Form verification method and electronic device

Abstract

The embodiment of the present application discloses a form verification method and electronic equipment. The method comprises the following steps: determining an initial collection form corresponding to a target function model, wherein the initial collection form is a form without filling in target collection data; determining historical data corresponding to the initial collection form, and determining a historical characteristic value according to the historical data, wherein the historical data comprises a historical collection form filled with historical collection data and / or historical collection data; obtaining a target collection form obtained after filling in the target collection data of the initial collection form, and verifying the target collection form according to the historical characteristic value, so as to process the target collection form through the target function model in the case that the obtained form verification result is a form verification pass. The technical scheme of the embodiment of the present application improves the accuracy of the function implementation of the target function model.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of data processing technology, and in particular to a form validation method and an electronic device. Background Technology

[0002] With the rapid development of the digital age, the target data collected is mostly used for processing by the target functional model.

[0003] However, directly processing the target acquisition data by the target functional model will reduce the accuracy of the target functional model's functional implementation, which urgently needs to be addressed. Summary of the Invention

[0004] This invention provides a form validation method and electronic device, which improves the accuracy of the functional implementation of the target functional model.

[0005] According to one aspect of the present invention, a form validation method is provided, which may include:

[0006] Determine the initial data collection form corresponding to the target functional model. The initial data collection form is the form in which no target data has been filled in.

[0007] Determine the historical data corresponding to the initial data collection form, and determine the historical feature values ​​based on the historical data. The historical data includes historical data collection forms and / or historical data that have been filled in.

[0008] The target collection form is obtained after the initial collection form is filled with target collection data. The target collection form is then validated based on historical feature values. If the form validation result is that the form validation is successful, the target collection form is processed through the target function model.

[0009] According to another aspect of the present invention, an electronic device is provided, which may include:

[0010] At least one processor; and

[0011] A memory that is communicatively connected to at least one processor; wherein,

[0012] The memory stores a computer program that can be executed by at least one processor, such that when the at least one processor executes the program, it implements the form validation method provided in any embodiment of the present invention.

[0013] The technical solution of this invention determines the initial collection form by identifying an initial collection form with unfilled target collection data corresponding to the target functional model; it determines historical data corresponding to the initial collection form and, based on the historical data, determines historical feature values ​​that can provide reference factors for form verification; it obtains the target collection form after filling in the target collection data on the initial collection form, and verifies the target collection form based on the historical feature values; and, if the form verification result is that the form verification is passed, it processes the target collection form through the target functional model to obtain a target collection form that can be processed by the target functional model. The above technical solution, by determining an initial data collection form corresponding to the target functional model and filling in the target data, and by using the initial data collection form to determine historical feature values ​​and obtain the target data collection form, and by validating the target data collection form based on the historical feature values, not only makes the format of the target data collection form more suitable for processing by the target functional model, but also improves the accuracy of the target data collection form processed by the target functional model through the validation of the target data collection form using historical feature values. This avoids the problem of the target functional model processing data that is unsuitable for processing and has low accuracy, which would reduce the accuracy of the target functional model's functional implementation, thereby improving the accuracy of the target functional model's functional implementation.

[0014] It should be understood that the description in this section is not intended to identify key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of a form validation method provided according to an embodiment of the present invention;

[0017] Figure 2 This is a flowchart illustrating the determination of historical feature values ​​in a form validation method according to an embodiment of the present invention;

[0018] Figure 3 This is a schematic diagram of a form validation model in a form validation method provided according to an embodiment of the present invention;

[0019] Figure 4 This is a flowchart of another form validation method provided according to an embodiment of the present invention;

[0020] Figure 5 This is a flowchart of an optional example of another form validation method provided according to an embodiment of the present invention;

[0021] Figure 6 This is a structural block diagram of a form validation device according to an embodiment of the present invention;

[0022] Figure 7 This is a schematic diagram of the structure of an electronic device that implements the form validation method of this invention. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. The same applies to "target," "original," etc., and will not be repeated here. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] Before introducing the embodiments of the present invention, the reasons for the problem of reducing the accuracy of the functional implementation of the target functional model will be explained by way of example, so as to better understand why the solution proposed in the embodiments of the present invention improves the accuracy of the functional implementation of the target functional model.

[0026] With the rapid development of the digital age, data collection has become a key source of basic data for achieving target functional models in enterprise decision-making and operation. However, the target data collected often suffers from problems such as inconsistent data formats, uneven data quality, and susceptibility to errors, which seriously affect the overall quality of the target data. Directly processing low-quality target data will reduce the accuracy of the target functional model's functional implementation.

[0027] To address this, this invention provides an embodiment that determines an initial data collection form corresponding to the target functional model, allowing for the collection of target data. Using this initial form, historical feature values ​​are determined, and the target data collection form is obtained. Based on these historical feature values, the target data collection form is validated. This not only makes the format of the target data collection form more suitable for processing by the target functional model but also, through validation using historical feature values, improves the accuracy of the target data collection form processed by the target functional model. This avoids the problem of data that is unsuitable for processing by the target functional model and has low accuracy being processed, which could reduce the accuracy of the target functional model's functional implementation. This will be explained in detail below.

[0028] Figure 1 This is a flowchart of a form validation method provided in an embodiment of the present invention. This embodiment is applicable to form validation scenarios. The method can be executed by the form validation device provided in this embodiment of the present invention. This device can be implemented in software and / or hardware, and can be integrated into an electronic device, which can be various user terminals or servers.

[0029] See Figure 1 The method of this invention specifically includes the following steps:

[0030] S110. Determine the initial data collection form corresponding to the target functional model, wherein the initial data collection form is a form in which no target data collection data has been filled in.

[0031] The target function model can be understood as a model capable of achieving the target function; see [link / reference]. Figure 2 For example, a target function model can be an enterprise management evaluation model that can achieve the enterprise management evaluation as a target function. The enterprise management evaluation model can include evaluation framework, evaluation indicators and evaluation methods, etc., to achieve enterprise management evaluation. Another example of a target function model is a geological resource prediction model, a geological flow capacity evaluation model, a production allocation model or a surface structure prediction model.

[0032] The initial data collection form can be understood as a form in which no target data has been filled in. For the same target functional model, the format, standards, and forms of the initial data collection form can be the same to ensure the uniformity of the format and standards of the target data collection form, which facilitates subsequent form validation and processing of the target data collection form by the target functional model.

[0033] It is understandable that the initial data collection form may be uniform for the target functional model. Therefore, the initial data collection form can serve as the basis for integrating and optimizing the collected data into the target data collection, which can help improve the quality of the collected data. Furthermore, since the initial data collection form may include relevant information to guide the data collection process, it can serve as a guiding factor for automatic data collection, thereby improving the efficiency of data collection.

[0034] The target data to be collected is the data that is collected according to requirements and entered into the initial data collection form.

[0035] In this embodiment of the invention, an initial data collection form can be determined, for example, based on at least one of the characteristics of the target function and the target function model.

[0036] S120. Determine the historical data corresponding to the initial data collection form, and determine the historical feature values ​​based on the historical data, wherein the historical data includes historical data collection forms and / or historical data collection data filled in.

[0037] Historical data can be understood to include historical collection forms and / or data containing historical collection data.

[0038] Historical feature values ​​can be understood as numerical values ​​that can characterize the features of historical data.

[0039] Historical data collection can be understood as target data that was previously entered. Historical data collection forms can be understood as target data collection forms that were previously obtained.

[0040] In this embodiment of the invention, historical data can be determined, for example, data from the data warehouse that has the same style as the initial collection form, the same target functional model, and the same target enterprise as the data can be determined as historical data.

[0041] In this embodiment of the invention, historical feature values ​​can be determined based on historical data. For example, historical data can be analyzed, summarized, and calculated to determine historical feature values.

[0042] Optionally, the historical feature values ​​include at least one of the following: historical data values ​​within a preset historical period, historical average value, historical maximum value, historical minimum value, historical average absolute deviation value, month-on-month value, and fluctuation threshold.

[0043] Among them, the preset historical time is a preset historical time. Specifically, the preset historical time can be a preset historical time period. For example, the preset historical time can be a preset time period that is adjacent to the current time before the current time when the initial data collection form is determined. For example, the preset historical time can be a time period corresponding to the past five years before the current time.

[0044] Historical data values ​​can be understood as historical data extracted directly within a preset historical time period, such as monthly, quarterly, or annual data. The content of the extracted time period and historical data values ​​can be determined based on the availability of historical data and the verification requirements of the target data collection form.

[0045] Historical average can be understood as the average value of data in historical data; historical average can include at least one of the following: overall average, annual average, quarterly average, and monthly average within a preset historical period; each individual data point in historical data can have a corresponding average value. For example, historical average can include at least one of the following: overall average, annual average, quarterly average, and monthly average within a preset historical period for each individual data point.

[0046] The historical maximum value can be understood as the maximum value of data in historical data; the historical maximum value can include at least one of the following: the overall maximum value, the maximum value of each year, the maximum value of each quarter, and the maximum value of each month within a preset historical period; each individual data in the historical data can have a corresponding maximum value data. For example, the historical maximum value can include at least one of the following: the overall maximum value, the maximum value of each year, the maximum value of each quarter, and the maximum value of each month within a preset historical period for each individual data.

[0047] The historical minimum can be understood as the minimum value of data in historical data; the historical minimum can include at least one of the following: the overall minimum value, the minimum value of each year, the minimum value of each quarter, and the minimum value of each month within a preset historical period; each individual data in the historical data can have a corresponding minimum value data. For example, the historical minimum can include at least one of the following: the overall minimum value, the minimum value of each year, the minimum value of each quarter, and the minimum value of each month within a preset historical period for each individual data.

[0048] The historical mean absolute deviation (MAD) can be understood as a statistic that measures the deviation between historical data and the historical average, and can be used to measure the dispersion of historical data; each individual data point in the historical data can have a corresponding historical mean absolute deviation.

[0049] The month-on-month value can be understood as the rate of change of historical data in adjacent time periods (such as between months, quarters, and years) within a preset historical period, reflecting the trend of historical data changes over time.

[0050] The fluctuation threshold can be understood as a threshold determined based on historical data fluctuations, which can be used to identify data with abnormal fluctuations in the target data collection form.

[0051] In this embodiment of the invention, at least one of the following historical data values, historical average values, historical maximum values, historical minimum values, historical average absolute deviation values, month-on-month values, and fluctuation thresholds within a preset historical period is used as historical feature values. This can improve the comprehensiveness of historical feature values ​​and thus improve the accuracy of form validation.

[0052] S130. Obtain the target collection form after filling in the target collection data on the initial collection form, and verify the target collection form according to the historical feature values. If the form verification result is that the form verification is passed, process the target collection form through the target function model.

[0053] The target data collection form is the form obtained by filling in the target data in the initial data collection form.

[0054] Form validation results are obtained by validating the target data collection form; the form validation result can be, for example, form validation passed or form validation failed; see also Figure 3 If the form validation result is that the form validation fails, the form validation result may also include at least one of the following reasons for failure: data in the target collection form whose data value exceeds the historical range represented by historical data values, data whose deviation from the historical average value is too large, and data with abnormal month-on-month values.

[0055] In this embodiment of the invention, a target data collection form can be obtained after filling in the target data in an initial data collection form. That is, the target data is obtained through the initial data collection form. For example, the target data can be automatically collected based on at least one of the following information in the initial data collection form: the enterprise to which the target data is collected, the data source, the data name, the period, and the data value. The collected data is then automatically filled into the initial data collection form to obtain the target data collection form. Alternatively, the initial data collection form can be distributed to the form filler so that they can fill in the target data and obtain the target data collection form. Another example is that data can be automatically collected based on at least one of the following information in the initial data collection form: the enterprise to which the target data is collected, the data source, the data name, the period, and the data value. A portion of the collected target data is then automatically filled into the initial data collection form to obtain an intermediate data collection form. This intermediate form is then distributed to the form filler so that they can fill in another portion of the target data and obtain the target data collection form. And so on.

[0056] In this embodiment of the invention, the target data collection form can be validated based on historical feature values. For example, historical feature values ​​can be matched and validated with the target data collection form to ensure the accuracy and validity of the target data collection form.

[0057] In this embodiment of the invention, the target collection form can also be verified by other verification methods such as form feature value checking and / or macro checking, and the form verification result can be updated based on the other verification results obtained.

[0058] In this embodiment of the invention, the above form validation process can be embedded into the data acquisition workflow, thereby achieving seamless connection between data acquisition, validation, integration and optimization, and improving the processing efficiency of the acquired data; the above form validation process can also be embedded into the workflow of the function implementation of the target function model, thereby improving the efficiency of the function implementation of the target function model.

[0059] In this embodiment of the invention, if the form validation result is that the form validation is successful, a message "Validation successful, you can upload" can be displayed, and / or the "Form Validation" status can be set to "Passed", etc., and then the target collection form can be processed through the target function model.

[0060] In an embodiment of the present invention, see Figure 2A stable data source can be established, such as a data warehouse, where the target data and / or target forms are stored as historical data. This allows for the determination of historical data corresponding to the initial forms from the data warehouse when form validation is required later, and then the determination of historical feature values ​​through the historical data.

[0061] The technical solution of this invention determines the initial collection form by identifying an initial collection form with unfilled target collection data corresponding to the target functional model; it determines historical data corresponding to the initial collection form and, based on the historical data, determines historical feature values ​​that can provide reference factors for form verification; it obtains the target collection form after filling in the target collection data on the initial collection form, and verifies the target collection form based on the historical feature values; and, if the form verification result is that the form verification is passed, it processes the target collection form through the target functional model to obtain a target collection form that can be processed by the target functional model. The above technical solution, by determining an initial data collection form corresponding to the target functional model and filling in the target data, and by using the initial data collection form to determine historical feature values ​​and obtain the target data collection form, and by validating the target data collection form based on the historical feature values, not only makes the format of the target data collection form more suitable for processing by the target functional model, but also improves the accuracy of the target data collection form processed by the target functional model through the validation of the target data collection form using historical feature values. This avoids the problem of the target functional model processing data that is unsuitable for processing and has low accuracy, which would reduce the accuracy of the target functional model's functional implementation, thereby improving the accuracy of the target functional model's functional implementation.

[0062] An optional technical solution, the form validation method, further includes: determining the validation rules corresponding to the initial collected form from a preset validation rule library; and validating the target collected form based on historical feature values, including: validating the target collected form based on historical feature values ​​and validation rules.

[0063] The validation rule base can be understood as a rule base that stores validation rules; the validation rule base can store various types of validation rules.

[0064] Validation rules can be understood as rules used to validate the target data collection form; that is, validation rules can serve as the basis for validating the target data collection form. (See also...) Figure 3 The validation rules may include at least one of the following: business rules, data format rules, and form feature value rules.

[0065] See Figure 3Business rules can be understood as rules that define the relationship between business logic and data. For example, business rules may include at least one of the following: data values ​​that are N times greater than the previous year are abnormal data; data values ​​that are less than N times the previous year are abnormal data; data values ​​that are greater than the sum of the historical average plus the historical average amplitude N times are abnormal data; data values ​​that are less than the sum of the historical average minus the historical average amplitude N times are abnormal data; and data with abnormal month-on-month values ​​are abnormal data.

[0066] See Figure 3 Data format rules can be understood as rules for logical judgments to check the data format; data format rules may include at least one of the following: data is empty, data is text, data is a number, and cell color settings.

[0067] See Figure 3 Form feature value rules can be understood as rules for checking the status fields of the target collection form to ensure that all validations pass. Form feature value rules may include, for example, checking whether the process task number, reporting unit, and number of reported items of the target collection form are consistent with the issued information, etc.

[0068] In this embodiment of the invention, validation rules can be determined from the validation rule base. For example, validation rules applicable to the initial data collection form can be determined from the validation rule base.

[0069] In this embodiment of the invention, the target collection form can be verified based on historical feature values ​​and verification rules. For example, historical feature values ​​and verification rules can be fused to obtain target rules, and the target collection form can be verified based on the target rules. Alternatively, historical feature values ​​can be compared with the target collection form based on the verification rules to achieve verification of the target collection form.

[0070] In this embodiment of the invention, by verifying the target data collection form according to historical feature values ​​and verification rules, the comprehensiveness of the target data collection form verification can be improved.

[0071] Another optional technical solution, the form validation method, further includes: if the form validation result indicates that the form validation has failed, passing the target collection form to the data modification end; obtaining the modified target collection form from the data modification end, and repeatedly executing the process of validating the target collection form based on historical feature values.

[0072] The data modification section can be understood as the end that can modify the target data collection form.

[0073] In this embodiment of the invention, if the form validation result indicates that the form validation has failed, the target collection form can be passed to the data modification end, allowing the data modification end to modify the target collection form. The modified target collection form is then retrieved from the data modification end, and the process of validating the target collection form based on historical feature values ​​is repeated to validate the modified target collection form. This technical solution provides a way to modify the target collection form, avoiding the resource waste caused by repeatedly re-retrieving the target collection form when the form validation result indicates that the form validation has failed. Furthermore, by repeatedly executing the process of validating the target collection form based on historical feature values, the problem of reduced accuracy of the target functional model due to the low accuracy of the modified target collection form can be avoided.

[0074] Another optional technical solution is to verify the target data collection form based on historical feature values, including: verifying the target data collection form based on historical feature values; if abnormal data is found during verification, marking the target data collection form as abnormal data, and passing the marked target data collection form to the manual verification end so that the manual verification end can manually verify the marked target data collection form.

[0075] Among them, abnormal data refers to data in the target data collection form that is abnormal; abnormal data may be, for example, data in the target data collection form that exceeds the historical range represented by historical data values, data that deviates too much from the historical average, and data with abnormal month-on-month values, etc.

[0076] The manual verification end can be understood as an end that can manually verify the labeled target collection form.

[0077] In this embodiment of the invention, when abnormal data is obtained during verification, the target data collection form is annotated with abnormal data. For example, the prompt information corresponding to the abnormal data can be displayed, and / or the position of the abnormal data in the target data collection form can be demonstrated and annotated, etc.

[0078] In this embodiment of the invention, the labeled target collection form can be passed to the manual verification end so that the manual verification end can manually verify the labeled target collection form and obtain the form verification result.

[0079] In this embodiment of the invention, if no abnormal data is found during the verification, the form verification can be directly passed as the form verification result.

[0080] In this embodiment of the invention, when abnormal data is obtained during verification, the labeled target acquisition form is passed to the manual verification end so that the manual verification end can manually verify the labeled target acquisition form. This avoids the problem of not being able to obtain a target acquisition form that can be processed by the target functional model due to incorrect verification of abnormal data.

[0081] Figure 4 This is a flowchart of another form validation method provided in this embodiment of the invention. This embodiment is based on and optimized from the above-described technical solutions. In this embodiment, optionally, determining the initial collection form corresponding to the target functional model includes: obtaining basic data associated with the target functional model; and generating the initial collection form corresponding to the target functional model based on the basic data. The explanations of terms that are the same as or corresponding to those in the above embodiments will not be repeated here.

[0082] See Figure 4 The method in this embodiment may specifically include the following steps:

[0083] S210. Obtain the basic data associated with the target functional model.

[0084] The basic data refers to the data associated with the target functional model that can be used to generate the initial data collection form; see [link to relevant documentation]. Figure 2 Basic data may include at least one of the following: the company to which the data belongs, the data type, the data source, the data name, the period, and the data value.

[0085] In this embodiment of the invention, basic data can be acquired, such as collecting all associated data related to the target enterprise, and determining the basic data associated with the target functional model from the associated data. The target enterprise can be understood as an enterprise that needs to implement the target function through the target functional model. There can be at least one target enterprise. For each target enterprise, the form validation scheme of this embodiment can be implemented. That is, for each of the at least one target enterprise, the basic data associated with the target functional model of that target enterprise can be acquired. This is used to subsequently determine the historical data corresponding to the initial collection form of the target enterprise, determine historical feature values ​​based on the historical data, acquire the target collection form of the target enterprise, and validate the target collection form based on the historical feature values. If the form validation result is that the form validation passes, the target collection form can be processed through the target functional model.

[0086] S220. Based on the basic data, generate an initial data collection form corresponding to the target functional model. The initial data collection form is a form in which the target data collection data has not been filled in.

[0087] In this embodiment of the invention, an initial data collection form can be generated based on basic data, for example, see [link to example]. Figure 2 It can automatically generate a standardized initial data collection form based on at least one of the following data items: company affiliation, data type, data source, data name, period, and data value. Figure 2 (The data collection form in the document).

[0088] S230. Determine the historical data corresponding to the initial data collection form, and determine the historical feature values ​​based on the historical data, wherein the historical data includes historical data collection forms and / or historical data collection data filled in.

[0089] S240. Obtain the target collection form after filling in the target collection data on the initial collection form, and verify the target collection form according to the historical feature values. If the form verification result is that the form verification is passed, process the target collection form through the target function model.

[0090] The technical solution of this invention generates an initial data collection form corresponding to the target functional model based on basic data, which makes the initial data collection form more closely related to the target functional model, thereby making the format of the target data collection form more suitable for processing by the target functional model.

[0091] An optional technical solution involves generating an initial data collection form corresponding to a target functional model based on basic data, including: inputting basic data into the target functional model to generate an initial data collection form corresponding to the target functional model based on the basic data using the target functional model.

[0092] In this embodiment of the invention, basic data can be input into the target functional model. Based on the basic data, the target functional model can then automatically generate an initial data collection form corresponding to the target functional model. This allows for the integration of the initial data collection form generation process into the automated workflow of the target functional model's functional implementation, thereby enhancing the automation and intelligence level of the target functional model's workflow.

[0093] Based on any of the above solutions, another optional technical solution is to determine the historical data corresponding to the initial data collection form, including: using the target function model to determine the historical data corresponding to the initial data collection form; and / or, to obtain the target data collection form obtained after filling in the target data on the initial data collection form, including: using the target function model to obtain the target data collection form obtained after filling in the target data on the initial data collection form.

[0094] In this embodiment of the invention, a target function model can be used to determine historical data. For example, the target function model can be used to automatically obtain historical data through an initial data collection form.

[0095] In this embodiment of the invention, the target function model can be used to automatically obtain the target collection form.

[0096] The technical solution of this invention utilizes the target functional model to determine historical data and / or obtain target collection forms, thereby realizing an automated workflow for the functional implementation of the target functional model by combining the determination of historical data and / or the acquisition of target collection forms. This enhances the automation and intelligence level of the target functional model's workflow while improving the efficiency of target data collection.

[0097] Based on any of the above solutions, another optional technical solution is to determine historical feature values ​​based on historical data, including: using the target function model to call the form validation model, so as to use the form validation model to determine historical feature values ​​based on historical data; and / or, to validate the target collection form based on the historical feature values, including: using the target function model to call the form validation model, so as to use the form validation model to validate the target collection form based on the historical feature values.

[0098] Among them, the form validation model can be understood as a model used to validate the target data collection form; the form validation model is, for example, a model based on algorithms and rules that can automatically identify, analyze and correct errors in the target data collection form. The form validation model can achieve automated validation and verification of the target data collection form by analyzing the inherent rules and characteristics of the target data collection form and by using historical data collection and corresponding validation rules.

[0099] In this embodiment of the invention, the target functional model can be used to call the form validation model, so that the form validation logic can be automatically executed using the form validation model, and the target collected form can be validated based on historical feature values.

[0100] For example, see Figure 3 The form validation model can include a data preprocessing part, a validation rule base part, and a validation engine part. The data preprocessing part can determine historical feature values ​​based on historical data. The validation rule base part stores various validation rules, and it can determine the validation rules corresponding to the initially collected form from the validation rule base. The validation engine part can automatically validate the target collected form based on historical feature values ​​and validation rules to obtain the form validation result. Figure 3 (Verification results in the data).

[0101] The technical solution of this invention, by calling the form validation model through the target function model, realizes an automated workflow for integrating form validation into the function implementation of the target function model. This enhances the automation and intelligence level of the target function model's workflow, while improving the efficiency of target data collection and the accuracy of target forms.

[0102] To better understand the technical solutions of the above embodiments of the present invention, an optional example is provided herein. For example, see... Figure 5 Form validation can be embedded into workflow management. Workflow management can be understood as a series of activities that organize, define, execute, and monitor business processes, aiming to improve business efficiency and ensure data accuracy and consistency. It mainly includes process initiation, data entry, data review, and data confirmation. Specifically, in the process initiation stage, a specific user (such as an employee or department head) can initiate the process based on a visualized enterprise management evaluation model. The enterprise management evaluation model will automatically call the data collection form template to generate the corresponding initial data collection form for each target enterprise. Figure 5The system uses an initial data collection form (in the workflow management system) to automatically determine the target company's historical data and historical feature values. Based on these historical data, the process flows to the data entry stage according to preset rules. In the data entry stage, data entry personnel receive task notifications requiring data entry through workflow management. They download the initial data collection form, fill in the target data, and obtain the target data collection form. After completion, they can click "Data Validation" to invoke the form validation model. This model uses validation rules from the validation rule base and historical feature values ​​to validate the completeness, accuracy, and compliance of the target data collection form. If abnormal data is detected, the data entry personnel manually confirm the abnormal data marked as abnormal in the target data collection form, obtain the form validation result, save and submit the target data collection form, thus achieving business-level confirmation of the marked abnormal data. Based on preset rules, the process flows to the data review stage. In the data review stage, data review personnel receive forms requiring review through workflow management. The task notification for the verification results allows for decision-making based on the form verification results, such as approval, rejection, or modification of the target data collection form. Review comments corresponding to the target data collection form and its verification results are then provided. In cases of rejection or modification, the process can be redirected to the data confirmation stage according to pre-defined workflow management rules. During data confirmation, the data confirmation personnel can click "Data Verification" again. Based on the latest target data collection form filled out or modified by the data entry personnel, the form verification model is invoked again. Historical feature values ​​are used to verify the latest target data collection form against automated verification. Simultaneously, abnormal data is manually re-verified. After successful verification, clicking the "Complete" button yields the form verification result, enabling further business-level confirmation of the identified abnormal data. The process status is updated to "Completed," and the target data collection form is pushed to the relevant application and / or data warehouse. Throughout the workflow management process, each stage is closely interconnected, forming a closed loop. The automatic invocation of the form verification model in some stages significantly improves the automation and execution efficiency of the form verification process, reducing human error and communication costs.

[0103] Figure 6 This is a structural block diagram of a form validation apparatus provided in an embodiment of the present invention. This apparatus is used to execute the form validation method provided in any of the above embodiments. This apparatus and the form validation methods of the above embodiments belong to the same inventive concept. Details not described in detail in the embodiments of the form validation apparatus can be found in the embodiments of the above form validation methods. See also... Figure 6 The device may specifically include: an initial data collection form determination module 310, a historical feature value determination module 320, and a target data collection form verification module 330.

[0104] The initial data collection form determination module 310 is used to determine the initial data collection form corresponding to the target functional model. The initial data collection form is a form in which no target data collection data has been filled in.

[0105] The historical feature value determination module 320 is used to determine the historical data corresponding to the initial collection form and determine the historical feature value based on the historical data. The historical data includes historical collection forms filled with historical collection data and / or historical collection data.

[0106] The target collection form verification module 330 is used to obtain the target collection form after the target collection data is filled in on the initial collection form, and to verify the target collection form according to historical feature values. If the form verification result is that the form verification is passed, the target collection form is processed through the target function model.

[0107] Optionally, the initial data collection form determination module 310 includes:

[0108] The basic data acquisition submodule is used to acquire basic data associated with the target functional model;

[0109] The initial data collection form generation submodule is used to generate an initial data collection form corresponding to the target functional model based on the basic data.

[0110] Optionally, based on the above device, the initial data collection form generation submodule includes:

[0111] The initial data collection form generation unit is used to input basic data into the target functional model, so as to generate an initial data collection form corresponding to the target functional model based on the basic data.

[0112] Optionally, based on any of the above devices, the historical feature value determination module 320 includes:

[0113] The historical data determination submodule is used to determine the historical data corresponding to the initial data collection form using the target function model; and / or,

[0114] The target data collection form validation module 330 includes:

[0115] The target data collection form acquisition submodule is used to obtain the target data collection form after the target data collection data is filled in on the initial data collection form, using the target function model.

[0116] Optionally, based on any of the above devices, the historical feature value determination module 320 includes:

[0117] The historical feature value determination submodule is used to utilize the target functional model, call the form validation model, and then use the form validation model to determine historical feature values ​​based on historical data; and / or,

[0118] The target data collection form validation module 330 includes:

[0119] The first target collection form validation submodule is used to call the form validation model using the target function model, so as to validate the target collection form based on historical feature values.

[0120] Optionally, the device may also include:

[0121] The verification rule determination module is used to determine the verification rule corresponding to the initial data collection form from the preset verification rule library;

[0122] The target data collection form validation module 330 includes:

[0123] The second target data collection form validation submodule is used to validate the target data collection form based on historical feature values ​​and validation rules.

[0124] Optionally, the device may also include:

[0125] The target collection form transmission module is used to transmit the target collection form to the data modification end when the form validation result indicates that the form validation has failed.

[0126] The repetitive execution module is used to obtain the modified target collection form from the data modification end and repeatedly execute the process of validating the target collection form based on historical feature values.

[0127] Optionally, the target data collection form validation module 330 includes:

[0128] The third target collection form validation submodule is used to validate the target collection form based on historical feature values;

[0129] The target data collection form transmission submodule is used to annotate the target data collection form when abnormal data is found during verification, and then transmit the annotated target data collection form to the manual verification end so that the manual verification end can perform manual verification of the annotated target data collection form.

[0130] Optionally, the historical feature values ​​include at least one of the following: historical data values ​​within a preset historical period, historical average value, historical maximum value, historical minimum value, historical average absolute deviation value, month-on-month value, and fluctuation threshold.

[0131] The form verification device provided in this embodiment of the invention determines the initial collection form by identifying an initial collection form with unfilled target collection data corresponding to the target functional model; it determines the historical data corresponding to the initial collection form through a historical feature value determination module, and determines historical feature values ​​that can provide reference factors for form verification based on the historical data; it obtains the target collection form after the target collection data is filled in on the initial collection form through a target collection form verification module, and verifies the target collection form based on the historical feature values. If the form verification result is that the form verification is passed, the target collection form is processed by the target functional model to obtain a target collection form that can be processed by the target functional model. The aforementioned device, by determining an initial data collection form corresponding to the target functional model and filling in the target data, and by using the initial data collection form to determine historical feature values ​​and obtain the target data collection form, and by validating the target data collection form based on the historical feature values, not only makes the format of the target data collection form more suitable for processing by the target functional model, but also improves the accuracy of the target data collection form processed by the target functional model through the validation of the target data collection form using historical feature values. This avoids the problem of the target functional model processing data that is unsuitable for processing and has low accuracy, which would reduce the accuracy of the target functional model's functional implementation, thereby improving the accuracy of the target functional model's functional implementation.

[0132] The form validation device provided in this embodiment of the invention can execute the form validation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0133] It is worth noting that in the above-described form validation device embodiments, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0134] Figure 7 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0135] like Figure 7 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded into the RAM 13 from storage unit 18. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0136] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0137] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as form validation methods.

[0138] In some embodiments, the form validation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the form validation method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the form validation method by any other suitable means (e.g., by means of firmware).

[0139] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0140] Computer programs used to implement the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0141] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0142] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0143] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0144] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0145] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0146] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A form validation method, characterized in that, include: Determine the initial data collection form corresponding to the target functional model, wherein the initial data collection form is a form in which no target data has been filled in; Determine the historical data corresponding to the initial data collection form, and determine the historical feature value based on the historical data, wherein the historical data includes the historical data collection form filled in and / or the historical data collection data; The target collection form is obtained after the initial collection form is filled with the target collection data, and the target collection form is validated according to the historical feature values. If the form validation result is that the form validation is passed, the target collection form is processed by the target function model.

2. The method according to claim 1, characterized in that, The determination of the initial data collection form corresponding to the target functional model includes: Obtain the basic data associated with the target functional model; Based on the basic data, an initial data collection form corresponding to the target functional model is generated.

3. The method according to claim 2, characterized in that, The step of generating an initial data collection form corresponding to the target functional model based on the basic data includes: The basic data is input into the target functional model, so that the target functional model can be used to generate an initial data collection form corresponding to the target functional model based on the basic data.

4. The method according to any one of claims 1-3, characterized in that, The determination of historical data corresponding to the initial data collection form includes: Using the target function model, determine the historical data corresponding to the initial data collection form; and / or, The process of obtaining the target collection form after filling in the target collection data on the initial collection form includes: Using the target function model, obtain the target collection form after filling in the target collection data on the initial collection form.

5. The method according to any one of claims 1-3, characterized in that, The step of determining historical feature values ​​based on the historical data includes: Using the target function model, the form validation model is invoked to determine historical feature values ​​based on the historical data; and / or, The step of validating the target data collection form based on the historical feature values ​​includes: Using the target functional model, the form validation model is invoked to validate the target collection form based on the historical feature values.

6. The method according to claim 1, characterized in that, Also includes: Determine the verification rules corresponding to the initial data collection form from the preset verification rule library; The step of validating the target data collection form based on the historical feature values ​​includes: The target data collection form is validated based on the historical feature values ​​and the validation rules.

7. The method according to claim 1, characterized in that, Also includes: If the form validation result indicates that the form validation has failed, the target collected form is transmitted to the data modification terminal. The modified target collection form is obtained from the data modification terminal, and the process of verifying the target collection form based on the historical feature values ​​is repeated.

8. The method according to claim 1, characterized in that, The step of validating the target data collection form based on the historical feature values ​​includes: The target data collection form is validated based on the historical feature values. If abnormal data is found during verification, the target data collection form is marked as abnormal, and the marked target data collection form is passed to the manual verification end so that the manual verification end can manually verify the marked target data collection form.

9. The method according to claim 1, characterized in that, The historical feature values ​​include at least one of the following: historical data values ​​within a preset historical period, historical average value, historical maximum value, historical minimum value, historical average absolute deviation value, month-on-month value, and fluctuation threshold.

10. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to cause the at least one processor to perform the form validation method as described in any one of claims 1-9.

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