Supply chain financial service data processing method and device, equipment and storage medium

Abstract

The invention relates to the technical field of financial science and technology, and provides a data processing method, device and equipment for a supply chain financial service and a storage medium, and the method comprises the steps: analyzing a service message of the supply chain financial service to obtain message content; the content of the message is converted into a DIKWP resource body; the DIKWP resource body is a structured representation of the message content; generating a DIKWP map based on the map structure of the DIKWP resource body; and searching the DIKWP map according to a mapping rule of a message field and a database field, and enabling matched data to fall into a database table. According to the embodiment of the invention, the service message processing and data storage efficiency in the supply chain financial service can be improved.

Description

Technical Field

[0001] This specification relates to the field of financial technology, and in particular to a data processing method, device, equipment and storage medium for supply chain finance business. Background Art

[0002] Supply Chain Finance (SCF) is a business model in which banks manage the capital flow, logistics and information flow of upstream and downstream small and medium-sized enterprises around core enterprises and provide financial services to core enterprises by controlling risks. In the supply chain finance business scenario, it generally involves multiple participants (such as core enterprises, suppliers, distributors, funding parties, etc.). When the systems of different participants interact with each other, it is often the docking of interfaces. It takes at least a few interfaces to dozens of interfaces to complete a business. Due to the differences and diversity of interfaces, the efficiency of processing business messages and data storage is low. Summary of the invention

[0003] The purpose of the embodiments of this specification is to provide a data processing method, device, equipment and storage medium for supply chain finance business, so as to improve the processing efficiency of business messages and data storage in supply chain finance business.

[0004] To achieve the above objectives, on the one hand, the embodiments of this specification provide a data processing method for supply chain finance business, including:

[0005] Parse the business message of supply chain finance business to obtain the message content;

[0006] Converting the message content into a DIKWP resource body; the DIKWP resource body is a structured representation of the message content;

[0007] Generate a DIKWP graph based on the graph structure of the DIKWP resource body;

[0008] The DIKWP map is searched according to the mapping rules between message fields and database fields, and the matched data is put into the database table.

[0009] In the data processing method for supply chain finance business in the embodiment of this specification, the message content includes:

[0010] Message metadata, message field information, interface information, service information and system information.

[0011] In the data processing method for supply chain finance business of the embodiment of this specification, the message content is converted into a DIKWP resource body, including:

[0012] Interpreting the message metadata as data of a DIKWP model, and converting the data of the DIKWP model into a data graph;

[0013] Interpreting the message field information as information of a DIKWP model, and converting the information of the DIKWP model into an information graph;

[0014] Interpreting the interface information into knowledge of a DIKWP model, and converting the knowledge of the DIKWP model into a knowledge graph;

[0015] interpreting the business information as the wisdom of the DIKWP model, and converting the wisdom of the DIKWP model into a wisdom map;

[0016] Interpreting the system information into the intent of the DIKWP model, and converting the intent of the DIKWP model into an intent graph;

[0017] The data graph, the information graph, the knowledge graph, the wisdom graph and the intention graph are stored in layers from bottom to top to form a DIKWP resource body.

[0018] In the data processing method for supply chain finance business of the embodiment of this specification, searching the DIKWP map according to the mapping rules between message fields and database fields includes:

[0019] Obtain a mapping rule map; the mapping rule map is used to characterize the mapping rules between message fields and database fields, and has the same hierarchical structure as the DIKWP map, and each layer in the mapping rule map is used to characterize the mapping rules of the corresponding layer;

[0020] According to the mapping rules of each layer, the DIKWP map is searched concurrently in layers, and the search accuracy of each layer is obtained accordingly;

[0021] The search results for the DIKWP graph are determined according to the search accuracy of each of the layers.

[0022] In the data processing method for supply chain finance business of the embodiment of this specification, the search results for the DIKWP graph are determined according to the search accuracy of each layer, including:

[0023] Calculating the weighted sum of the search accuracy rates of each of the layers;

[0024] Determining whether the weighted sum reaches a correctness threshold;

[0025] If the weighted sum reaches the threshold, the search result of the DIKWP graph is confirmed to be a hit; otherwise, the search result of the DIKWP graph is confirmed to be a miss.

[0026] In the data processing method for supply chain finance business of the embodiment of this specification, the step of putting the matched data into the database table includes:

[0027] Generate a corresponding SQL command set based on the matched data;

[0028] Execute the SQL command set to put the matched data into the corresponding database table.

[0029] On the other hand, the embodiment of this specification also provides a data processing device for supply chain financial services, including:

[0030] The parsing module is used to parse the business messages of the supply chain finance business and obtain the message content;

[0031] A conversion module, used for converting the message content into a DIKWP resource body; the DIKWP resource body is a structured representation of the message content;

[0032] A generating module, used for generating a DIKWP graph based on the graph structure of the DIKWP resource body;

[0033] The storage module is used to search the DIKWP map according to the mapping rules between the message field and the database field, and put the matched data into the database table.

[0034] On the other hand, an embodiment of the present specification further provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein when the computer program is executed by the processor, the instructions of the above method are executed.

[0035] On the other hand, an embodiment of the present specification further provides a computer storage medium on which a computer program is stored. When the computer program is executed by a processor of a computer device, the instructions of the above method are executed.

[0036] On the other hand, an embodiment of the present specification further provides a computer program product, wherein the computer program product includes a computer program, and when the computer program is executed by a processor of a computer device, the computer program executes instructions of the above method.

[0037] It can be seen from the technical solutions provided in the above embodiments of this specification that in the embodiments of this specification, various business messages of the supply chain financial business can be converted into corresponding DIKWP resource bodies, and a DIKWP graph can be generated based on the graph structure of the DIKWP resource body; on this basis, the DIKWP graph is searched according to the mapping rules between the message fields and the database fields, and the matched data is automatically entered into the database table; thereby avoiding the processing complexity caused by the differences and diversity of the interfaces, and improving the processing efficiency of business messages and data entry in the supply chain financial business. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art description. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. In the drawings:

[0039] Figure 1 The purpose of the data processing system for supply chain finance business in some embodiments of this specification is shown;

[0040] Figure 2 A flowchart showing a data processing method for supply chain finance business in some embodiments of this specification;

[0041] Figure 3 Shows Figure 2 A flowchart of converting the message content into a DIKWP resource body in the method shown;

[0042] Figure 4 A schematic diagram showing a process of converting a message into a DIKWP resource body in an exemplary embodiment of this specification is shown;

[0043] Figure 5 A schematic diagram of a DIKWP resource body in an exemplary embodiment of this specification is shown;

[0044] Figure 6 Shows Figure 2 A flowchart of searching the DIKWP map according to the mapping rules between message fields and database fields in the method shown;

[0045] Figure 7 Shows Figure 2 A flowchart of determining the search results for the DIKWP graph according to the search accuracy of each layer in the method shown;

[0046] Figure 8A schematic diagram showing a method of determining search results for a DIKWP graph according to the search accuracy of each layer in an exemplary embodiment of the present specification;

[0047] Fig. 9 Shows Figure 2 A flowchart of the method shown in which the matched data is put into a database table;

[0048] Fig.10 A structural block diagram showing a data processing device for supply chain finance services in some embodiments of this specification;

[0049] Fig.11 The structure block diagram of the computer device in some embodiments of the present specification is shown.

[0050] [Description of Reference Numerals]

[0051] 10. Client;

[0052] 20. Server;

[0053] 21. Parsing module;

[0054] 22. Conversion module;

[0055] 23. Generate module;

[0056] 24. Warehouse entry module;

[0057] 1102. Computer equipment;

[0058] 1104. Processor;

[0059] 1106. Memory;

[0060] 1108, driving mechanism;

[0061] 1110, input / output interface;

[0062] 1112. Input device;

[0063] 1114. Output device;

[0064] 1116. Presentation equipment;

[0065] 1118. Graphical user interface;

[0066] 1120. Network interface;

[0067] 1122. Communication link;

[0068] 1124. Communication bus. DETAILED DESCRIPTION

[0069] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0070] Figure 1 A schematic diagram of a data processing system for supply chain finance business in some embodiments of this specification is shown in the figure; the system includes a client 10 and a server 20. The client 10 can send a business message of supply chain finance business to the server; the server 20 can parse the business message of supply chain finance business to obtain the message content; convert the message content into a DIKWP resource body; the DIKWP resource body is a structured representation of the message content; generate a DIKWP graph based on the graph structure of the DIKWP resource body; search the DIKWP graph according to the mapping rules between the message field and the database field, and put the matched data into the database table. Through the embodiments of this specification, the processing of business messages and the efficiency of data storage in the supply chain finance business can be improved.

[0071] In some embodiments of the present specification, the client 10 may be a self-service terminal device, a mobile terminal (i.e., a smart phone), a display, a desktop computer, a tablet computer, a laptop computer, a digital assistant, or a smart wearable device, etc. Among them, the smart wearable device may include a smart bracelet, a smart watch, smart glasses, or a smart helmet, etc. Of course, the client 10 is not limited to the above-mentioned electronic devices with a certain entity, and it may also be software running in the above-mentioned electronic devices.

[0072] In some embodiments of the present specification, the server 20 may be an electronic device with computing and network interaction functions; or may be software running in the electronic device and providing business logic for data processing and network interaction.

[0073] In addition, it should be noted that Figure 1 What is shown is only an application environment provided by this specification. In actual application, there may be multiple clients 10 and multiple servers 20, and this specification does not impose any limitation.

[0074] This specification embodiment provides a data processing method for supply chain financial services, which can be applied to the above-mentioned service side, refer to Figure 2 As shown, in some embodiments of this specification, the data processing method of supply chain finance business may include the following steps:

[0075] Step 201: parse the business message of the supply chain finance business to obtain the message content.

[0076] Step 202: Convert the message content into a DIKWP resource body; the DIKWP resource body is a structured representation of the message content.

[0077] Step 203: Generate a DIKWP graph based on the graph structure of the DIKWP resource body.

[0078] Step 204: search the DIKWP graph according to the mapping rules between message fields and database fields, and put the matched data into the database table.

[0079] In the embodiments of the present specification, various business messages of the supply chain finance business can be converted into corresponding DIKWP resource bodies, and a DIKWP graph can be generated based on the graph structure of the DIKWP resource body; on this basis, the DIKWP graph is searched according to the mapping rules between the message fields and the database fields, and the matched data is automatically entered into the database table; thereby avoiding the processing complexity caused by the differences and diversity of interfaces, and improving the processing efficiency of business messages and data entry in the supply chain finance business.

[0080] In some embodiments of the present specification, an adaptively integrated scalable Internet access network can be pre-built before implementation to support operator dedicated lines, VPN networks, SOCKET technologies, etc. to achieve secure Internet access; and an adaptively integrated client-server data transmission service can be built to achieve data message transmission between institutional systems.

[0081] In some embodiments of the present specification, the business message of the supply chain finance business can be a request message or a response message. When parsing the message, appropriate parsing tools or libraries can be used to extract the required information according to different message types (such as TCP / IP messages, HTTP messages, etc.). For example, in Python, the scapy library can be used to parse network messages and extract the required information such as source IP address, destination IP address, source port, destination port, protocol type, etc. In other embodiments of the present specification, before parsing the message, data preprocessing (such as data cleaning, removal of irrelevant characters or filling of missing values) can also be performed to ensure that the message data is clean and in a uniform format.

[0082] In some embodiments of the present specification, parsing a message may obtain message metadata, message field information, interface information, service information, and system information, etc. Among them, the message metadata may include basic information such as source address, destination address, message length, and protocol type. Message field information may include, for example, field name, field length, field type, etc.; interface information may include, for example, interface name, interface transmission mode, number of interface fields, and interface service meaning; service information may include service name and service identifier involved in the message, etc. System information may include system name and system identifier of the sender (source) and receiver (destination) involved in the message, etc.

[0083] The DIKWP model is a cognitive framework that describes the networked relationship between data, information, knowledge, wisdom, and purpose; it is a networked model that can vividly describe the cognitive process. In the DIKWP model, data (D): represents the original facts or observations identified and classified by the cognitive system. Information (I): forms a meaningful data set through semantic integration and differentiation. Knowledge (K): a structured and complete information set that emphasizes the systematicness and integrity of knowledge. Wisdom (W): knowledge-based decision-making and ethical alignment, emphasizing decision-making and ethical judgment. Purpose (P): goal-oriented behavior and decision-making that guides and shapes the transformation of other components.

[0084] refer to Figure 3 As shown, in some embodiments of this specification, converting the message content into a DIKWP resource body may include the following steps:

[0085] Step 301: interpret the message metadata as data of the DIKWP model, and convert the data of the DIKWP model into a data graph.

[0086] Interpreting the message metadata as data of the DIKWP model means: using the message metadata as data of the DIKWP model (D).

[0087] Step 302: interpret the message field information as information of the DIKWP model, and convert the information of the DIKWP model into an information graph.

[0088] Interpreting the message field information as information of the DIKWP model means: interpreting the message field information as information of the DIKWP model (I).

[0089] Step 303: interpret the interface information as knowledge of the DIKWP model, and convert the knowledge of the DIKWP model into a knowledge graph.

[0090] Interpreting the interface information as knowledge of the DIKWP model means: taking the interface information as knowledge (K) of the DIKWP model.

[0091] Step 304: interpret the business information as the wisdom of the DIKWP model, and convert the wisdom of the DIKWP model into a wisdom graph.

[0092] Interpreting the business information as the wisdom of the DIKWP model means: using the business information as the wisdom (W) of the DIKWP model.

[0093] Step 305: interpret the system information as the intent of the DIKWP model, and convert the intent of the DIKWP model into an intent graph.

[0094] Interpreting the system information as the intention of the DIKWP model means: interpreting the system information as the intention of the DIKWP model (P).

[0095] There is no dependency between steps 301 to 305 , and no execution order requirement. They can be executed asynchronously and concurrently or in any order.

[0096] Step 306: The data graph, the information graph, the knowledge graph, the wisdom graph, and the intention graph are stored in layers from bottom to top to form a DIKWP resource body.

[0097] In the embodiments of this specification, the structured representation of the DIKWP resource body message is a resource organization form with business meaning. In the embodiments of this specification, by converting the message into a hierarchical DIKWP resource body, it can not only better adapt to the docking of different systems and different businesses, but also reduce the scale of traversal search when the data is subsequently put into the database table, improve the efficiency of traversal search, and facilitate message understanding.

[0098] For each message, it can be converted into a DIKWP resource body. In some embodiments of the present specification, the conversion process of converting a message into a DIKWP resource body can be as follows: Figure 4 shown. Figure 5 A schematic diagram of a DIKWP resource body obtained in an exemplary embodiment of this specification is shown; Figure 5 In the diagram, there are five layers from top to bottom: intention map, wisdom map, knowledge map, information map and data map.

[0099] In some embodiments of the present specification, generating a DIKWP graph based on the graph structure of the DIKWP resource body means: constructing a corresponding DIKWP graph based on the graph structure of the DIKWP resource body. When constructing a DIKWP graph, you can first define entity types, entity attributes, and relationship types, and then construct entity nodes and relationship edges. Among them, entity types may include, for example, interfaces, fields, methods, systems, services, etc. Entity attributes may include, for example, the version, creation time, description, etc. of the interface; the type, whether it is required, description, etc. of the field; the HTTP method, URL, description, etc. of the method. Relationship types may include, for example:

[0100] Interfaces and methods: Interfaces and methods are associated through the hasMethod relationship.

[0101] Interface and field: The interface and field are associated through the hasField relationship.

[0102] Fields and Types: Associate fields and their types through the isTypeOf relationship.

[0103] Interface and system: The usedIn relationship associates the interface with the used system or service.

[0104] Interface and interface: The inheritance or implementation relationship of interfaces is represented by the extendsFrom or implements relationship.

[0105] In some embodiments of this specification, after constructing the DIKWP graph, a knowledge graph tool (such as Neo4j, Dexie.js, Anchore, etc.) can be used to visualize and query the DIKWP graph. For example, query all interfaces that use a specific system, or find all interfaces related to a specific field.

[0106] In some embodiments of this specification, after generating a DIKWP graph based on the graph structure of the DIKWP resource body, an interface-related business database table may also be generated, and fields and their attributes may be stored in the form of a knowledge graph. The business database table may include, for example, an interface information table (Interfaces), an interface field table (Fields), and an interface method table (Methods). Among them:

[0107] The interface information table (Interfaces) includes:

[0108] interface_id (INT): primary key that uniquely identifies each interface.

[0109] name (VARCHAR): the name of the interface.

[0110] description(TEXT): Detailed description of the interface.

[0111] version (VARCHAR): interface version.

[0112] created_at(DATETIME): creation time.

[0113] updated_at(DATETIME): Last updated time.

[0114] The interface field table (Fields) includes:

[0115] field_id (INT): primary key, uniquely identifies each field.

[0116] interface_id (INT): foreign key associated with the interface_id of the Interfaces table.

[0117] name (VARCHAR): field name.

[0118] type (VARCHAR): field type (for example: string, integer, date, etc.).

[0119] description(TEXT): Description of the field.

[0120] required(BOOLEAN): Whether the field is required.

[0121] created_at(DATETIME): creation time.

[0122] updated_at(DATETIME): The time when the data was last updated.

[0123] The interface method table (Methods) includes:

[0124] method_id (INT): primary key, uniquely identifies each method.

[0125] interface_id (INT): foreign key associated with the interface_id of the Interfaces table.

[0126] http_method(VARCHAR): HTTP method (GET, POST, PUT, DELETE, etc.) url(VARCHAR): Request URL.

[0127] description (TEXT): Method description.

[0128] created_at(DATETIME): creation time.

[0129] updated_at(DATETIME): The time when the data was last updated.

[0130] refer to Figure 6 As shown, in some embodiments of the present specification, searching the DIKWP map according to the mapping rules between message fields and database fields may include the following steps:

[0131] Step 601, obtain a mapping rule map; the mapping rule map is used to characterize the mapping rules between message fields and database fields, and has the same hierarchical structure as the DIKWP map, and each layer in the mapping rule map is used to characterize the mapping rules of the corresponding layer.

[0132] In some embodiments of the present specification, the mapping rules between message fields and database fields can be represented in the form of a graph structure, i.e., a mapping rule graph. The mapping rule graph is also a hierarchical structure, and has the same hierarchical structure as the DIKWP graph, i.e., the mapping rule graph includes a rule intent graph, a rule wisdom graph, a rule knowledge graph, a rule information graph, and a rule data graph (e.g., Figure 8 shown).

[0133] Among them, the rule intent graph is the mapping rules between message fields and database fields in the intent graph of the DIKWP graph; the rule wisdom graph is the mapping rules between message fields and database fields in the wisdom graph of the DIKWP graph; the rule knowledge graph is the mapping rules between message fields and database fields in the knowledge graph of the DIKWP graph; the rule information graph is the mapping rules between message fields and database fields in the information graph of the DIKWP graph; the rule data graph is the mapping rules between message fields and database fields in the data graph of the DIKWP graph. The specific mapping rules of each layer (or each sub-graph) in the mapping rule graph can be customized as needed.

[0134] Step 602: Perform a layered concurrent search on the DIKWP graph according to the mapping rules of each layer, and obtain the search accuracy of each layer accordingly.

[0135] On the DIKWP graph, the database field obtains the DIKWP resource body related elements through the mapping function (mapping relationship table), and matches the related elements through the Search function.

[0136] In some embodiments of the present specification, the core fields of the mapping relationship table may be as shown in Table 1 below:

[0137] Table 1

[0138] Field Name illustrate Business Type Use the business type field to identify different business scenarios Mapping Table After completing the field mapping, the database table to be stored Mapping table name After completing the field mapping, the name of the database table to be stored Mapping fields Target field after mapping Mapping field names The name of the target field after mapping Original Field The original field that needs to be mapped Original field name The original field name to be mapped Parent primitive fields The field in the previous layer of the original field Is it enabled? Whether to enable the field mapping relationship

[0139] Step 603: Determine the search results for the DIKWP graph according to the search accuracy of each layer.

[0140] Combination Figure 7 As shown, in some embodiments of the present specification, determining the search results for the DIKWP graph according to the search accuracy of each layer may include the following steps:

[0141] Step 701: Calculate the weighted sum of the search accuracy rates of each layer.

[0142] In some embodiments of the present specification, the weighted sum can be calculated according to the weighted sum formula as shown below: S = ∑λ1P+λ2W+λ3K+λ4I+λ5D; wherein S is the weighted sum, P is the business system rule retrieval accuracy based on rule intent graph retrieval, W is the retrieval accuracy obtained based on rule wisdom graph retrieval, K is the retrieval accuracy obtained based on rule knowledge graph retrieval, I is the retrieval accuracy obtained based on rule information graph retrieval, and D is the retrieval accuracy obtained based on rule data graph retrieval; λ1, λ2, λ3, λ4, and λ5 correspond to the weight system of P, W, K, I, and D.

[0143] For example, Figure 8 Taking the mapping rule graph shown as an example, the business system rule retrieval accuracy rate based on rule intent graph retrieval is 50%, the business attribution retrieval accuracy rate based on rule wisdom graph retrieval is 0%, the entity alignment retrieval accuracy rate based on rule knowledge graph retrieval is 80%, the association statistics retrieval accuracy rate based on rule information graph retrieval is 66%, and the structural association retrieval accuracy rate based on rule data graph retrieval is 50%. If the values ​​of λ1, λ2, λ3, λ4, and λ5 are all 0.2, then according to the above weighted summation formula, we have:

[0144] S=0.2×0.5+0.2×0+0.2×0.8+0.2×0.66+0.2×0.5=0.492

[0145] Step 702, determine whether the weighted sum reaches the accuracy threshold; if the weighted sum reaches the threshold, execute step 703; otherwise, execute step 704.

[0146] Step 703: confirm that the search result for the DIKWP graph is a hit.

[0147] Confirming that the search result of the DIKWP map is a hit means that data is matched from the DIKWP map.

[0148] Step 704: confirm that the search result for the DIKWP graph is a miss.

[0149] Confirming that the search result of the DIKWP graph is a miss means that no data is matched from the DIKWP graph. This may be because the business relationship (interconnection relationship) corresponding to the message has not been agreed upon between the interacting parties.

[0150] refer to Fig. 9 As shown, in some embodiments of this specification, the step of putting the matched data into a database table may include the following steps:

[0151] Step 901: Generate a corresponding SQL command set based on the matched data.

[0152] The matched data refers to any one or more operations such as query, insert, create and delete for the database table, and the corresponding SQL command can be generated accordingly. For example, if the matched data is a query operation for the database table, the following SQL statement (i.e., SQL command) can be generated:

[0153] SELECT column 1, column 2, ... FROM table name WHERE condition

[0154] Step 902: Execute the SQL command set to put the matched data into a corresponding database table.

[0155] pass Fig. 9 The step of putting the matched data into the database table can realize the automatic storage of the message data.

[0156] Although the process flows described above include multiple operations that occur in a particular order, it should be clearly understood that the processes may include more or fewer operations, which may be performed sequentially or in parallel (eg, using parallel processors or a multi-threaded environment).

[0157] Corresponding to the above-mentioned data processing method for supply chain finance business, the embodiment of this specification also provides a data processing device for supply chain finance business, which can be configured on the above-mentioned server, referring to Fig.10 As shown, in some embodiments of this specification, the data processing device for supply chain financial services may include:

[0158] The parsing module 21 is used to parse the business message of the supply chain finance business and obtain the message content;

[0159] A conversion module 22, configured to convert the message content into a DIKWP resource body; the DIKWP resource body is a structured representation of the message content;

[0160] A generating module 23, configured to generate a DIKWP graph based on the graph structure of the DIKWP resource body;

[0161] The storage module 24 is used to search the DIKWP map according to the mapping rules between the message fields and the database fields, and put the matched data into the database table.

[0162] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0163] It should be noted that in the embodiments of this specification, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user and fully authorized by all parties, that is, the acquisition, transmission, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0164] The embodiments of this specification also provide a computer device. Fig.11 As shown, in some embodiments of this specification, the computer device 1102 may include one or more processors 1104, such as one or more central processing units (CPUs) or graphics processing units (GPUs), and each processing unit may implement one or more hardware threads. The computer device 1102 may also include any memory 1106, which is used to store any kind of information such as code, settings, data, etc. In a specific embodiment, the computer program on the memory 1106 and can be run on the processor 1104, when the computer program is run by the processor 1104, the instructions of the data processing method of the supply chain financial business described in any of the above embodiments may be executed. Non-limitingly, for example, the memory 1106 may include any one or more combinations of the following: any type of RAM, any type of ROM, flash memory device, hard disk, optical disk, etc. More generally, any memory may use any technology to store information. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent a fixed or removable component of the computer device 1102. In one embodiment, when the processor 1104 executes the associated instructions stored in any memory or combination of memories, the computer device 1102 can perform any operation of the associated instructions. The computer device 1102 also includes one or more drive mechanisms 1108 for interacting with any memory, such as a hard disk drive mechanism, an optical disk drive mechanism, etc.

[0165] The computer device 1102 may also include an input / output interface 1110 (I / O) for receiving various inputs (via input devices 1112) and for providing various outputs (via output devices 1114). A specific output mechanism may include a presentation device 1116 and an associated graphical user interface 1118 (GUI). In other embodiments, the input / output interface 1110 (I / O), input device 1112, and output device 1114 may not be included, and the computer device 1102 may be used as a computer device in a network. The computer device 1102 may also include one or more network interfaces 1120 for exchanging data with other devices via one or more communication links 1122. One or more communication buses 1124 couple the components described above together.

[0166] The communication link 1122 may be implemented in any manner, for example, through a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication link 1122 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc. governed by any protocol or combination of protocols.

[0167] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), computer-readable storage media, and computer program products of some embodiments of the present specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processor to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processor generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0168] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processor to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0169] These computer program instructions can also be loaded onto a computer or other programmable data processor so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0170] In a typical configuration, a computer device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0171] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0172] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computer device. As defined in this specification, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0173] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, the embodiments of this specification may take the form of complete hardware embodiments, complete software embodiments or embodiments combining software and hardware. Moreover, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0174] The present specification embodiments may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present specification embodiments may also be practiced in distributed computing environments where tasks are performed by remote processors connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0175] It should also be understood that in the embodiments of this specification, the term "and / or" is only a description of the association relationship of the associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0176] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0177] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiments of this specification. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0178] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A data processing method for supply chain finance business, characterized in that: include: Parse the business message of supply chain finance business to obtain the message content; Convert the message content into a DIKWP resource body; The DIKWP resource body is a structured representation of the message content; Generate a DIKWP graph based on the graph structure of the DIKWP resource body; The DIKWP map is searched according to the mapping rules between message fields and database fields, and the matched data is put into the database table.

2. The data processing method for supply chain financial services according to claim 1, characterized in that: The message content includes: Message metadata, message field information, interface information, service information and system information.

3. The data processing method for supply chain financial business according to claim 2, characterized in that: Convert the message content into a DIKWP resource body, including: Interpreting the message metadata as data of a DIKWP model, and converting the data of the DIKWP model into a data graph; Interpreting the message field information as information of a DIKWP model, and converting the information of the DIKWP model into an information graph; Interpreting the interface information into knowledge of a DIKWP model, and converting the knowledge of the DIKWP model into a knowledge graph; interpreting the business information as the wisdom of the DIKWP model, and converting the wisdom of the DIKWP model into a wisdom map; Interpreting the system information into the intent of the DIKWP model, and converting the intent of the DIKWP model into an intent graph; The data graph, the information graph, the knowledge graph, the wisdom graph and the intention graph are stored in layers from bottom to top to form a DIKWP resource body.

4. The data processing method for supply chain financial services according to claim 1, characterized in that: Searching the DIKWP graph according to the mapping rules between the message fields and the database fields includes: Obtain a mapping rule map; the mapping rule map is used to characterize the mapping rules between message fields and database fields, and has the same hierarchical structure as the DIKWP map, and each layer in the mapping rule map is used to characterize the mapping rules of the corresponding layer; According to the mapping rules of each layer, the DIKWP map is searched concurrently in layers, and the search accuracy of each layer is obtained accordingly; The search results for the DIKWP graph are determined according to the search accuracy of each of the layers.

5. The data processing method for supply chain financial business according to claim 4, characterized in that: The step of determining the search results for the DIKWP graph according to the search accuracy of each layer comprises: Calculating the weighted sum of the search accuracy rates of each of the layers; Determining whether the weighted sum reaches a correctness threshold; If the weighted sum reaches the threshold, the search result of the DIKWP graph is confirmed to be a hit; otherwise, the search result of the DIKWP graph is confirmed to be a miss.

6. The data processing method for supply chain financial business according to claim 1, characterized in that: The step of putting the matched data into a database table includes: Generate a corresponding SQL command set based on the matched data; Execute the SQL command set to put the matched data into the corresponding database table.

7. A data processing device for supply chain finance business, characterized in that: include: The parsing module is used to parse the business messages of the supply chain finance business and obtain the message content; A conversion module, used for converting the message content into a DIKWP resource body; the DIKWP resource body is a structured representation of the message content; A generating module, used for generating a DIKWP graph based on the graph structure of the DIKWP resource body; The storage module is used to search the DIKWP map according to the mapping rules between the message field and the database field, and put the matched data into the database table.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that: When the computer program is executed by the processor, the computer program executes the instructions of the method according to any one of claims 1 to 6.

9. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor of a computer device, the computer program executes instructions of the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor of a computer device, the computer program executes instructions of the method according to any one of claims 1 to 6.

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