Data processing method and device for off-cabinet cleaning equipment

Abstract

The application provides a data processing method and device of an out-of-cabinet clearing device, which can be used in the financial field or other fields. The method comprises the following steps: according to a preset splitting rule, splitting and processing acquired transaction data to obtain dynamic data and static data corresponding to the transaction data; performing eigenvalue calculation processing on the static data to obtain eigenvalues corresponding to the static data, and performing difference comparison processing on the eigenvalues corresponding to the static data to generate a difference comparison result; according to the difference comparison result, recombining the dynamic data and the static data to generate recombined transaction data, and sending the recombined transaction data to the out-of-cabinet clearing device for transaction processing. The application solves the problem of lag caused by the use of the out-of-cabinet clearing device in the cloud desktop high-latency scene, reduces the data transmission size by splitting the transaction data, analyzes and compares the differences in the static data, transmits the difference data, avoids repeated transmission, reduces the number of interactions, and improves the use performance of the out-of-cabinet clearing device.

Description

Technical Field

[0001] This invention relates to the field of cabinet external cleaning equipment technology, and more particularly to a data processing method and apparatus for cabinet external cleaning equipment. Background Technology

[0002] Currently, when banks provide services to customers at bank counters, customer feedback and evaluations are typically provided using a keypad evaluation device (off-counter clearing). The off-counter clearing screen often displays advertisements and promotional information to facilitate marketing activities. Each transaction's data generally includes dynamic data (transaction information, customer information) and static data (images, templates, etc.), ranging in size from tens to hundreds of megabytes. If the transaction occurs locally on a PC, a direct USB connection to the off-counter clearing ensures smooth operation due to the near-zero latency of network transmission between the USB cable and the PC. However, with the development of new technologies, the deployment of business terminals in some branches has changed significantly. For example, some banks have begun using cloud desktops to handle counter services, thus requiring a connection between the off-counter clearing system and the cloud desktop.

[0003] Because the cloud desktop is deployed in the data center server room, while the teller's PC terminal is deployed locally at the branch, there is network latency between the branch and the data center. Furthermore, USB devices typically use the HID protocol for transmission within the cloud desktop; due to HID protocol limitations, the maximum transmission size of a single data packet is only 1MB. Therefore, the business system needs to transmit hundreds of data packets between the cloud desktop and the off-site clearing system, and after processing the transaction, the off-site clearing system also needs to return the business information to the business system, resulting in hundreds of interactions between the two sides. In this scenario, lag occurs, and the higher the latency, the more severe the lag, affecting the normal processing of business. Summary of the Invention

[0004] To address the problems existing in the prior art, the main objective of this invention is to provide a data processing method and apparatus for external cabinet cleaning equipment, thereby avoiding repeated data transmission, reducing the number of interactions, and improving the performance of external cabinet cleaning.

[0005] To achieve the above objectives, embodiments of the present invention provide a data processing method for an external cleaning device, the method comprising:

[0006] According to the preset splitting rules, the acquired transaction data is split to obtain the dynamic data and static data corresponding to the transaction data;

[0007] The static data is processed by eigenvalue calculation to obtain the corresponding eigenvalues, and the eigenvalues ​​corresponding to the static data are compared to generate the comparison results.

[0008] Based on the difference comparison results, the dynamic data and the static data are recombined to generate recombined transaction data, which is then sent to the off-counter clearing equipment for transaction processing.

[0009] Optionally, in one embodiment of the present invention, the method further includes:

[0010] Obtain transaction feedback data sent by off-counter clearing equipment;

[0011] The transaction feedback data is transmitted to the transaction processing backend server to complete the transaction processing.

[0012] Optionally, in one embodiment of the present invention, the acquired transaction data is split according to a preset splitting rule to obtain dynamic data and static data corresponding to the transaction data, including:

[0013] Based on the data change time and data storage location in the preset splitting rules, dynamic and static data in the transaction data are identified to obtain data identification results;

[0014] Based on the data identification results, the transaction data is split and processed to obtain the corresponding dynamic and static data.

[0015] Optionally, in one embodiment of the present invention, performing feature value calculation on static data to obtain the feature values ​​corresponding to the static data includes:

[0016] The average value of the static data is calculated to obtain the average value of the static data, and the average value is used as the feature value of the static data.

[0017] Optionally, in one embodiment of the present invention, performing difference comparison processing on the feature values ​​corresponding to the static data to generate difference comparison results includes:

[0018] Obtain the feature value corresponding to the previously transmitted static data that was previously stored in the external clearing device;

[0019] The feature values ​​corresponding to the static data are compared with the feature values ​​corresponding to the previously transmitted static data to generate a difference comparison result.

[0020] Optionally, in one embodiment of the present invention, based on the difference comparison results, dynamic data and static data are recombined to generate recombined transaction data, including:

[0021] Based on the difference comparison results, identify the differential static data in the static data;

[0022] Dynamic data and differing static data are recombined to generate recombined transaction data.

[0023] Optionally, in one embodiment of the present invention, determining the differential static data in the static data based on the difference comparison results includes:

[0024] The difference comparison results are compared with the preset difference threshold to identify the data in the static data whose difference comparison results exceed the difference threshold, and the data in the static data whose difference comparison results exceed the difference threshold are taken as the difference static data.

[0025] This invention also provides a data processing device for an external cleaning device, the device comprising:

[0026] The data splitting module is used to split the acquired transaction data according to preset splitting rules to obtain the dynamic and static data corresponding to the transaction data.

[0027] The difference comparison module is used to perform feature value calculation on static data to obtain the feature values ​​corresponding to the static data, and to perform difference comparison on the feature values ​​corresponding to the static data to generate difference comparison results.

[0028] The data recombination module is used to recombine the dynamic data and the static data based on the difference comparison results, generate recombined transaction data, and send the recombined transaction data to the off-counter clearing equipment for transaction processing.

[0029] Optionally, in one embodiment of the present invention, the device further includes: a feedback data module, used to acquire transaction feedback data sent by the off-counter clearing device and transmit the transaction feedback data to the transaction processing backend server to complete the transaction processing.

[0030] Optionally, in one embodiment of the present invention, the data splitting module includes:

[0031] The data identification unit is used to identify dynamic and static data in transaction data according to the data change time and data storage location in the preset splitting rules, and obtain data identification results;

[0032] The data splitting unit is used to split the transaction data according to the data identification results to obtain the corresponding dynamic and static data.

[0033] Optionally, in one embodiment of the present invention, the difference comparison module is further used to calculate the average value of the static data, obtain the average value corresponding to the static data, and use the average value as the feature value corresponding to the static data.

[0034] Optionally, in one embodiment of the present invention, the difference comparison module includes:

[0035] The feature value acquisition unit is used to acquire the feature value corresponding to the previously transmitted static data that was pre-stored from the external clearing device.

[0036] The difference comparison unit is used to compare the feature values ​​corresponding to the static data with the feature values ​​corresponding to the previously transmitted static data to generate difference comparison results.

[0037] Optionally, in one embodiment of the present invention, the data reconstruction module includes:

[0038] The difference data unit is used to determine the difference static data in the static data based on the difference comparison results;

[0039] The data recombination unit is used to recombine dynamic data and differential static data to generate recombined transaction data.

[0040] Optionally, in one embodiment of the present invention, the difference data unit is further configured to compare the difference comparison result with a preset difference threshold, determine the data in the static data whose difference comparison result exceeds the difference threshold, and use the data in the static data whose difference comparison result exceeds the difference threshold as the difference static data.

[0041] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method.

[0042] The present invention also provides a computer-readable storage medium storing a computer program for performing the above-described methods.

[0043] The present invention also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the above-described method.

[0044] This invention solves the problem of lag in the use of the password keyboard evaluator (off-counter clearing) in high-latency cloud desktop scenarios. By splitting transaction data, the amount of data transmitted is reduced, the differences between static data are analyzed and compared, and the difference data is transmitted to avoid repeated transmission, reduce the number of interactions, and improve the performance of the off-counter clearing device. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the 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.

[0046] Figure 1 This is a flowchart illustrating a data processing method for an external cleaning device according to an embodiment of the present invention;

[0047] Figure 2This is a flowchart of the transaction processing in an embodiment of the present invention;

[0048] Figure 3 This is a flowchart illustrating the transaction data splitting process in an embodiment of the present invention;

[0049] Figure 4 This is a flowchart illustrating the generation of difference comparison results in an embodiment of the present invention;

[0050] Figure 5 This is a flowchart illustrating data reconstruction in an embodiment of the present invention;

[0051] Figure 6 This is a schematic diagram of the system structure of the data processing method for the external cleaning device in an embodiment of the present invention;

[0052] Figure 7 This is a schematic diagram of the existing system structure in an embodiment of the present invention;

[0053] Figure 8 This is a system workflow diagram in an embodiment of the present invention;

[0054] Figure 9 This is a schematic diagram of the structure of a data processing device for an external cleaning equipment according to an embodiment of the present invention;

[0055] Figure 10 This is a schematic diagram of the data processing device of the external cleaning equipment in another embodiment of the present invention;

[0056] Figure 11 This is a schematic diagram of the data splitting module in an embodiment of the present invention;

[0057] Figure 12 This is a schematic diagram of the difference comparison module in an embodiment of the present invention;

[0058] Figure 13 This is a schematic diagram of the data reconstruction module in an embodiment of the present invention;

[0059] Figure 14 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0060] This invention provides a data processing method and apparatus for off-counter clearing equipment, which can be used in the financial field and other fields. It should be noted that the data processing method and apparatus for off-counter clearing equipment of this invention can be used in the financial field, or in any field other than the financial field. The application field of the data processing method and apparatus for off-counter clearing equipment of this invention is not limited.

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0062] like Figure 1 The diagram shows a flowchart of a data processing method for an off-counter clearing device according to an embodiment of the present invention. The execution subject of the data processing method for the off-counter clearing device provided in this embodiment includes, but is not limited to, a computer. This invention solves the problem of lag in the use of the password keyboard evaluator (off-counter clearing) in high-latency cloud desktop scenarios. By splitting transaction data, the amount of data transmitted is reduced; differences in static data are analyzed and compared; and the differential data is transmitted, avoiding repeated transmission, reducing the number of interactions, and improving the performance of the off-counter clearing device. Figure 1 The methods shown include:

[0063] Step S1: According to the preset splitting rules, the acquired transaction data is split to obtain the dynamic data and static data corresponding to the transaction data.

[0064] The system separates transaction data into dynamic and static data according to preset splitting rules. Dynamic data changes with each transaction and needs to be transmitted every time, while static data changes less and can be transmitted on demand to reduce the amount of data transmitted. In addition, by comparing the static data already stored on the off-site clearing device with the static data of the transaction, only the differences are transmitted, thus realizing incremental data transmission for each transaction.

[0065] Step S2: Perform feature value calculation on the static data to obtain the feature values ​​corresponding to the static data, and perform difference comparison processing on the feature values ​​corresponding to the static data to generate difference comparison results.

[0066] Specifically, the static data feature value of this transmission is calculated, and the static data feature value of the previous transmission is obtained from the external clearing device. The static data feature value of this transmission is compared with the static data feature value of the previous transmission to obtain the comparison result.

[0067] Furthermore, the difference comparison results include identifying which specific static data points differ, i.e., which static data points have changed. This determines the static data points with discrepancies in this data transmission.

[0068] Step S3: Based on the difference comparison results, the dynamic data and static data are recombined to generate recombined transaction data, and the recombined transaction data is sent to the off-counter clearing equipment for transaction processing.

[0069] In this process, based on the difference comparison results, the parts of the static data that show discrepancies are recombined into transaction data. Specifically, the dynamic data obtained from the splitting in step S1 and the static data that show discrepancies are recombined to obtain the recombined transaction data, which is then sent to the off-exchange clearing equipment for transaction processing.

[0070] In this embodiment, the keypad evaluation device (off-counter clearing) refers to the keypad evaluation device used by customers to evaluate and provide feedback on services provided at the bank counter. Currently, common keypad evaluation devices include a touch-screen LCD display, a storage unit, and a keypad; they are also known as dual-screen or off-counter clearing devices.

[0071] Furthermore, dynamic data refers to the data in the transaction data involved in the keypad evaluator that changes with each transaction, such as transaction information including transaction number, transaction code, customer information, transaction account, transaction amount, etc. Static data refers to the relatively fixed data in the transaction data involved in the keypad evaluator, such as screen display templates, advertising images, etc.

[0072] Furthermore, the transaction data is obtained through the transaction backend server, and the specific data can be directly entered by the user.

[0073] As one embodiment of the present invention, such as Figure 2 As shown, the method also includes:

[0074] Step S21: Obtain transaction feedback data sent by the off-counter clearing device;

[0075] Step S22: Transmit the transaction feedback data to the transaction processing backend server to complete the transaction processing.

[0076] The off-counter clearing equipment receives the reorganized transaction data, processes the transaction, and generates transaction feedback data. It then receives the transaction feedback data from the off-counter clearing equipment and sends it to the transaction processing backend server, thus completing the overall transaction processing process.

[0077] As one embodiment of the present invention, such as Figure 3 As shown, according to the preset splitting rules, the acquired transaction data is split to obtain the corresponding dynamic and static data, including:

[0078] Step S31: Based on the data change time and data storage location in the preset splitting rules, identify the dynamic and static data in the transaction data to obtain the data identification result;

[0079] Step S32: Based on the data recognition results, the transaction data is split to obtain the dynamic data and static data corresponding to the transaction data.

[0080] The preset splitting rules include data change time and data storage location. For example, if the data change time is 72 hours, meaning the data hasn't changed in 72 hours, it can be considered static data; otherwise, it's dynamic data. Furthermore, data storage location includes memory and hard drive; data stored in memory can be considered dynamic data, while data stored on the hard drive can be considered static data.

[0081] Furthermore, the splitting rules can also include data types, specifically the data types corresponding to dynamic data and the data types corresponding to static data. Thus, the splitting rules are used to identify static and dynamic data in transaction data, yielding data identification results—that is, which transaction data is dynamic and which is static. Alternatively, conventional data splitting methods can be used to split the transaction data, obtaining the corresponding dynamic and static data.

[0082] As an embodiment of the present invention, the feature value calculation process for static data to obtain the feature value corresponding to the static data includes: calculating the average value of the static data to obtain the average value corresponding to the static data, and using the average value as the feature value corresponding to the static data.

[0083] The eigenvalues ​​can be numerical values ​​such as mean and variance. The mean or variance of the static data is calculated, and the result is used as the eigenvalue of the static data.

[0084] Furthermore, if the static data is images or other similar data, the images can be processed such as grayscale or binarization to obtain the feature values ​​corresponding to the image data. The image processing uses conventional techniques, which will not be elaborated here.

[0085] In this embodiment, as Figure 4 As shown, the feature values ​​corresponding to the static data are subjected to difference comparison processing, and the difference comparison results are generated as follows:

[0086] Step S41: Obtain the feature value corresponding to the previously transmitted static data from the external clearing device;

[0087] Step S42: Compare the feature values ​​corresponding to the static data with the feature values ​​corresponding to the previously transmitted static data to generate a difference comparison result.

[0088] Specifically, the static data feature value of this transmission is calculated, and the static data feature value of the previous transmission is obtained from the external data processing. The static data feature value of this transmission is compared with the static data feature value of the previous transmission to obtain the comparison result.

[0089] Furthermore, the difference comparison results include identifying which specific static data points differ, i.e., which static data points have changed. This determines the static data points with discrepancies in this data transmission.

[0090] Specifically, if the characteristic value is the average value of static data, it can be determined whether the static data has changed by checking if the average value has changed. This avoids comparing each piece of static data individually, improving processing efficiency. If the characteristic value of the static data, such as the average value, has not changed, subsequent data reorganization is unnecessary, and transaction processing can proceed directly. If the characteristic value of the static data has changed, it indicates the existence of changed static data, and a comparison of each piece of static data is then performed. The result of the difference comparison indicates whether the static data has changed.

[0091] As one embodiment of the present invention, such as Figure 5 As shown, based on the difference comparison results, dynamic and static data are recombined to generate recombined transaction data, including:

[0092] Step S51: Based on the difference comparison results, determine the differential static data in the static data;

[0093] Step S52: Reorganize the dynamic data and the differential static data to generate reorganized transaction data.

[0094] Based on the difference comparison results, it can be determined whether the static data has changed. If it has changed, the static data is compared one by one to identify the static data that has changed.

[0095] Furthermore, the discrepancies in the static data are recombined into transaction data. Specifically, the dynamic data obtained from the splitting and the discrepancies in the static data are reassembled to obtain the recombined transaction data.

[0096] In this embodiment, determining the differential static data in the static data based on the difference comparison results includes: comparing the difference comparison results with a preset difference threshold, determining the data in the static data whose difference comparison results exceed the difference threshold, and taking the data in the static data whose difference comparison results exceed the difference threshold as differential static data.

[0097] The preset difference threshold can be zero or any other value. Specifically, when comparing static data one by one, if the change in the value of the static data exceeds the difference threshold, the static data is considered to have changed and is treated as the static data with difference.

[0098] In this embodiment, the off-exchange clearing device undergoes transaction data initialization processing. Specifically, the off-exchange clearing device is initialized before transaction data processing, thus caching the initialization transaction data in the device's storage unit. If a different off-exchange clearing device is used, the off-exchange clearing device needs to be re-initialized.

[0099] In a specific embodiment of the present invention, such as Figure 6 The diagram shows a system structure diagram of the data processing method for the application cabinet clearing equipment. The data processing system shown in the diagram includes: performance enhancement device 201 (data splitting module 202, data analysis and processing module 203), data transmission module 204, and transaction processing module 205.

[0100] Performance enhancement device 201 includes a data splitting module 202 and a data analysis and processing module 203, which mainly splits the dynamic and static data of transaction data. Since dynamic data changes with each transaction, it needs to be transmitted every time, but static data changes less and can be transmitted on demand to reduce the amount of data transmitted; in addition, by comparing the static data already existing on the storage unit of the off-exchange clearing equipment with the static data of the transaction, only the differences are transmitted, realizing incremental data transmission for each transaction.

[0101] Data splitting module 202: Responsible for splitting data from the trading system backend into dynamic and static data according to certain rules.

[0102] Data Analysis and Processing Module 203: Responsible for processing dynamic and static data from the data splitting module, calculating the feature values ​​of static data, analyzing them with the feature values ​​of static data in the off-exchange clearing, and recombining the differences into transaction data.

[0103] Data transmission module 204: encrypts and decrypts data from the data analysis and processing module and interacts with the external cleaning equipment.

[0104] Transaction processing module 205: Receives transaction data feedback from off-counter clearing equipment, processes it, and sends it back to the transaction processing system backend.

[0105] In this embodiment, as Figure 8 The workflow diagram shown includes:

[0106] Step 301: Transaction data splitting. The transaction processing system backend 206 transmits the transaction data to the data splitting module 202. The data splitting module 202 splits the transaction data into dynamic and static data according to the pre-set rules, and then transmits it to the data analysis and processing module 203.

[0107] Step 302: Static data feature value calculation. After receiving the static data transmitted by the data splitting module 202, the data analysis and processing module 203 performs the calculation through the feature value calculation unit.

[0108] Step 303, Static data feature value analysis: The data analysis and processing module 203 compares the static data feature values ​​generated in step 302 with the feature values ​​of the static data previously transmitted to the external cleaning equipment through the feature value analysis unit of this module, generates a difference instruction, and provides it to the data reassembly unit within this module.

[0109] Step 304, data recombination: The data analysis and processing module 203 recombines the dynamic data and the static data of differences generated in step 301 according to the difference instructions generated in step 303, and then transmits them to the data transmission module 204.

[0110] Step 305, data transmission: The data reconstructed in step 304 is transmitted to the external clearing device, namely the password keypad evaluator 207, through the data transmission module 204.

[0111] Step 306: Transaction processing is complete. After the transaction is processed and feedback is received by the password keyboard evaluator 207, it is converted by the transaction processing module 205 and sent back to the transaction processing system backend 206.

[0112] The above process indicates that the off-counter clearing device has completed its initialization, and the initialization transaction data has been cached in the device's storage unit. If a different off-counter clearing device is used, the off-counter clearing process must be re-initialized.

[0113] In this embodiment, the present invention provides a method and system for improving the performance of off-site clearance equipment by splitting business data and using an incremental delivery mode. To highlight the features of the present invention and make its description more easily understood, the following description compares the technical solutions of the present invention with those of existing technologies, such as... Figure 7 The diagram shown illustrates the existing system architecture, illustrating the specific technologies, structural framework, and processing flow. Figure 7 The system shown includes: a transaction processing system backend 101, a data transmission module 102, and a transaction processing module 103.

[0114] Transaction Processing System Backend 101: Responsible for a series of backend processing of related transactions, including storing customer information, transaction information, business data, etc.

[0115] Data transmission module 102: encrypts and decrypts data from the transaction processing system backend and interacts with off-exchange clearing equipment.

[0116] Transaction processing module 103: Receives transaction data from off-counter clearing equipment, processes it, and then sends it back to the transaction processing system backend.

[0117] Clearly, existing solutions transmit the entire transaction data directly from the backend to the off-site clearing device via the transaction processing system client for each transaction. The off-site clearing device's storage unit caches the transaction data and displays it to the client. This invention solves the problem of lag in the password keyboard evaluator (off-site clearing) under high latency scenarios on cloud desktops. By splitting transaction data, the amount of data transmitted is reduced. Differences in static data are analyzed and compared. The caching mechanism of the off-site clearing device's storage unit is used to transmit the difference data, avoiding repeated transmissions and reducing the number of interactions. This improves the performance of the off-site clearing device without changing the network bandwidth in cloud desktop scenarios.

[0118] like Figure 9 The figure shows a schematic diagram of a data processing device for an external cleaning equipment according to an embodiment of the present invention. The device shown in the figure includes:

[0119] The data splitting module 10 is used to split the acquired transaction data according to the preset splitting rules to obtain the dynamic data and static data corresponding to the transaction data.

[0120] The difference comparison module 20 is used to perform feature value calculation on static data to obtain the feature values ​​corresponding to the static data, and to perform difference comparison on the feature values ​​corresponding to the static data to generate difference comparison results.

[0121] The data recombination module 30 is used to recombine the dynamic data and the static data according to the difference comparison results, generate recombined transaction data, and send the recombined transaction data to the off-counter clearing equipment for transaction processing.

[0122] The system separates transaction data into dynamic and static data according to preset splitting rules. Dynamic data changes with each transaction and needs to be transmitted every time, while static data changes less and can be transmitted on demand to reduce the amount of data transmitted. In addition, by comparing the static data already stored on the off-site clearing device with the static data of the transaction, only the differences are transmitted, thus realizing incremental data transmission for each transaction.

[0123] Furthermore, the static data feature value of this transmission is calculated, and the static data feature value of the previous transmission is obtained from the external clearing device. The static data feature value of this transmission is compared with the static data feature value of the previous transmission to obtain the comparison result.

[0124] Furthermore, the difference comparison results include identifying which specific static data points differ, i.e., which static data points have changed. This determines the static data points with discrepancies in this data transmission.

[0125] Furthermore, based on the difference comparison results, the parts of the static data that show discrepancies are recombined into transaction data. Specifically, the dynamic data obtained from the splitting and the static data that show discrepancies are recombined to obtain the recombined transaction data, which is then sent to the off-exchange clearing equipment for transaction processing.

[0126] As one embodiment of the present invention, such as Figure 10 As shown, the device also includes a feedback data module 40, which is used to acquire transaction feedback data sent by the off-counter clearing equipment and transmit the transaction feedback data to the transaction processing backend server to complete the transaction processing.

[0127] As one embodiment of the present invention, such as Figure 11 As shown, the data splitting module 10 includes:

[0128] The data identification unit 11 is used to identify dynamic and static data in transaction data according to the data change time and data storage location in the preset splitting rules, and obtain data identification results;

[0129] The data splitting unit 12 is used to split the transaction data according to the data identification results to obtain the dynamic data and static data corresponding to the transaction data.

[0130] As an embodiment of the present invention, the difference comparison module 20 is also used to calculate the average value of the static data, obtain the average value corresponding to the static data, and use the average value as the feature value corresponding to the static data.

[0131] As one embodiment of the present invention, such as Figure 12 As shown, the difference comparison module 20 includes:

[0132] Feature value acquisition unit 21 is used to acquire feature values ​​corresponding to the previously transmitted static data that are pre-stored from the external clearing device;

[0133] The difference comparison unit 22 is used to compare the feature value corresponding to the static data with the feature value corresponding to the previously transmitted static data to generate a difference comparison result.

[0134] As one embodiment of the present invention, such as Figure 13 As shown, the data reconstruction module 30 includes:

[0135] The difference data unit 31 is used to determine the difference static data in the static data based on the difference comparison results;

[0136] The data recombination unit 32 is used to recombine dynamic data and differential static data to generate recombined transaction data.

[0137] Optionally, in one embodiment of the present invention, the difference data unit 31 is further configured to compare the difference comparison result with a preset difference threshold, determine the data in the static data whose difference comparison result exceeds the difference threshold, and use the data in the static data whose difference comparison result exceeds the difference threshold as the difference static data.

[0138] This invention solves the problem of lag in the use of the password keyboard evaluator (out-of-counter clearing) in high-latency cloud desktop scenarios. By splitting transaction data, the amount of data transmitted is reduced. The differences between static data are analyzed and compared. The caching mechanism of the storage unit of the out-of-counter clearing device is used to transmit the difference data, avoid repeated transmission, and reduce the number of interactions. Under the condition that the network bandwidth in the cloud desktop scenario remains unchanged, the performance of the out-of-counter clearing device is improved.

[0139] Based on the same application concept as the aforementioned data processing method for an external cabinet cleaning device, this invention also provides a data processing apparatus for the aforementioned external cabinet cleaning device. Since the problem-solving principle of this data processing apparatus for an external cabinet cleaning device is similar to that of the aforementioned data processing method, the implementation of this data processing apparatus for an external cabinet cleaning device can refer to the implementation of the aforementioned data processing method for an external cabinet cleaning device; repeated details will not be elaborated further.

[0140] This invention solves the problem of lag in the use of the password keyboard evaluator (outside the counter) in high-latency cloud desktop scenarios. By splitting transaction data, the amount of data transmitted is reduced. The differences between static data are analyzed and compared. The caching mechanism of the outside counter storage unit is used to transmit the difference data, avoid repeated transmission, and reduce the number of interactions. This improves the performance of the outside counter without changing the network bandwidth in the cloud desktop scenario.

[0141] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method.

[0142] The present invention also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the above-described method.

[0143] The present invention also provides a computer-readable storage medium storing a computer program for performing the above-described method.

[0144] like Figure 14 As shown, the electronic device 600 may also include: a communication module 110, an input unit 120, an audio processor 130, a display 160, and a power supply 170. It is worth noting that the electronic device 600 does not necessarily need to include these components. Figure 14 All components shown; in addition, the electronic device 600 may also include Figure 14 For components not shown, please refer to existing technologies.

[0145] like Figure 14 As shown, the central processing unit 100, sometimes also referred to as a controller or operating control, may include a microprocessor or other processor device and / or logic device. The central processing unit 100 receives inputs and controls the operation of various components of the electronic device 600.

[0146] The memory 140 may be, for example, one or more of a cache, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices. It may store the aforementioned failure-related information, and also store a program for executing that information. The central processing unit 100 may execute the program stored in the memory 140 to perform information storage or processing, etc.

[0147] Input unit 120 provides input to central processing unit 100. Input unit 120 may be, for example, a keypad or touch input device. Power supply 170 provides power to electronic device 600. Display 160 displays images and text. Display may be, for example, an LCD display, but is not limited thereto.

[0148] The memory 140 can be a solid-state memory, such as a read-only memory (ROM), random access memory (RAM), a SIM card, etc. It can also be a memory that retains information even when power is off, can be selectively erased, and contains more data; examples of this type of memory are sometimes referred to as EPROMs. The memory 140 can also be some other type of device. The memory 140 includes a buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application / function storage unit 142 for storing application programs and function programs or processes for executing the operation of the electronic device 600 via the central processing unit 100.

[0149] The memory 140 may also include a data storage unit 143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 144 of the memory 140 may include various drivers for the electronic device's communication functions and / or for performing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0150] The communication module 110 is a transmitter / receiver 110 that transmits and receives signals via antenna 111. The communication module (transmitter / receiver) 110 is coupled to the central processing unit 100 to provide input signals and receive output signals, which can be the same as in a conventional mobile communication terminal.

[0151] Based on different communication technologies, multiple communication modules 110 can be configured in the same electronic device, such as cellular network modules, Bluetooth modules, and / or wireless LAN modules. The communication module (transmitter / receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide audio output via the speaker 131 and receive audio input from the microphone 132, thereby enabling typical telecommunications functions. The audio processor 130 may include any suitable buffer, decoder, amplifier, etc. Additionally, the audio processor 130 is coupled to a central processing unit 100, enabling on-device recording via the microphone 132 and on-device playback of stored audio via the speaker 131.

[0152] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0153] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0154] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0155] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0156] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A data processing method of an off-premise cleaning device, characterized by, The method includes: According to the data change time and data storage location in the preset splitting rules, the acquired transaction data is split to obtain the dynamic data and static data corresponding to the transaction data. The dynamic data is the data that changes with each transaction in the transaction data involved in the password keyboard evaluator, and the static data is the fixed data in the transaction data involved in the password keyboard evaluator. The static data is processed by feature value calculation to obtain the feature value corresponding to the static data, and the feature value corresponding to the static data is processed by difference comparison to generate difference comparison results. The step of performing feature value calculation on the static data to obtain the feature value corresponding to the static data includes: calculating the average value of the static data to obtain the average value corresponding to the static data, and using the average value as the feature value corresponding to the static data. Based on the difference comparison results, the dynamic data and the static data are recombined to generate recombined transaction data, which is then sent to the off-counter clearing equipment for transaction processing.

2. The method according to claim 1, characterized in that, The method further includes: Obtain the transaction feedback data sent by the off-counter clearing device; The transaction feedback data is transmitted to the transaction processing backend server to complete the transaction processing.

3. The method according to claim 1, characterized in that, The step of splitting the acquired transaction data according to a preset splitting rule to obtain the dynamic data and static data corresponding to the transaction data includes: Based on the data change time and data storage location in the preset splitting rules, the dynamic data and static data in the transaction data are identified to obtain the data identification results; Based on the data identification results, the transaction data is split to obtain the dynamic data and static data corresponding to the transaction data.

4. The method of claim 1, wherein, The step of performing difference comparison processing on the feature values ​​corresponding to the static data to generate difference comparison results includes: Obtain the feature value corresponding to the previously transmitted static data that was previously stored in the external clearing device; The feature values ​​corresponding to the static data are compared with the feature values ​​corresponding to the previously transmitted static data to generate a difference comparison result.

5. The method of claim 1, wherein, The step of recombining the dynamic data and the static data based on the difference comparison results to generate recombined transaction data includes: Based on the difference comparison results, determine the differential static data in the static data; The dynamic data and the differing static data are recombined to generate recombined transaction data.

6. The method of claim 5, wherein, The step of determining the differential static data in the static data based on the difference comparison results includes: The difference comparison results are compared with a preset difference threshold to determine the data in the static data whose difference comparison results exceed the difference threshold, and the data in the static data whose difference comparison results exceed the difference threshold are taken as the difference static data.

7. A data processing device of an off-premise cleaning apparatus, characterized in that, The device includes: The data splitting module is used to split the acquired transaction data according to the data change time and data storage location in the preset splitting rules to obtain the dynamic data and static data corresponding to the transaction data. The dynamic data is the data that changes with each transaction in the transaction data involved in the password keyboard evaluator, and the static data is the fixed data in the transaction data involved in the password keyboard evaluator. The difference comparison module is used to perform feature value calculation processing on the static data to obtain the feature value corresponding to the static data, and to perform difference comparison processing on the feature value corresponding to the static data to generate difference comparison results. The difference comparison module is also used to calculate the average value of static data, obtain the average value corresponding to the static data, and use the average value as the feature value corresponding to the static data. The data recombination module is used to recombine the dynamic data and the static data according to the difference comparison results, generate recombined transaction data, and send the recombined transaction data to the off-counter clearing equipment for transaction processing.

8. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that performs the method according to any one of claims 1 to 6.

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