CN110599338A - Transaction data processing method and device, computer equipment and storage medium - Google Patents
Transaction data processing method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The present application relates to the field of data processing, and in particular, to a method and an apparatus for processing transaction data, a computer device, and a storage medium. The method comprises the following steps: acquiring a data entry request, and reading a target entry node from the data entry request; acquiring a chain identification field and a node data template corresponding to a target entry node; extracting chain identification data corresponding to the chain identification field from the data entry request, and searching transaction chain data corresponding to the chain identification data; extracting a chain foundation field corresponding to the node data template from the transaction chain data, and acquiring a node characteristic field corresponding to the node data template; and generating node transaction data according to the chain foundation field and the node characteristic field, and adding the node transaction data into the transaction chain data. By adopting the method, the working efficiency of data processing can be improved.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a transaction data processing method and apparatus, a computer device, and a storage medium.
Background
An asset usually undergoes multiple transactions such as asset subscription and transfer, and when each transaction is performed, related transaction information of the transaction needs to be entered. The input operation of the transaction information needs to be based on the data record of the past transaction data of the capital product, extract the basic information of the capital product from the data record, and integrate the basic information to input the transaction information of the new transaction.
At present, transaction records of each transaction of an asset are stored sporadically, an operator needs to inquire the transaction records by means of memory, multidimensional data records need to be searched in some complex scenes, and the transaction data is inquired and input only by means of memory, so that the transaction data input operation is low in working efficiency and high in error rate.
Disclosure of Invention
In view of the above, it is necessary to provide a transaction data processing method, an apparatus, a computer device and a storage medium capable of improving the data processing efficiency.
A method of transaction data processing, the method comprising:
acquiring a data entry request, and reading a target entry node from the data entry request;
acquiring a chain identification field and a node data template corresponding to the target entry node;
extracting chain identification data corresponding to the chain identification field from the data entry request, and searching transaction chain data corresponding to the chain identification data;
extracting a chain foundation field corresponding to the node data template from the transaction chain data, and acquiring a node characteristic field corresponding to the node data template;
and generating node transaction data according to the chain foundation field and the node characteristic field, and adding the node transaction data into the transaction chain data.
In one embodiment, the obtaining of the node characteristic field corresponding to the node data template includes:
inputting the chain foundation field into the node data template;
generating a data entry interface according to the node data template, and displaying the data entry interface;
and acquiring the entered node characteristic field through the data entry interface.
In one embodiment, generating a data entry interface according to the node data template includes:
searching a transaction chain graph corresponding to the transaction chain data;
marking node basic data corresponding to the chain basic field in each transaction node graph in the transaction chain graph;
generating a basic data area according to the chain basic field, and generating a data entry area according to a field to be entered in the node data template;
and generating a data entry interface according to the marked transaction chain diagram, the basic data area and the data entry area.
In one embodiment, the obtaining of the node characteristic field corresponding to the node data template includes:
receiving an uploaded data document;
acquiring a field name to be input in the node template data;
and identifying the node characteristic field matched with the field name to be input from the uploaded data document.
In one embodiment, identifying a node characteristic field matching the field name to be entered from the uploaded data document includes:
when the document type of the uploaded data document is an image, identifying a character area in the uploaded data document, and dividing the character area into a plurality of single character images;
inputting the single character image into a character recognition model to obtain single characters, and combining the single characters to obtain a character summary text;
and performing semantic analysis on the character summarizing text according to the field name to be input to obtain a node characteristic field matched with the field name to be input.
In one embodiment, the method further comprises:
acquiring a numerical regression generation logic corresponding to the target entry node, and acquiring a determinant factor in the numerical regression generation logic;
extracting factor data corresponding to the determinant factor from the chain basis field and the node feature field;
and obtaining a regression date and a regression value according to the numerical regression generation logic and the factor data, and generating a numerical regression plan according to the regression date and the regression value.
In one embodiment, the method further comprises:
detecting whether settlement identification data exists in the acquired node characteristic field;
and when the settlement identification data is detected, generating a numerical settlement instruction according to the settlement identification data, and sending the numerical settlement instruction to a settlement terminal.
A transaction data processing apparatus, the apparatus comprising:
the request acquisition module is used for acquiring a data entry request and reading a target entry node from the data entry request;
the node data acquisition module is used for acquiring a chain identification field and a node data template corresponding to the target entry node;
the data searching module is used for extracting the chain identification data corresponding to the chain identification field from the data entry request and searching the transaction chain data corresponding to the chain identification data;
a field extraction module, configured to extract a chain foundation field corresponding to the node data template from the transaction chain data, and obtain a node feature field corresponding to the node data template;
and the data adding module is used for generating node transaction data according to the chain foundation field and the node characteristic field and adding the node transaction data into the transaction chain data.
A computer device comprising a memory storing a computer program and a processor implementing the steps of the above method when executing the computer program.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.
According to the transaction data processing method, the transaction data processing device, the computer equipment and the storage medium, node data of nodes which have undergone transaction are connected in series in a transaction chain mode to form transaction chain data, each node is provided with a node data template, a node field which needs to be recorded is set in each node data template, when a new transaction node occurs and data needs to be recorded, a chain foundation field can be directly extracted from the transaction chain data corresponding to the node, and the recording of the node characteristic data can be carried out according to the node characteristic field in the node data template, so that multiple times of transaction data of one asset can be correlated, the recording is convenient to find, and the data processing efficiency of the transaction data is improved.
Drawings
FIG. 1 is a diagram of an application scenario of a transaction data processing method in one embodiment;
FIG. 2 is a schematic flow chart diagram illustrating a method for transaction data processing according to one embodiment;
FIG. 3 is a schematic flow chart diagram illustrating the regression plan generation step in one embodiment;
FIG. 4 is a block diagram of the structure of a transaction data processing device in one embodiment;
FIG. 5 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The transaction data processing method provided by the application can be applied to the application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The method comprises the steps that a terminal 102 obtains a data entry request, a target entry node is read from the data entry request, the terminal 102 obtains a chain identification field and a node data template corresponding to the target entry node from a server 104, extracts chain identification data corresponding to the chain identification field from the data entry request, searches transaction chain data corresponding to the chain identification data from the server 104, extracts a chain basic field corresponding to the node data template from the transaction chain data, obtains a node characteristic field corresponding to the node data template, the terminal 102 generates node transaction data according to the chain basic field and the node characteristic field, and sends the node transaction data to the server 104, so that the server 104 adds the node transaction data to the transaction chain data.
The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented by an independent server or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 2, a transaction data processing method is provided, which is described by taking the method as an example applied to the terminal 102 in fig. 1, and includes the following steps:
step 210, obtaining a data entry request, and reading a target entry node from the data entry request.
When a user wants to input transaction data of a certain transaction of an asset, the user can operate on the terminal, a target input node corresponding to the data to be input is selected on a data input interface of the terminal, a data input request is generated after the target input node is selected and input is determined, and the terminal acquires the data input request and reads the target input node from the data input request. The target entry node is a transaction node corresponding to data to be entered, such as an asset root node, a benefit right subscription node, a benefit right transfer node and the like which can be used for an asset.
And step 220, acquiring a chain identification field and a node data template corresponding to the target entry node.
The terminal generates a node data acquisition instruction carrying a target entry node, the node data acquisition instruction is sent to the server, the server reads the target entry node from the node data acquisition instruction, searches a chain identification field and a node data template corresponding to the target entry node, and returns the chain identification field and the node data template to the terminal.
The chain identification field is a field which can be used for global identification and is used for data connection between each transaction node of an asset and an upstream node and/or a downstream node. The number of the chain identification fields may be one or more, generally, the chain identification field of the asset root node is an asset number, and all other child nodes except the asset root node generally include a plurality of chain identification fields, where one of the chain identification fields is a global identification of the asset chain, that is, the chain identification field of the asset root node, and the other chain identification fields are fields that can be associated with upstream and downstream transaction nodes, for example, if the associated field of the benefit right transfer node is a taken position number, the taken position number is associated with the upstream benefit right subscription node.
The server stores a transaction chain graph of the assets in advance, the transaction chain graph comprises transaction nodes and connection directions among the transaction nodes, and the transaction chain graphs corresponding to different business assets may be different. In addition, the server also stores chain identification fields and node data templates of the transaction nodes on the transaction chain graphs. The transaction information required to be entered by the transaction node is set in the node data template, and the transaction information comprises a plurality of transaction fields to be entered. The server can firstly acquire the service type of the asset from the terminal, search transaction chain data corresponding to the service type, search a chain identification field and a node data template corresponding to the target entry node from the transaction chain graph, and return the chain identification field and the node data template to the terminal.
Step 230, extracting the chain identification data corresponding to the chain identification field from the data entry request, and searching the transaction chain data corresponding to the chain identification data.
When a user records data, basic information of an asset corresponding to the data to be recorded is selected, wherein the basic information of the asset comprises global data, such as asset numbers, position taking numbers and the like. The generated data entry request carries basic asset information. The terminal searches specific chain identification data corresponding to each chain identification field from the data entry request, and if the chain identification field is an asset number, the searched chain identification data is ZC 6534534.
The terminal extracts the chain identification data and then sends the chain identification data to the server, the server can judge which specific asset corresponds to the data to be input according to the chain identification data, specific transaction chain data corresponding to the asset are searched, the transaction chain data are generated according to a transaction chain graph, which fields need to be input by transaction nodes are set in the transaction chain graph, and the transaction chain data are records of real data generated in the actual transaction process of the asset. The server returns the transaction chain data corresponding to the searched chain identification data to the terminal, the transaction chain data searched by the server can not be returned to the terminal, and then the data can be extracted from the transaction chain data according to the data requirement of the terminal and returned to the terminal.
And 240, extracting a chain foundation field corresponding to the node data template from the transaction chain data, and acquiring a node characteristic field corresponding to the node data template.
The chain basic fields are basic fields of basic information to be input in each transaction, such as fields of an asset provider, an asset account number and a transaction account number, the chain basic fields are stored in node data of transaction nodes recorded in transaction chain data, however, the chain basic fields of different transaction nodes may be different, the fields to be input in a node data template can be classified and identified, a terminal obtains the chain basic field names with the chain basic field identifiers from the node data template, and extracts the chain basic fields corresponding to the chain basic field names from the transaction chain data, so that the chain basic fields do not need manual input and can be automatically associated and searched.
The node characteristic field is a special field which needs to be input by the transaction node, and the node characteristic field needs to be input by a user or provides transaction information and captures the transaction information.
And 250, generating node transaction data according to the chain basic field and the node characteristic field, and adding the node transaction data into the transaction chain data.
The terminal inputs the acquired chain basic field and the acquired node characteristic field into a field position corresponding to the node data template to generate node transaction data, the generated node transaction data is sent to the server to be stored, the server adds the transaction node data into the corresponding transaction chain data, and the incidence relation between the transaction node and the upstream node is recorded.
In the transaction data processing method, the node data of the nodes which have undergone transaction are connected in series in a transaction chain form to form transaction chain data, each node is provided with a node data template, a node field which needs to be recorded is set in each node data template, when a new transaction node occurs and needs to be recorded in the data, a chain basic field can be directly extracted from the transaction chain data corresponding to the node, and the recording of the node characteristic data can be carried out according to the node characteristic field in the node data template, so that the transaction data of a plurality of times of assets can be correlated, the searching and the recording are convenient, and the data processing efficiency of the transaction data is improved.
In one embodiment, the step of obtaining the node characteristic field corresponding to the node data template may include: inputting the chain basic field into a node data template; generating a data entry interface according to the node data template, and displaying the data entry interface; and acquiring the entered node characteristic field through the data entry interface.
The terminal inputs the extracted chain basic field into the node data template, acquires the node characteristic field name in the node data template, and generates a plurality of field input options according to the node characteristic field name, further, can acquire the data type, format and other field information corresponding to each node characteristic field name, and sets the field input options according to the field information, such as the data format allowed to be input by the input options can be set, and the type of the input options can be set according to the data type, such as the input options of the fixed value type can be set into a pull-down selection box and the like. And the terminal generates a data entry interface according to the chain basic field and the field input options, displays the acquired chain basic field on the data entry interface, and outputs the field input options.
The terminal obtains the data of each field input option input by the user as a node characteristic field through the data input interface.
In this embodiment, chain basic fields that can be automatically obtained are displayed, and the field input options of the node characteristic fields are generated for the user to input, and the user can input data which cannot be automatically extracted according to a display interface, so that the work efficiency of the input work is improved.
In one embodiment, the step of generating a data entry interface from the node data template may comprise: searching a transaction chain graph corresponding to the transaction chain data; marking node basic data corresponding to the chain basic field in each transaction node graph in the transaction chain graph; generating a basic data area according to the chain basic field, and generating a data entry area according to a field to be entered in the node data template; and generating a data entry interface according to the marked transaction chain diagram, the basic data area and the data entry area.
The method comprises the steps that a server draws transaction chain data of an asset in real time to generate a transaction chain graph, the transaction chain graph is generated by a plurality of transaction nodes in series according to a transaction sequence and an incidence relation, each transaction node can only display a node name in the transaction chain graph, a plurality of node fields corresponding to the transaction nodes are hidden, and when the node names in the transaction chain graph are clicked or selected, the node fields are displayed; each trading node can also directly show the contained node fields in the trading chain graph. And with the increase of each asset transaction node, the server updates the corresponding transaction chain graph according to the node transaction data.
And the terminal acquires the transaction chain graph corresponding to the transaction chain data of the asset from the server, and labels the node basic data corresponding to the chain basic field in each existing transaction node graph in the transaction chain graph, such as character fonts and highlight labeling of background areas. And the terminal generates a basic data area according to the chain basic field, wherein the basic data area is a fixed information display area, and a user cannot edit the basic data area. And generating a data entry area according to a field to be entered in the node data template, namely a special field of the transaction node, specifically, generating field input options and the like as described in the above embodiments, wherein the data entry area is available for a user to perform data editing operation.
And the terminal generates a data entry interface according to the marked transaction chain diagram, the basic data area and the data entry area, and displays the data entry interface. Therefore, the transaction chain graph is displayed on the data entry interface, the user can conveniently check the past transaction information of the asset, and the data searching efficiency is improved.
In one embodiment, the step of obtaining the node characteristic field corresponding to the node data template may include: receiving an uploaded data document; acquiring a field name to be input in node template data; and identifying the node characteristic field matched with the field name to be input from the uploaded data document.
In this embodiment, when the user makes a data entry request, the data document of the transaction information is also uploaded, and the terminal receives the uploaded data document uploaded by the user. The uploaded data document can be a scanned image document of the transaction and equivalent data, and can also be a text data document of transaction information and the like.
The terminal obtains a field name to be input of a special field of a node in the node template data, identifies information in the uploaded data document according to the field name to be input, identifies information matched with the field name to be input in the uploaded data document, and extracts a node characteristic field from the matched information. For example, when the uploaded data document is an image document, the image document is subjected to character recognition to generate a character document, and then the character document is subjected to semantic analysis to extract information corresponding to the field name to be input.
In one embodiment, identifying the node characteristic field matching the field name to be entered in the upload data document includes: when the document type of the uploaded data document is an image, identifying a character area in the uploaded data document, and dividing the character area into a plurality of single character images; inputting the single-character image into a character recognition model to obtain single characters, and combining the single characters to obtain a character summary text; and performing semantic analysis on the character summarizing text according to the field name to be input to obtain a node characteristic field matched with the field name to be input.
When the terminal detects that the document type of the uploaded data document is an image, the terminal identifies a character area in the uploaded data document, eliminates a blank area, and divides the identified character area into a plurality of single character images, wherein the single character images only contain one character, and the character can be a Chinese character or an English character.
And the terminal inputs the cut single character image into the character recognition model and outputs the single character matched with the single character image. The character recognition model can be trained and generated in a terminal or a server, and the model training process can comprise the steps of firstly collecting Chinese character and English character image samples to manufacture a corpus, carrying out data processing on sample data in the corpus, for example, collecting a plurality of image sample files, cutting the image files into single character picture files, marking corresponding labels on each character picture, and splitting training set, verification set and test set data. The terminal builds a training model, such as a neural network model, a decision tree model and the like, determines initial parameters in the model, such as the number of network layers, the number of nodes in each layer, an activation function, a loss function, an optimizer and the like if the model is the neural network model. And the terminal inputs the character pictures into the built model for training, draws the accuracy and loss of training and verification, adjusts the initial parameters of training and takes the optimized model as a character recognition model.
The terminal sorts and summarizes all the obtained single characters to obtain a character summarizing text, analyzes the character summarizing text, finds whether words with the same semantic as the field name to be input exist in the character summarizing text, if yes, sorts out similar words with the similar semantic as the field name to be input in advance, establishes a mapping relation between the similar words and the field name to be input, identifies matched words from the character summarizing text according to the mapped similar words and the field name to be input, and extracts specific field contents corresponding to the matched words as node characteristic fields according to information such as symbols, breakpoints, spaces and the like. For example, when the terminal generates a text summary, the punctuation mark and the space position of the original image document can be used for setting the break point mark for the text.
Further, the terminal generates an information confirmation interface according to the extracted chain basic field and the extracted node characteristic field for the user to confirm the input information, and when the user finds that the information is wrong, the data of each field can be modified on the information confirmation interface.
In this embodiment, in addition to automatic identification and extraction of the chain basic field of the transaction node, text identification and semantic identification can be performed on the transaction information uploaded by the user, and the node characteristic field is automatically identified from the text identification and semantic identification, so that the user does not need to perform entry operation.
In one embodiment, as shown in fig. 3, the transaction data processing method may further include the following regression plan generation step:
and 310, acquiring a numerical regression generation logic corresponding to the target entry node, and acquiring a determinant factor in the numerical regression generation logic.
The value regression plan refers to a return plan of the asset value corresponding to the transaction node, such as an asset subscription plan, an asset return plan scheme after asset transfer, and a payment plan scheme. The asset return plan may include information such as the return period number of the staged return, the return date, the return value of each period, and the like, and may also include a calculation method of the information. Different numerical value regression generation logics are set for different transaction nodes, a terminal extracts a decision factor from the numerical value regression generation logics, the decision factor needs to be determined according to actual transaction conditions, the decision factor can be an asset cashing mode, a transaction share, an earning rate and the like, for example, different cashing modes can correspond to different return period numbers, and different earning rates and transaction shares can determine planned asset values and the like in each period. The terminal can calculate return plan information such as the return period number of the assets and the return value of each period according to the calculation logic in the decision factor and the numerical value regression generation logic.
Step 320, factor data corresponding to the determinant factor is extracted from the chain foundation field and the node feature field.
And after the terminal acquires the decision factor, searching factor data corresponding to the decision factor in the chain basic field and the node characteristic field, and if the decision factor is the yield and the transaction share, extracting specific numerical values corresponding to the yield and the transaction share from the chain basic field and the node characteristic field.
Step 330, obtaining a regression date and a regression value according to the numerical regression generation logic and the factor data, and generating a numerical regression plan according to the regression date and the regression value.
The terminal extracts data capable of determining the number of regression periods, such as data of a cash mode and the like, from the factor data, determines the number of regression periods and the regression period according to the data, and calculates the regression date corresponding to each period according to the number of regression periods and the regression period, for example, if the regression period is 6 months and the number of regression periods is 3 periods, the regression date of each period is 2 months, 4 months and 6 months from the current date. And the terminal extracts a transaction value and a numerical influence factor from the factor data, wherein the numerical influence factor can be a factor such as interest rate and profitability, and the data such as the transaction value and the numerical influence factor are input into numerical regression generation logic to calculate a regression value of each period. And summarizing the calculated regression date and regression value of each period to generate a numerical regression plan, wherein the regression date can be used as a time axis to display the regression value of each period.
Further, the terminal may send the numerical regression plan to the server, and the server adds the numerical regression plan to the transaction chain data and the transaction chain map corresponding to the asset, and displays the numerical regression plan in a plan option form in a corresponding transaction node in the transaction chain map. For example, when the user selects the transaction node, the plan option is popped up, and the numerical regression plan is displayed after the plan option is selected.
In one embodiment, after the terminal generates the node transaction data, the terminal detects whether a determinant in the numerical regression plan of the upstream transaction node exists in the node transaction data, specifically, the terminal first obtains a numerical regression generation logic of the upstream transaction node, obtains a determinant in the numerical regression generation logic, detects whether data matching the determinant exists in the node transaction data, and if data matching the determinant is detected, recalculates a specific regression value of the numerical regression plan of the upstream node according to the detected data, and adjusts the numerical regression plan of the upstream node according to the recalculated regression value.
In one embodiment, the transaction data processing method may further include: detecting whether settlement identification data exists in the acquired node characteristic field; and when the settlement identification data is detected, generating a numerical settlement instruction according to the settlement identification data, and sending the numerical settlement instruction to a settlement terminal.
The settlement identification data is data indicating that the current node transaction is finished and the transaction data settlement is to be performed, such as when the numerical regression plan is finished and value-added tax is recorded. The terminal detects whether the acquired node characteristic field has settlement identification data, when the settlement identification data is detected, a numerical settlement instruction is generated according to the settlement identification data and global identification data of the transaction chain, such as asset numbers and the like, the numerical settlement instruction is sent to the settlement terminal so that the settlement terminal can acquire corresponding transaction chain data according to the global identification data, and then data settlement of the transaction is carried out according to the transaction chain data and the settlement identification data.
It should be understood that although the various steps in the flow charts of fig. 2-3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-3 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 4, there is provided a transaction data processing apparatus including: a request acquisition module 410, a node data acquisition module 420, a data lookup module 430, a field extraction module 440, and a data addition module 450, wherein:
the request obtaining module 410 is configured to obtain a data entry request, and read a target entry node from the data entry request.
And the node data obtaining module 420 is configured to obtain a chain identification field and a node data template corresponding to the target entry node.
And the data searching module 430 is configured to extract the chain identification data corresponding to the chain identification field from the data entry request, and search the transaction chain data corresponding to the chain identification data.
The field extraction module 440 is configured to extract a chain basic field corresponding to the node data template from the transaction chain data, and obtain a node feature field corresponding to the node data template.
And the data adding module 450 is configured to generate node transaction data according to the chain basic field and the node characteristic field, and add the node transaction data to the transaction chain data.
In one embodiment, the field extraction module 440 may further include:
and the field input unit is used for inputting the chain basic field into the node data template.
And the interface display unit is used for generating a data entry interface according to the node data template and displaying the data entry interface.
And the field acquisition unit is used for acquiring the input node characteristic field through the data input interface.
In one embodiment, the interface presentation unit may further include:
and the chain graph searching subunit is used for searching the transaction chain graph corresponding to the transaction chain data.
And the data labeling subunit is used for labeling the node basic data corresponding to the chain basic field in each transaction node graph in the transaction chain graph.
And the area generation subunit is used for generating a basic data area according to the chain basic field and generating a data entry area according to the field to be entered in the node data template.
And the interface generating subunit is used for generating a data entry interface according to the marked transaction chain diagram, the basic data area and the data entry area.
In one embodiment, the field extraction module 440 may further include:
and the document receiving unit is used for receiving the uploaded data document.
And the field name acquisition unit is used for acquiring the field name to be input in the node template data.
And the field identification unit is used for identifying the node characteristic field matched with the field name to be input from the uploaded data document.
In one embodiment, the field identification unit may include:
and the image segmentation subunit is used for identifying a character area in the uploaded data document and segmenting the character area into a plurality of single character images when the document type of the uploaded data document is an image.
And the character summarizing subunit inputs the single-character image into the character recognition model to obtain single characters, and combines the single characters to obtain a character summarizing text.
And the semantic analysis unit is used for performing semantic analysis on the character summarizing text according to the field name to be input to obtain a node characteristic field matched with the field name to be input.
In one embodiment, the transaction data processing apparatus may further include:
and the factor acquisition module is used for acquiring the numerical regression generation logic corresponding to the target entry node and acquiring the determinant factor in the numerical regression generation logic.
And the factor extraction module is used for extracting factor data corresponding to the decision factor from the chain foundation field and the node characteristic field.
And the plan generating module is used for obtaining a regression date and a regression value according to the numerical regression generation logic and the factor data and generating a numerical regression plan according to the regression date and the regression value.
In one embodiment, the transaction data processing apparatus may further include:
and the settlement detection module is used for detecting whether the acquired node characteristic field has settlement identification data.
And the instruction sending module is used for generating a numerical settlement instruction according to the settlement identification data when the settlement identification data is detected, and sending the numerical settlement instruction to the settlement terminal.
For the specific definition of the transaction data processing device, reference may be made to the above definition of the transaction data processing method, which is not described herein again. The various modules in the transaction data processing apparatus described above may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 5. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a transaction data processing method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 5 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, there is provided a computer device comprising a memory storing a computer program and a processor implementing the following steps when the processor executes the computer program: acquiring a data entry request, and reading a target entry node from the data entry request; acquiring a chain identification field and a node data template corresponding to a target entry node; extracting chain identification data corresponding to the chain identification field from the data entry request, and searching transaction chain data corresponding to the chain identification data; extracting a chain foundation field corresponding to the node data template from the transaction chain data, and acquiring a node characteristic field corresponding to the node data template; and generating node transaction data according to the chain foundation field and the node characteristic field, and adding the node transaction data into the transaction chain data.
In one embodiment, when the processor executes the computer program to perform the step of obtaining the node characteristic field corresponding to the node data template, the processor is further configured to: inputting the chain basic field into a node data template; generating a data entry interface according to the node data template, and displaying the data entry interface; and acquiring the entered node characteristic field through the data entry interface.
In one embodiment, the processor, when executing the computer program, further performs the step of generating a data entry interface from the node data template, by: searching a transaction chain graph corresponding to the transaction chain data; marking node basic data corresponding to the chain basic field in each transaction node graph in the transaction chain graph; generating a basic data area according to the chain basic field, and generating a data entry area according to a field to be entered in the node data template; and generating a data entry interface according to the marked transaction chain diagram, the basic data area and the data entry area.
In one embodiment, when the processor executes the computer program to perform the step of obtaining the node characteristic field corresponding to the node data template, the processor is further configured to: receiving an uploaded data document; acquiring a field name to be input in node template data; and identifying the node characteristic field matched with the field name to be input from the uploaded data document.
In one embodiment, the processor, when executing the computer program, further performs the step of identifying from the uploaded data document a node characteristic field matching the name of the field to be entered: when the document type of the uploaded data document is an image, identifying a character area in the uploaded data document, and dividing the character area into a plurality of single character images; inputting the single-character image into a character recognition model to obtain single characters, and combining the single characters to obtain a character summary text; and performing semantic analysis on the character summarizing text according to the field name to be input to obtain a node characteristic field matched with the field name to be input.
In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring a numerical regression generation logic corresponding to the target entry node, and acquiring a determinant factor in the numerical regression generation logic; extracting factor data corresponding to the decision factor from the chain basic field and the node characteristic field; and obtaining a regression date and a regression value according to the numerical regression generation logic and the factor data, and generating a numerical regression plan according to the regression date and the regression value.
In one embodiment, the processor, when executing the computer program, further performs the steps of: detecting whether settlement identification data exists in the acquired node characteristic field; and when the settlement identification data is detected, generating a numerical settlement instruction according to the settlement identification data, and sending the numerical settlement instruction to a settlement terminal.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of: acquiring a data entry request, and reading a target entry node from the data entry request; acquiring a chain identification field and a node data template corresponding to a target entry node; extracting chain identification data corresponding to the chain identification field from the data entry request, and searching transaction chain data corresponding to the chain identification data; extracting a chain foundation field corresponding to the node data template from the transaction chain data, and acquiring a node characteristic field corresponding to the node data template; and generating node transaction data according to the chain foundation field and the node characteristic field, and adding the node transaction data into the transaction chain data.
In one embodiment, when being executed by a processor, the computer program further implements the step of obtaining the node feature field corresponding to the node data template, and is further configured to: inputting the chain basic field into a node data template; generating a data entry interface according to the node data template, and displaying the data entry interface; and acquiring the entered node characteristic field through the data entry interface.
In one embodiment, the computer program when executed by the processor performs the step of generating a data entry interface from the node data template further operable to: searching a transaction chain graph corresponding to the transaction chain data; marking node basic data corresponding to the chain basic field in each transaction node graph in the transaction chain graph; generating a basic data area according to the chain basic field, and generating a data entry area according to a field to be entered in the node data template; and generating a data entry interface according to the marked transaction chain diagram, the basic data area and the data entry area.
In one embodiment, when executed by the processor, the computer program further performs the step of obtaining the node feature field corresponding to the node data template, and is further configured to: receiving an uploaded data document; acquiring a field name to be input in node template data; and identifying the node characteristic field matched with the field name to be input from the uploaded data document.
In one embodiment, the computer program when executed by the processor performs the step of identifying from the uploaded data document a node characteristic field matching the field name to be entered, is further operable to: when the document type of the uploaded data document is an image, identifying a character area in the uploaded data document, and dividing the character area into a plurality of single character images; inputting the single-character image into a character recognition model to obtain single characters, and combining the single characters to obtain a character summary text; and performing semantic analysis on the character summarizing text according to the field name to be input to obtain a node characteristic field matched with the field name to be input.
In one embodiment, the computer program when executed by the processor performs the further steps of: acquiring a numerical regression generation logic corresponding to the target entry node, and acquiring a determinant factor in the numerical regression generation logic; extracting factor data corresponding to the decision factor from the chain basic field and the node characteristic field; and obtaining a regression date and a regression value according to the numerical regression generation logic and the factor data, and generating a numerical regression plan according to the regression date and the regression value.
In one embodiment, the computer program when executed by the processor performs the further steps of: detecting whether settlement identification data exists in the acquired node characteristic field; and when the settlement identification data is detected, generating a numerical settlement instruction according to the settlement identification data, and sending the numerical settlement instruction to a settlement terminal.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of transaction data processing, the method comprising:
acquiring a data entry request, and reading a target entry node from the data entry request;
acquiring a chain identification field and a node data template corresponding to the target entry node;
extracting chain identification data corresponding to the chain identification field from the data entry request, and searching transaction chain data corresponding to the chain identification data;
extracting a chain foundation field corresponding to the node data template from the transaction chain data, and acquiring a node characteristic field corresponding to the node data template;
and generating node transaction data according to the chain foundation field and the node characteristic field, and adding the node transaction data into the transaction chain data.
2. The method according to claim 1, wherein the obtaining the node characteristic field corresponding to the node data template comprises:
inputting the chain foundation field into the node data template;
generating a data entry interface according to the node data template, and displaying the data entry interface;
and acquiring the entered node characteristic field through the data entry interface.
3. The method of claim 2, wherein generating a data entry interface from the node data template comprises:
searching a transaction chain graph corresponding to the transaction chain data;
marking node basic data corresponding to the chain basic field in each transaction node diagram in the transaction chain diagram;
generating a basic data area according to the chain basic field, and generating a data entry area according to a field to be entered in the node data template;
and generating a data entry interface according to the marked transaction chain diagram, the basic data area and the data entry area.
4. The method according to claim 1, wherein the obtaining the node characteristic field corresponding to the node data template comprises:
receiving an uploaded data document;
acquiring a field name to be input in the node template data;
and identifying the node characteristic field matched with the field name to be input from the uploaded data document.
5. The method according to claim 4, wherein the identifying the node characteristic field matching the field name to be entered from the uploaded data document comprises:
when the document type of the uploaded data document is an image, identifying a character area in the uploaded data document, and dividing the character area into a plurality of single character images;
inputting the single character image into a character recognition model to obtain single characters, and combining the single characters to obtain a character summary text;
and performing semantic analysis on the character summarizing text according to the field name to be input to obtain a node characteristic field matched with the field name to be input.
6. The method of claim 1, further comprising:
acquiring a numerical regression generation logic corresponding to the target entry node, and acquiring a determinant factor in the numerical regression generation logic;
extracting factor data corresponding to the determinant factor from the chain basis field and the node feature field;
and obtaining a regression date and a regression value according to the numerical regression generation logic and the factor data, and generating a numerical regression plan according to the regression date and the regression value.
7. The method of claim 1, further comprising:
detecting whether settlement identification data exists in the acquired node characteristic field;
and when the settlement identification data is detected, generating a numerical settlement instruction according to the settlement identification data, and sending the numerical settlement instruction to a settlement terminal.
8. A transaction data processing apparatus, characterized in that the apparatus comprises:
the request acquisition module is used for acquiring a data entry request and reading a target entry node from the data entry request;
the node data acquisition module is used for acquiring a chain identification field and a node data template corresponding to the target entry node;
the data searching module is used for extracting the chain identification data corresponding to the chain identification field from the data entry request and searching the transaction chain data corresponding to the chain identification data;
a field extraction module, configured to extract a chain foundation field corresponding to the node data template from the transaction chain data, and obtain a node feature field corresponding to the node data template;
and the data adding module is used for generating node transaction data according to the chain foundation field and the node characteristic field and adding the node transaction data into the transaction chain data.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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