keyword table on the transaction content text information to obtain the first keyword score set, and performing a text feature extraction operation on the transaction content text information, and performing a relevance matching operation based on the preset keyword table on the extracted text features to obtain a second keyword score set; Performing positional addition and average calculation on the first keyword score set and the second keyword score set to obtain a keyword score set corresponding to the transaction content text information, and performing score sum calculation based on a preset target type on the keyword score set to obtain a total score of each target type, where the target type is a grouping type of each keyword in the preset keyword table; The target type corresponding to the highest total score is extracted as the transaction data classification result of the transaction content text information.

3. The intelligent management method based on enterprise asset data according to claim 1, characterized in that: The storing the data storage item into the file storage table according to a preset data storage rule includes: Identify an identification field in the data storage item and obtain a timestamp; Determining whether the identification field appears in the file storage table; When the identification field does not appear in the file storage table, sequentially storing the data storage items in the file storage table according to the timestamp; When the identification field appears in the file storage table, historical storage data related to the identification field in the file storage table is extracted, and the historical storage data is updated and stored using the data storage item, and the timestamp is recorded.

4. The intelligent management method based on enterprise asset data according to claim 1, characterized in that: Before identifying the file type of the pre-built transaction data to be uploaded, the method further includes: Get real-time upload status; When the upload status is to be uploaded, receiving the transaction data to be uploaded sent by the user and the preset timing service, wherein the transaction data to be uploaded may be a compressed file of multiple data; When the upload status is parsing, new transaction data to be uploaded cannot be uploaded; When the upload status is uploaded, the upload status is changed to pending upload according to a preset time interval.

5. The intelligent management method based on enterprise asset data according to claim 1, characterized in that: After storing the data storage item in the file storage table according to the preset data storage rule, the method further includes: Encrypting the sensitive fields in the data storage item to obtain encrypted fields; When the user queries the encrypted field, the role information of the user is identified, and when the role information belongs to a preset advanced role, the encrypted field is decrypted and displayed.

6. The intelligent management method based on enterprise asset data according to claim 1, characterized in that: The calling of a pre-built file content identification service according to the file type includes: Perform binary classification judgment on the file type based on image category and text category; When the file type is a picture, a text content recognition service based on OCR scanning is called; When the file type is text, a text content recognition service based on text extraction is called.

7. An intelligent management device based on enterprise asset data, characterized in that: The device comprises: A data text recognition module is used to identify the file type of the pre-built transaction data to be uploaded, call the pre-built file content recognition service according to the file type, and use the file content recognition service to extract the content of the transaction data to be uploaded to obtain the transaction content text information; A data matching and classification module is used to perform a file classification operation on the transaction content text information based on a preset keyword table matching, obtain a transaction data classification result, and query a file storage table corresponding to the transaction data classification result; A management field extraction module, used to query the file management field corresponding to the transaction data classification result according to the data management parameter rule of the file storage table, and perform an identification and extraction operation based on the file management field on the transaction content text information to obtain a management field parameter set; The data storage module is used to construct a data storage item according to the management field parameter set, and store the data storage item in the file storage table according to a preset data storage rule.

8. The intelligent management device based on enterprise asset data as claimed in claim 7, characterized in that: The file classification operation based on matching of a preset keyword table is performed on the transaction content text information to obtain a transaction data classification result, including: Performing a string matching operation based on a preset keyword table on the transaction content text information to obtain the first keyword score set, and performing a text feature extraction operation on the transaction content text information, and performing a relevance matching operation based on the preset keyword table on the extracted text features to obtain a second keyword score set; Performing positional addition and average calculation on the first keyword score set and the second keyword score set to obtain a keyword score set corresponding to the transaction content text information, and performing score sum calculation based on a preset target type on the keyword score set to obtain a total score of each target type, where the target type is a grouping type of each keyword in the preset keyword table; The target type corresponding to the highest total score is extracted as the transaction data classification result of the transaction content text information.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the intelligent management method based on enterprise asset data as described in any one of claims 1 to 6.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the intelligent management method based on enterprise asset data as described in any one of claims 1 to 6 is implemented.

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