Data processing method, device and electronic equipment based on sample processing

Abstract

The present invention discloses a data processing method, device and electronic device based on sample processing. The method includes: when input data processing information is detected, detecting whether the target data volume contained in the data processing information is less than the preset data volume; if so, matching the data processing information with the pre-stored data samples through an automatic matching module; when the data processing information matches any target data sample in the pre-stored data samples, obtaining the processing method corresponding to the target data sample, and processing the data processing information according to the processing method. Under this method, the sample processing technology in the big data engine based on data analysis simplifies the process of data processing. In summary, the efficiency of data processing can be improved.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to a data processing method, device and electronic equipment based on sample processing. Background Art

[0002] At present, when processing data, a data processing device usually generates a processing method corresponding to the received data, and then processes the data using the determined processing method. However, in practice, it is found that among the several data received by the data processing device, there are usually data with similar processing methods. The data processing device needs to analyze each data to generate a processing method corresponding to each data, which makes the data processing process of the data processing device too cumbersome, thereby making the data processing efficiency low. Summary of the invention

[0003] In order to solve the technical problem of low efficiency of data processing existing in the related art, the present invention provides a data processing method, device and electronic device based on sample processing.

[0004] A data processing method based on sample processing, characterized in that the method comprises:

[0005] When the input data processing information is detected, detecting whether the target data amount contained in the data processing information is less than a preset data amount;

[0006] If yes, matching the data processing information with pre-stored data samples through an automatic matching module;

[0007] When the data processing information matches any target data sample in the pre-stored data samples, a processing method corresponding to the target data sample is obtained, and the data processing information is processed according to the processing method.

[0008] A data processing device based on sample processing, characterized in that the device comprises:

[0009] a detection unit, configured to detect, when input data processing information is detected, whether a target data amount contained in the data processing information is less than a preset data amount;

[0010] A matching unit, configured to match the data processing information with a pre-stored data sample through an automatic matching module when the result of the detection by the detection unit is yes;

[0011] An acquisition unit is used to acquire a processing method corresponding to a target data sample when the data processing information matches any target data sample in the pre-stored data samples, and process the data processing information according to the processing method.

[0012] An electronic device, comprising:

[0013] processor;

[0014] A memory having computer-readable instructions stored therein, wherein the computer-readable instructions, when executed by the processor, implement the aforementioned method.

[0015] A computer-readable storage medium, characterized in that it stores a computer program, wherein the computer program enables a computer to execute the method as described above.

[0016] The technical solution provided by the embodiments of the present invention may have the following beneficial effects:

[0017] The data processing method based on sample processing provided by the present invention includes the following steps: when input data processing information is detected, whether the target data amount contained in the data processing information is less than the preset data amount; if so, matching the data processing information with the pre-stored data samples through the automatic matching module; when the data processing information matches any target data sample in the pre-stored data samples, obtaining the processing method corresponding to the target data sample, and processing the data processing information according to the processing method.

[0018] Under this method, the sample processing technology in the big data engine based on data analysis can detect the data volume of the input data processing information. Only the data processing information with a smaller data volume can be matched with the pre-stored data samples, thereby determining the processing method of the data sample, and then processing the data processing information through the determined processing method, simplifying the data processing process. In summary, the efficiency of data processing can be improved.

[0019] It is to be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0021] Figure 1 is a schematic diagram of a network scenario applicable to a reimbursement method based on risk management according to an exemplary embodiment;

[0022] Figure 2 is a flow chart of a reimbursement method based on risk management according to an exemplary embodiment;

[0023] Figure 3is a flow chart of a reimbursement method based on risk management according to another exemplary embodiment;

[0024] Figure 4 is a block diagram of a reimbursement device based on risk management according to an exemplary embodiment;

[0025] Figure 5 It is a block diagram of a reimbursement device based on risk management according to another exemplary embodiment. DETAILED DESCRIPTION

[0026] Here, exemplary embodiments will be described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0027] The implementation environment of the present invention may be a portable mobile device, such as a smart phone, a tablet computer, or a desktop computer. The images stored in the portable mobile device may be: images downloaded from the Internet; images received via a wireless connection or a wired connection; images captured by a built-in camera.

[0028] Figure 1 1 is a schematic diagram of a device according to an exemplary embodiment. The device 100 may be the portable mobile device mentioned above. Figure 1 As shown, the apparatus 100 may include one or more of the following components: a processing component 102 , a memory 104 , a power component 106 , a multimedia component 108 , an audio component 110 , a sensor component 114 , and a communication component 116 .

[0029] The processing component 102 generally controls the overall operation of the device 100, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 102 may include one or more processors 118 to execute instructions to perform all or part of the steps of the method described below. In addition, the processing component 102 may include one or more modules to facilitate the interaction between the processing component 102 and other components. For example, the processing component 102 may include a multimedia module to facilitate the interaction between the multimedia component 108 and the processing component 102.

[0030] The memory 104 is configured to store various types of data to support operations on the device 100. Examples of such data include instructions for any application or method operating on the device 100. The memory 104 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The memory 104 also stores one or more modules, which are configured to be executed by the one or more processors 118 to complete all or part of the steps in the method shown below.

[0031] The power supply component 106 provides power to the various components of the device 100. The power supply component 106 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 100.

[0032] The multimedia component 108 includes a screen that provides an output interface between the device 100 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel. If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. The screen may also include an organic light emitting display (OLED).

[0033] The audio component 110 is configured to output and / or input audio signals. For example, the audio component 110 includes a microphone (MIC), which is configured to receive external audio signals when the device 100 is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode. The received audio signal can be further stored in the memory 104 or sent via the communication component 116. In some embodiments, the audio component 110 also includes a speaker for outputting audio signals.

[0034] The sensor assembly 114 includes one or more sensors for providing various aspects of status evaluation for the device 100. For example, the sensor assembly 114 can detect the open / closed state of the device 100, the relative positioning of the components, and the sensor assembly 114 can also detect the position change of the device 100 or a component of the device 100 and the temperature change of the device 100. In some embodiments, the sensor assembly 114 can also include a magnetic sensor, a pressure sensor or a temperature sensor.

[0035] The communication component 116 is configured to facilitate wired or wireless communication between the device 100 and other devices. The device 100 can access a wireless network based on a communication standard, such as WiFi (Wireless-Fidelity). In an exemplary embodiment, the communication component 116 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 116 also includes a near field communication (NFC) module for facilitating short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth technology and other technologies.

[0036] In an exemplary embodiment, the device 100 can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors, digital signal processing devices, programmable logic devices, field programmable gate arrays, controllers, microcontrollers, microprocessors or other electronic components to perform the following method.

[0037] Figure 2 FIG. 1 is a flow chart of a data processing method based on sample processing according to an exemplary embodiment. Figure 2As shown, this method includes the following steps.

[0038] Step 201, when the input data processing information is detected, whether the target data volume contained in the data processing information is less than the preset data volume, if yes, execute steps 202 to 203; if no, end this process.

[0039] In an embodiment of the present invention, the data processing information may be reimbursement application information, the target data volume may be the reimbursement amount in the reimbursement application information, and the preset data volume may meet the requirements for automatic review of small reimbursements, that is, the reimbursement application information may include the user's personal information, the reimbursement amount, reimbursement items, invoice information, etc. The user's personal information may include the user's name, age, position, department, number, etc., and it may be determined whether the user is an employee of the enterprise based on the user's personal information. If the user is not an employee of the enterprise, the reimbursement application information input by the user will not be accepted; if the user is an employee of the enterprise, it is detected whether the reimbursement amount in the reimbursement application information meets the requirements for automatic review of small reimbursements. Since the reimbursement amount for small reimbursements is small, even if an error occurs during reimbursement, the impact on the enterprise is small, so the reimbursement application information with a small reimbursement amount can be automatically approved, thereby improving the efficiency of reimbursement application review.

[0040] Optionally, when automatically approving reimbursement application information, the information that appears in the approval process can be recorded so that the financial staff can review the reimbursement approval process after the reimbursement is completed. If the financial staff finds that an error occurred during the reimbursement approval process, the reimbursement amount can be recovered based on the stored personal information of the user who applied for reimbursement, thereby ensuring the property safety of the company.

[0041] In an embodiment of the present invention, the preset reimbursement amount can be calculated based on previous reimbursement application information, the applied reimbursement amount in the previous reimbursement application information can be obtained, and a normal distribution curve related to the applied reimbursement amount can be generated through big data calculation, and the applied reimbursement amount with the highest probability of occurrence is determined based on the generated normal distribution curve, and the applied reimbursement amount is determined as the preset reimbursement amount, so that most reimbursement applications can be automatically approved, and the reimbursement amount will not be too high, thereby improving the efficiency of the reimbursement process.

[0042] Step 202: Match the data processing information with the pre-stored data samples through the automatic matching module.

[0043] In an embodiment of the present invention, the automatic matching module can be an automatic approval module, and the data sample can be a pre-stored standard sample for reimbursement information approval. The automatic approval module can automatically approve the reimbursement application information input by the user, and the approval method can include verifying the user's identity information, verifying the authenticity of the invoice, verifying the matching of the invoice information and the reimbursement information, etc.

[0044] Step 203: when the data processing information matches any target data sample in the pre-stored data samples, a processing method corresponding to the target data sample is obtained, and the data processing information is processed according to the processing method.

[0045] In an embodiment of the present invention, after the data processing information matches any target data sample in the pre-stored data samples, the processing method corresponding to the target data sample may be to obtain the reimbursement amount corresponding to the information of this reimbursement, and to issue the reimbursement amount to the account of the user who inputs the reimbursement application information, and the reimbursement amount in the reimbursement application information may be determined as the amount of reimbursement that needs to be issued to the user. In addition, the reimbursement application information input by the user may also include the user's account information, so that the reimbursement amount is issued to the user's account after the reimbursement application information is approved.

[0046] As an optional implementation, after step 203, the following steps may also be performed:

[0047] A data processing credential is generated according to the data processing information and the data processing credential is stored.

[0048] Among them, by implementing this implementation method, data processing credentials can be generated based on all the information of this data processing process, so that management personnel can review each data processing information at any time to ensure the security of the data processing process.

[0049] For example, data processing information can be reimbursement application information, and data processing vouchers can be reimbursement accounting vouchers, which can then be generated based on all the information generated by the reimbursement process, so that financial personnel or leaders and other personnel can review each reimbursement application at any time to ensure the security of the company's finances.

[0050] exist Figure 2 The method described can simplify the process of data processing and improve the efficiency of data processing. Figure 2 The described method can review each data processing information at any time to ensure the security of the data processing process.

[0051] Figure 3 FIG. 1 is a flow chart of a data processing method based on sample processing according to another exemplary embodiment. Figure 3 As shown, this method includes the following steps.

[0052] Step 301, obtain pre-stored historical data processing information, and divide the historical data processing information according to the data type in the historical data processing information to obtain at least one data processing information group, wherein one data processing information group corresponds to one data type.

[0053] In the embodiment of the present invention, the historical data processing information may be historical reimbursement application information, the data type may be a reimbursement item, the average data volume may be an application reimbursement amount, and the historical reimbursement application information may include personal information of the user who inputs the historical reimbursement application information, the application reimbursement amount, the reimbursement item, invoice information, etc. In addition, the embodiment of the present invention does not limit the number of historical reimbursement application information. When there are multiple historical reimbursement application information, one or more reimbursement items may be obtained, and then the historical reimbursement application information with the same reimbursement items may be divided into the same group. When there are multiple reimbursement items, multiple historical reimbursement application information groups may be obtained.

[0054] Step 302, according to the data volume in the data processing application information, respectively calculate the average data volume of each data processing information group, wherein one data processing information group corresponds to one average data volume.

[0055] In an embodiment of the present invention, by implementing the above-mentioned steps 301 to 302, different historical data processing information can be classified according to different data types, and then the average data volume corresponding to the different data types can be calculated, so that the determination of the average data volume conforms to the actual data processing situation, thereby improving the intelligence of the average data volume calculation.

[0056] Step 303, when an input data processing request is detected, the data processing interface is output and displayed, and data processing information is output in the data processing interface. The data processing information is used to prompt the input of data processing information through the data processing interface. The data processing information at least includes data address information, data type and data amount.

[0057] In the embodiment of the present invention, the data processing interface can be a reimbursement application interface, the data processing information can be reimbursement prompt information, the data address information can be the user's personal information, the reimbursement application interface can be displayed through a display output, and the reimbursement prompt information can be displayed and output on the reimbursement application interface in the form of text. In addition, the reimbursement prompt information can also be output in the form of sound through a speaker of the reimbursement device based on risk management. And the user can input the invoice image corresponding to the invoice as the invoice information in the reimbursement application information.

[0058] Step 304: when it is detected that the completion instruction is triggered, the input data processing information is obtained from the data processing interface.

[0059] In the embodiment of the present invention, the implementation of the above steps 303 to 304 can prompt the user to fill in the data processing information, so that the filled-in data processing information is more accurate, further improving the intelligence of the data processing flow.

[0060] Step 305: when input data processing information is detected, the target data type is obtained from the data processing information.

[0061] As an optional implementation, when the input data processing information is detected, the method of obtaining the target data type from the data processing information may specifically include the following steps:

[0062] When the input data processing information is detected, obtaining data address information from the data processing information;

[0063] Obtaining a credit value corresponding to the data address information from a pre-built credit model;

[0064] Determine whether the credit value is greater than the preset credit value;

[0065] If yes, get the target data type from the data processing information.

[0066] Among them, by implementing this implementation method, after confirming that the credit value of the data address information of the data processing information meets the credit requirements of automatic matching, it is possible to detect whether the target data volume of this data processing meets the preset data volume requirements, thereby avoiding the detection of the data address information of the data processing information whose credit value does not meet the requirements, and improving the efficiency of determining whether the data processing information can be automatically matched.

[0067] For example, the data processing information filled in can be the user of the data processing device, the data processing information can be the reimbursement application information, and the credit requirement can be the credit requirement for automatic approval of small reimbursements. That is, after confirming that the credit value of the user applying for reimbursement meets the credit requirements for automatic approval of small reimbursements, it can be checked whether the reimbursement amount applied for this reimbursement meets the amount requirement for exemption from review for small reimbursements, thereby avoiding the detection of the reimbursement amount applied for by users whose credit values ​​do not meet the requirements, and improving the efficiency of determining whether the reimbursement application can be automatically approved.

[0068] Step 306: Determine a target data processing information group that matches the target data type from the data processing information groups, and determine a target average data volume corresponding to the target data processing information group.

[0069] In an embodiment of the present invention, it is possible to first search from the reimbursement application information group to see whether the target reimbursement item exists. If so, the target reimbursement application information group matching the target reimbursement item can be obtained. If not, the average value of the application reimbursement amounts in the historical reimbursement application information can be calculated, and the average value can be determined as the target average reimbursement amount, thereby ensuring the accuracy of the determination of the target average reimbursement amount.

[0070] Step 307, determine the target average data volume as the preset data volume, and detect whether the target data volume contained in the data type information is less than the preset data volume. If so, execute steps 308 to 310; if not, end this process.

[0071] In the embodiment of the present invention, by implementing the above steps 305 to 307, the average data volume corresponding to the data type of the data processing information group can be obtained, and after determining that the current target data volume is less than the average data volume, the current data processing is converted to automatic matching data processing, and the data processing information can be automatically matched when the data volume is small, thereby improving the speed of matching the data processing information.

[0072] Step 308: Acquire the data information image contained in the data processing information through the automatic matching module.

[0073] Step 309, identifying the data information image by using character recognition technology to obtain current data information contained in the data information image, where the current data information at least includes the current data type and the current data amount.

[0074] In the embodiment of the present invention, the character recognition technology may be an optical character recognition (OCR) technology. The OCR technology may first recognize text information contained in the invoice image, and integrate the recognized text information to obtain the invoice information contained in the invoice image.

[0075] As an optional implementation, after step 309, the following steps may also be performed:

[0076] Pack the current data type and current data amount read from the current data information to obtain a data packet corresponding to the current data information;

[0077] Send data packets to the inspection platform through the inspection interface, so that the inspection platform can check the rationality of the current data information according to the data packets;

[0078] When it is detected that the inspection result fed back by the inspection platform is passed, step 310 is executed.

[0079] Among them, by implementing this implementation method, the rationality of the current data information can be queried through the verification platform, and based on the rationality of the current data information, it can assist in judging whether the data processing information matches this time, so as to make the matching of the data processing information more accurate.

[0080] For example, the verification platform may be an invoice verification platform, the current data information may be an invoice, and the rationality of the current data information may be the authenticity of the invoice. That is, the authenticity of the invoice may be queried through the invoice verification platform, and the authenticity of the invoice may be used to assist in determining whether the reimbursement application is approved, so as to make the approval of the reimbursement application more accurate.

[0081] Step 310, detect whether the current data type matches the target data type of any target data sample in the pre-stored data samples and whether the current data volume matches the target data volume in the target data sample. If so, execute steps 311 to 312; if not, end this process.

[0082] Step 311: determine whether the data processing information matches a target data sample in the pre-stored data samples.

[0083] In an embodiment of the present invention, by implementing the above-mentioned steps 308 to 311, the data information image can be identified through character recognition technology to obtain the current data information contained in the data information image, and the filled-in data processing information can be detected based on the current data information, thereby ensuring that the uploaded current data information matches the data processing information.

[0084] Step 312: when the data processing information matches any target data sample in the pre-stored data samples, a processing method corresponding to the target data sample is obtained, and the data processing information is processed according to the processing method.

[0085] exist Figure 3 The method described can simplify the process of data processing and improve the efficiency of data processing. Figure 3 The described method improves the intelligence of the average data volume calculation. In addition, the implementation Figure 3 The described method improves the intelligence of data processing process. In addition, implementation Figure 3 The described method improves the efficiency of determining whether data processing information can be automatically matched. In addition, implementation Figure 3 The described method can improve the speed of matching data processing information. In addition, implementation Figure 3 The described method can make the matching of data processing information more accurate. In addition, implementation Figure 3 The described method ensures that the uploaded current data information matches the data processing information.

[0086] The following are device embodiments of the present invention.

[0087] Figure 4 FIG. 1 is a block diagram of a data processing device based on sample processing according to an exemplary embodiment. Figure 4 As shown, the device comprises:

[0088] The detection unit 401 is used to detect whether the target data amount contained in the data processing information is less than the preset data amount when the input data processing information is detected.

[0089] The matching unit 402 is used to match the data processing information with the pre-stored data samples through the automatic matching module when the detection result of the detection unit 401 is yes.

[0090] The acquisition unit 403 is used to acquire the processing mode corresponding to the target data sample when the matching unit 402 determines that the data processing information matches any target data sample in the pre-stored data samples, and process the data processing information according to the processing mode.

[0091] As an optional implementation, the acquiring unit 403 may also be used to:

[0092] A data processing credential is generated according to the data processing information and the data processing credential is stored.

[0093] Among them, by implementing this implementation method, data processing credentials can be generated based on all the information of this data processing process, so that management personnel can review each data processing information at any time to ensure the security of the data processing process.

[0094] It can be seen that in Figure 4 In the described device, the process of data processing can be simplified and the efficiency of data processing can be improved. Figure 4 In the described device, each data processing information can be reviewed at any time to ensure the security of the data processing process.

[0095] Figure 5 is a block diagram of a data processing device based on sample processing according to another exemplary embodiment. Figure 5 The data processing device based on sample processing shown is composed of Figure 4 The data processing device shown in the figure is optimized based on sample processing. Figure 4 Compared with the data processing device based on sample processing shown, Figure 5 The data processing device based on sample processing shown may also include:

[0096] The output unit 404 is used to output and display the data processing interface and output the data processing information in the data processing interface when the detection unit 401 detects the input data processing information and detects whether the target data amount contained in the data processing information is less than the preset data amount, and when the input data processing request is detected. The data processing information is used to prompt the input of the data processing information through the data processing interface, and the data processing information at least includes data address information, data type and data amount.

[0097] The information acquisition unit 405 is used to acquire the input data processing information from the data processing interface output by the output unit 404 when it is detected that the completion instruction is triggered.

[0098] In the embodiment of the present invention, a prompt may be provided to fill in the data processing information, so that the filled-in data processing information is more accurate, further improving the intelligence of the data processing flow.

[0099] As an optional implementation, Figure 5 The data processing device based on sample processing shown may also include:

[0100] The dividing unit 406 is used to obtain the pre-stored historical data processing information before outputting and displaying the data processing interface when the output unit 404 detects the input data processing request, and divide the historical data processing information according to the data type in the historical data processing information to obtain at least one data processing information group, wherein one data processing information group corresponds to one data type;

[0101] The calculation unit 407 is used to calculate the average data volume of each data processing information group according to the data volume in the data processing application information obtained by the division unit 406, wherein one data processing information group corresponds to one average data volume.

[0102] Among them, by implementing this implementation method, different historical data processing information can be classified according to different data types, and then the average data volume corresponding to different data types can be calculated, so that the determination of the average data volume conforms to the actual data processing situation, thereby improving the intelligence of the average data volume calculation.

[0103] As an optional implementation, Figure 5 The detection unit 401 of the data processing device based on sample processing shown may include:

[0104] The first acquisition subunit 4011 is used to acquire the target data type from the data processing information when the input data processing information is detected;

[0105] The first determining subunit 4012 is used to determine, from the data processing information groups, a target data processing information group that matches the target data type obtained by the first obtaining subunit 4011, and determine a target average data volume corresponding to the target data processing information group;

[0106] The first detection subunit 4013 is used to determine the target average data volume determined by the first determination subunit 4012 as the preset data volume, and detect whether the target data volume included in the data type information is smaller than the preset data volume.

[0107] Among them, by implementing this implementation method, the average data volume corresponding to the data type of the data processing information group can be obtained, and after determining that the current target data volume is less than the average data volume, the current data processing is converted into automatic matching data processing, and the data processing information can be automatically matched when the data volume is small, thereby improving the speed of matching the data processing information.

[0108] As an optional implementation, when the first acquisition subunit 4011 detects the input data processing information, the method of acquiring the target data type from the data processing information may be:

[0109] When the input data processing information is detected, obtaining data address information from the data processing information;

[0110] Obtaining a credit value corresponding to the data address information from a pre-built credit model;

[0111] Determine whether the credit value is greater than the preset credit value;

[0112] If yes, get the target data type from the data processing information.

[0113] Among them, by implementing this implementation method, after confirming that the credit value of the data address information of the data processing information meets the credit requirements of automatic matching, it is possible to detect whether the target data volume of this data processing meets the preset data volume requirements, thereby avoiding the detection of the data address information of the data processing information whose credit value does not meet the requirements, and improving the efficiency of determining whether the data processing information can be automatically matched.

[0114] As an optional implementation, Figure 5 The matching unit 402 of the data processing apparatus based on sample processing shown may include:

[0115] The second acquisition subunit 4021 is used to acquire the data information image contained in the data processing information through the automatic matching module when the result of the detection by the detection unit 401 is yes;

[0116] The recognition subunit 4022 is used to recognize the data information image acquired by the second acquisition subunit 4021 by using a character recognition technology to obtain current data information contained in the data information image, where the current data information at least includes a current data type and a current data amount;

[0117] The second detection subunit 4023 is used to detect whether the current data type obtained by the identification subunit 4022 matches the target data type of any target data sample in the pre-stored data samples and whether the current data volume matches the target data volume in the target data sample;

[0118] The second determining subunit 4024 is used to determine, when the result of detection by the second detecting subunit 4023 is yes, whether the data processing information matches the target data sample in the pre-stored data samples.

[0119] Among them, by implementing this implementation method, the data information image can be identified through character recognition technology to obtain the current data information contained in the data information image, and the filled-in data processing information can be detected based on the current data information, ensuring that the uploaded current data information matches the data processing information.

[0120] As an optional implementation, the identification subunit 4022 may also be used for:

[0121] Pack the current data type and current data amount read from the current data information to obtain a data packet corresponding to the current data information;

[0122] Send the data packet to the inspection platform through the inspection interface, so that the inspection platform can inspect the rationality of the current data information according to the data packet;

[0123] When it is detected that the inspection result fed back by the received inspection platform is passed, the second detection sub-unit 4023 is triggered to execute detection whether the current data type matches the target data type of any target data sample in the pre-stored data samples and whether the current data amount matches the target data amount in the target data sample.

[0124] Among them, by implementing this implementation method, the rationality of the current data information can be queried through the verification platform, and based on the rationality of the current data information, it can assist in judging whether the data processing information matches this time, so as to make the matching of the data processing information more accurate.

[0125] It can be seen that in Figure 5 In the described device, the process of data processing can be simplified and the efficiency of data processing can be improved. Figure 5 In the described device, the intelligence of the average data volume calculation is improved. Figure 5In the device described, the intelligence of data processing is improved. Figure 5 In the described device, the efficiency of determining whether data processing information can be automatically matched is improved. In addition, Figure 5 In the described device, the speed of matching data processing information can be improved. Figure 5 In the described device, the matching of data processing information can be made more accurate. Figure 5 In the described device, it is ensured that the uploaded current data information matches the data processing information.

[0126] The present invention also provides an electronic device, the electronic device comprising:

[0127] processor;

[0128] A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the data processing method based on sample processing as shown above is implemented.

[0129] The electronic device may be Figure 1 The device 100 is shown.

[0130] In an exemplary embodiment, the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the risk management-based reimbursement method as shown above is implemented.

[0131] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be performed without departing from its scope. The scope of the present invention is limited only by the appended claims.

Claims

1. A data processing method based on sample processing, characterized in that: The method comprises: Obtain the reimbursement amount in the historical reimbursement application information, and generate a normal distribution curve related to the reimbursement amount through big data calculation, and determine the reimbursement amount with the highest probability of occurrence as the preset reimbursement amount based on the generated normal distribution curve, and use it as the preset data volume; When the input data processing information is detected, detecting whether the target data amount contained in the data processing information is less than a preset data amount; If yes, automatically review and approve the data processing information, and match the data processing information with pre-stored data samples through an automatic matching module; When the data processing information matches any target data sample in the pre-stored data samples, a processing method corresponding to the target data sample is obtained, and the data processing information is processed according to the processing method.

2. The method according to claim 1, characterized in that When the input data processing information is detected, before detecting whether the target data amount contained in the data processing information is less than the preset data amount, the method further includes: When an input data processing request is detected, a data processing interface is output and displayed, and data processing information is output in the data processing interface, where the data processing information is used to prompt the input of data processing information through the data processing interface, and the data processing information at least includes data address information, data type, and data amount; When it is detected that the completion instruction is triggered, the input data processing information is obtained from the data processing interface.

3. The method according to claim 2, characterized in that When the input data processing request is detected, before outputting and displaying the data processing interface, the method further includes: Acquire pre-stored historical data processing information, and divide the historical data processing information according to the data type in the historical data processing information to obtain at least one data processing information group, wherein one data processing information group corresponds to one data type; Calculate the average data volume of each data processing information group according to the data volume in the data processing application information, wherein one data processing information group corresponds to one average data volume; When the input data processing information is detected, detecting whether the target data amount contained in the data processing information is less than a preset data amount includes: When the input data processing information is detected, obtaining a target data type from the data processing information; Determine a target data processing information group that matches the target data type from the data processing information groups, and determine a target average data volume corresponding to the target data processing information group; The target average data volume is determined as a preset data volume, and it is detected whether the target data volume included in the data type information is smaller than the preset data volume.

4. The method according to claim 3, characterized in that When the input data processing information is detected, obtaining the target data type from the data processing information includes: When the input data processing information is detected, acquiring data address information from the data processing information; Acquire a credit value corresponding to the data address information from a pre-built credit model; Determining whether the credit value is greater than a preset credit value; If yes, the target data type is obtained from the data processing information.

5. The method according to claim 4, characterized in that The step of matching the data processing information with the pre-stored data samples by the automatic matching module includes: Acquiring the data information image contained in the data processing information through the automatic matching module; Recognize the data information image by character recognition technology to obtain current data information contained in the data information image, wherein the current data information at least includes a current data type and a current data amount; Detecting whether the current data type matches a target data type of any target data sample in the pre-stored data samples and whether the current data volume matches a target data volume in the target data sample; If the current data type matches the target data type and the current data amount matches the target data amount, it is determined that the data processing information matches the target data sample in the pre-stored data samples.

6. The method according to claim 5, characterized in that After the data information image is identified by the character recognition technology to obtain the current data information contained in the data information image, and before the detection of whether the current data type matches the target data type of any target data sample in the pre-stored data samples and whether the current data amount matches the target data amount in the target data sample, the method further includes: Packing the current data type and the current data amount read from the current data information to obtain a data packet corresponding to the current data information; Sending the data packet to the inspection platform through the inspection interface, so that the inspection platform inspects the rationality of the current data information according to the data packet; When it is detected that the inspection result received from the inspection platform is passed, the detection is performed to determine whether the current data type matches the target data type of any target data sample in the pre-stored data samples and whether the current data volume matches the target data volume in the target data sample.

7. The method according to any one of claims 1 to 6, characterized in that: After processing the data processing information according to the processing method, the method further includes: A data processing credential is generated according to the data processing information, and the data processing credential is stored.

8. A data processing device based on sample processing, characterized in that: The device comprises: The device is configured to obtain the reimbursement amount in the historical reimbursement application information, and generate a normal distribution curve related to the reimbursement amount through big data calculation, and determine the reimbursement amount with the highest probability of occurrence as the preset reimbursement amount according to the generated normal distribution curve, and use it as the preset data volume; a detection unit, configured to detect, when input data processing information is detected, whether a target data amount contained in the data processing information is less than a preset data amount; a matching unit, configured to automatically review and approve the data processing information when the result of the detection by the detection unit is yes, and match the data processing information with a pre-stored data sample through an automatic matching module; An acquisition unit is used to acquire a processing method corresponding to a target data sample when the data processing information matches any target data sample in the pre-stored data samples, and process the data processing information according to the processing method.

9. An electronic device, characterized in that: The electronic device comprises: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The device stores a computer program, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 7.

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