Efficient processing system based on big data information

Abstract

The invention discloses an efficient information processing system based on big data, which relates to the technical field of efficient information processing, and comprises a behavior habit analysis module for analyzing the operation complexity and time complexity of the same type of touch events of the same application, calculating the comprehensive complexity of the same type of touch events of the same application, and calculating the comprehensive complexity of the same type of touch events of the same application; determining the touch habit complexity of the user under the specific application; the application information processing and dividing module is used for dividing touch information processing requirements of different applications and taking corresponding touch information processing measures; the mistaken touch analysis module is used for calculating the real-time application touch complexity of the application in the application use process and sending a mistaken touch analysis instruction to the outside; and the mistaken touch early warning module is used for calculating an operation complexity change coefficient of a real-time touch event after receiving the mistaken touch analysis instruction, sending mistaken touch early warning outwards and stopping touch information processing. A more personalized interface design and interaction mode can be provided for a specific user group or individual, and a touch response mechanism of an application is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of efficient information processing, and in particular to an efficient information processing system based on big data. Background Art

[0002] With the rapid development of digitalization and information technology, touch screen technology has been widely used in various industries, such as smart phones, tablet computers, self-service terminals, etc. These devices receive user input commands through the touch screen to achieve human-computer interaction. However, with the increase in the number of users and the increase in the frequency of touch operations, the amount of touch information processing has also increased dramatically, which has put forward higher requirements for the touch information processing system. As an important interface for human-computer interaction, touch screen technology has undergone an evolution from resistive, capacitive to infrared and other technical types. Among them, capacitive touch screens have become the mainstream of the current market due to their high sensitivity, good durability, and easy multi-touch. However, with the continuous advancement of touch screen technology, higher requirements have been put forward for the processing speed and accuracy of touch information.

[0003] In the Chinese invention application with application publication number CN116107483A, a touch event processing method, device, electronic device and storage medium are disclosed, including that when a client monitors a touch event, the client collects touch data corresponding to the touch event, inputs the touch data corresponding to the touch event into a false touch recognition model deployed in the client, and obtains a recognition result; when the recognition result indicates that the touch event is a false touch event, the touch data is marked with a false touch label, and a first training sample is obtained to update the model parameters of the false touch recognition model deployed on the client, so that the false touch recognition model after the model parameters are updated is used as the false touch recognition model for false touch recognition when the touch event is monitored next time. Through the method of this embodiment, it is possible to accurately determine whether a false touch occurs according to the diversity of user usage habits, thereby improving the accuracy of false touch recognition.

[0004] In the above invention application, the touch data corresponding to the touch event is input into the false touch recognition model deployed in the client to obtain the recognition result and determine whether a false touch occurs. However, in actual use, due to the different touch information processing requirements of different applications, for example, for game applications, faster touch response speed and higher accuracy may be required; while for reading applications, more attention may be paid to the smoothness and stability of touch. If the same false touch standard is used, it will lead to the inability to effectively identify the false touch operation of applications with low touch information processing requirements, resulting in problems such as freeze and crash of the application. For game applications with high touch information processing requirements, misjudgment will occur, affecting the user experience.

[0005] To this end, the present invention provides an efficient processing system based on big data information. Summary of the invention

[0006] 1. Technical issues to be resolved In view of the shortcomings of the prior art, the present invention provides an efficient processing system based on big data information. The present invention records user touch events, analyzes the operation complexity Cz and time complexity Sz of the same type of touch events in the same application, calculates the comprehensive complexity Zf of the same type of touch events in the same application, and determines the complexity of the user's touch habits in a specific application. , divide the touch information processing requirements of different applications, and take corresponding touch information processing measures. During the use of the application, calculate the real-time application touch complexity Ycf of the application. If the real-time application touch complexity Ycf exceeds the touch habit complexity corresponding to the application , then send out a false touch analysis instruction, calculate the operation complexity change coefficient Bh of the real-time touch event, send out a false touch warning, stop touch information processing, and provide a more personalized interface design and interaction method for specific user groups or individuals, optimize the touch response mechanism of the application, and be able to quickly identify and send out a false touch analysis instruction, which helps to correct the user's erroneous operation in time, avoid operational errors or interface confusion caused by false touches, and take corresponding preventive measures, such as reducing resource consumption, optimizing code, etc., to improve the stability of the application, thereby solving the technical problems recorded in the background technology.

[0007] (II) Technical solution To achieve the above objectives, the present invention is implemented through the following technical solutions: A system for efficient processing of big data information, comprising: The behavior habit analysis module records user touch events, analyzes the operation complexity Cz and time complexity Sz of the same type of touch events in the same application, calculates the comprehensive complexity Zf of the same type of touch events in the same application, and determines the complexity of the user's touch habits in a specific application. ; Application information processing division module to obtain the complexity of users' touch habits in specific applications , divide the touch information processing requirements of different applications and take corresponding touch information processing measures; The false touch analysis module calculates the real-time application touch complexity Ycf of the application during the use of the application. If the real-time application touch complexity Ycf exceeds the touch habit complexity corresponding to the application, , then send out an error touch analysis instruction; The false touch warning module obtains the touch position of the real-time touch event after receiving the false touch analysis instruction and touch strength , calculate the operation complexity change coefficient Bh of the real-time touch event, send out a false touch warning, and stop touch information processing.

[0008] Furthermore, the built-in sensors and drivers of the touch screen device are used to capture the touch events of users when using different applications. For each touch event, its related attributes are recorded, such as the type of touch event (click, slide, long press, etc.), touch duration, frequency, touch position (X and Y coordinates) and touch strength.

[0009] Furthermore, the touch position of the same type of touch event of the same application is obtained. and touch strength , calculate the operation complexity Cz of the same type of touch event of the same application:

[0010] in, i Indicates the time sequence number of the same type of touch events in the same application. , n The total number of touch events of the same type that occurred for the same application.

[0011] Furthermore, get the duration of the same type of touch event in the same application and frequency , calculate the time complexity Sz of the same type of touch event for the same application:

[0012] The calculation formula of the time complexity Sz of the same type of touch event of the same application is as above.

[0013] Furthermore, the operation complexity Cz and time complexity Sz of the same type of touch event of the same application are obtained, and the comprehensive complexity Zf of the same type of touch event of the same application is calculated:

[0014] Among them, e is a natural constant.

[0015] Furthermore, the comprehensive complexity of different types of touch events in different applications is obtained. , calculate the complexity of the user's touch habits in a specific application :

[0016] in, j Indicates the order of different types of touch events in the same application. Single click is numbered 1, double click is numbered 2, long press is numbered 3, and sliding is numbered 4. .

[0017] Furthermore, the complexity of the user's touch habits in a specific application is obtained , the touch information processing requirements of different applications are divided into: when When the touch habit of the current application is not complex, the user will be fed back that the touch habit is not complex, and the normal touch accuracy and response speed will be used to continue monitoring to prevent abnormal situations. when When the touch habit complexity of the current application is medium, the touch accuracy or response speed is improved when using the application; when When the touch habits of the current application are complex, the user is prompted to improve touch accuracy and response speed when using the application. in, Touch custom complexity for all apps The mean of .

[0018] Furthermore, during the use of the application, the built-in sensors and drivers of the touch screen device are used to capture the real-time touch events of the user when using the application, analyze the operation complexity and time complexity of the same type of real-time touch events, calculate the comprehensive complexity of the same type of real-time touch events, and calculate the real-time application touch complexity Ycf of the application.

[0019] The calculation method of real-time application touch complexity Ycf and the complexity of user touch habits in specific applications The calculation method is the same.

[0020] Further, after receiving the false touch analysis instruction, the touch position of the real-time touch event is obtained and touch strength , calculate the operation complexity change coefficient Bh of real-time touch events:

[0021] in, Indicates the touch position of a real-time touch event The touch position of the previous sequential touch event, Indicates real-time touch strength The touch intensity of the previous sequential touch event.

[0022] If the operation complexity variation coefficient Bh If it is less than 0.1, it means that there is false touch information in the current touch information, and a false touch warning is sent out to stop the touch information processing.

[0023] (III) Beneficial effects The present invention provides a system for efficiently processing big data information, which has the following beneficial effects: 1. Obtain the operation complexity Cz and time complexity Sz of the same type of touch event in the same application, and calculate the comprehensive complexity Zf of the same type of touch event in the same application. This can accurately identify the user's behavioral habits of the same type of touch event in the same application. Based on this information, the application's interactive design can be optimized to improve the application's response speed and make the operation smoother, more intuitive, and easier to understand.

[0024] 2. By recording user touch events, analyzing the operation complexity Cz and time complexity Sz of the same type of touch events in the same application, calculating the comprehensive complexity Zf of the same type of touch events in the same application, and determining the complexity of the user's touch habits in a specific application , which provides a comprehensive evaluation index for user touch behavior, can more accurately grasp the user's operating habits in specific applications, provide a basis for subsequent optimization, provide more personalized services and experience, and improve the efficiency of touch information processing.

[0025] 3. Obtain the complexity of the user's touch habits in a specific application , dividing the touch information processing requirements of different applications and taking corresponding touch information processing measures can provide more personalized interface design and interaction methods for specific user groups or individuals, and optimize the touch response mechanism of the application, which is of great significance for improving user experience, improving application performance, enhancing user stickiness and promoting technological innovation.

[0026] 4. During the use of the application, calculate the real-time application touch complexity Ycf of the application. If the real-time application touch complexity Ycf exceeds the touch habit complexity corresponding to the application , an accidental touch analysis instruction is issued. The system can quickly identify and issue an accidental touch analysis instruction, which helps to correct the user's incorrect operation in time, avoid operational errors or interface confusion caused by accidental touch, and take corresponding preventive measures, such as reducing resource consumption, optimizing code, etc., to improve the stability of the application.

[0027] 5. After receiving the false touch analysis instruction, obtain the touch position of the real-time touch event and touch strength , calculate the operation complexity change coefficient Bh of the real-time touch event, send out a false touch warning, and stop the touch information processing, which can remind the user to pay attention to the current operation status and avoid operation errors or interface confusion caused by false touches. Stopping the touch information processing can prevent the false touch operation from being further processed by the system, thereby reducing unnecessary interference and trouble, and helping to maintain the stability of the application. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a structural schematic diagram of an efficient processing system based on big data information according to the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] See also Figure 1 The present invention provides a system for efficiently processing big data information, comprising: The behavior habit analysis module records user touch events, analyzes the operation complexity Cz and time complexity Sz of the same type of touch events in the same application, calculates the comprehensive complexity Zf of the same type of touch events in the same application, and determines the complexity of the user's touch habits in a specific application. .

[0031] Use the built-in sensors and drivers of the touch screen device to capture the touch events of users when using different applications. For each touch event, record its related attributes, such as the type of touch event (click, slide, long press, etc.), touch duration, frequency, touch position (X and Y coordinates), and touch strength.

[0032] Get the touch position of the same type of touch event in the same application and touch strength , calculate the operation complexity Cz of the same type of touch event of the same application:

[0033] in, i Indicates the time sequence number of the same type of touch events in the same application. , n The total number of touch events of the same type that occurred for the same application.

[0034] Get the duration of the same type of touch event for the same application and frequency , calculate the time complexity Sz of the same type of touch event for the same application:

[0035] The calculation formula of the time complexity Sz of the same type of touch event of the same application is as above.

[0036] Get the operation complexity Cz and time complexity Sz of the same type of touch event in the same application, and calculate the comprehensive complexity Zf of the same type of touch event in the same application:

[0037] Among them, e is a natural constant.

[0038] By obtaining the operation complexity Cz and time complexity Sz of the same type of touch event in the same application and calculating the comprehensive complexity Zf of the same type of touch event in the same application, we can accurately identify the user's behavioral habits in the same type of touch event in the same application. Based on this information, we can optimize the interaction design of the application, improve the response speed of the application, and make the operation smoother, more intuitive and easier to understand.

[0039] Get the comprehensive complexity of different types of touch events for different applications , calculate the complexity of the user's touch habits in a specific application :

[0040] in, j Indicates the order of different types of touch events in the same application. Single click is numbered 1, double click is numbered 2, long press is numbered 3, and sliding is numbered 4. .

[0041] By recording user touch events, analyzing the operation complexity Cz and time complexity Sz of the same type of touch events in the same application, calculating the comprehensive complexity Zf of the same type of touch events in the same application, and determining the complexity of the user's touch habits in a specific application , which provides a comprehensive evaluation index for user touch behavior, can more accurately grasp the user's operating habits in specific applications, provide a basis for subsequent optimization, provide more personalized services and experience, and improve the efficiency of touch information processing.

[0042] Application information processing division module to obtain the complexity of users' touch habits in specific applications , divide the touch information processing requirements of different applications, and take corresponding touch information processing measures.

[0043] Get the complexity of the user's touch habits in a specific application , the touch information processing requirements of different applications are divided into: when When the user touches the touch screen, the user can see that the touch habits of the current application are of low complexity, and the normal touch accuracy and response speed are used to continue monitoring to prevent abnormal situations.

[0044] when When the touch habits of the current application are of medium complexity, the user is prompted to improve the touch accuracy or response speed when using the application.

[0045] when When the touch habits of the current application are complex, feedback is given, and the touch accuracy and response speed are improved when using the application.

[0046] in, Touch custom complexity for all apps The mean of .

[0047] Get the complexity of the user's touch habits in a specific application , dividing the touch information processing requirements of different applications and taking corresponding touch information processing measures can provide more personalized interface design and interaction methods for specific user groups or individuals, and optimize the touch response mechanism of the application, which is of great significance for improving user experience, improving application performance, enhancing user stickiness and promoting technological innovation.

[0048] The false touch analysis module calculates the real-time application touch complexity Ycf of the application during the use of the application. If the real-time application touch complexity Ycf exceeds the touch habit complexity corresponding to the application, , then an error touch analysis instruction is issued.

[0049] During the use of the application, the built-in sensors and drivers of the touch screen device are used to capture the real-time touch events of the user when using the application, analyze the operation complexity and time complexity of the same type of real-time touch events, calculate the comprehensive complexity of the same type of real-time touch events, and calculate the real-time application touch complexity Ycf of the application.

[0050] Among them, the calculation method of real-time application touch complexity Ycf is different from the complexity of user touch habits in specific applications. The calculation method is the same.

[0051] If the touch complexity Ycf of the real-time application exceeds the touch habit complexity corresponding to the application , then an error touch analysis instruction is issued.

[0052] During the application use, the real-time application touch complexity Ycf of the application is calculated. If the real-time application touch complexity Ycf exceeds the touch habit complexity corresponding to the application , an accidental touch analysis instruction is issued. The system can quickly identify and issue an accidental touch analysis instruction, which helps to correct the user's incorrect operation in time, avoid operational errors or interface confusion caused by accidental touch, and take corresponding preventive measures, such as reducing resource consumption, optimizing code, etc., to improve the stability of the application.

[0053] The false touch warning module obtains the touch position of the real-time touch event after receiving the false touch analysis instruction and touch strength , calculate the operation complexity change coefficient Bh of the real-time touch event, send out a false touch warning, and stop touch information processing.

[0054] After receiving the false touch analysis instruction, obtain the touch position of the real-time touch event and touch strength , calculate the operation complexity change coefficient Bh of real-time touch events:

[0055] in, Indicates the touch position of a real-time touch event The touch position of the previous sequential touch event, Indicates real-time touch strength The touch intensity of the previous sequential touch event.

[0056] If the operation complexity variation coefficient Bh If it is less than 0.1, it means that there is false touch information in the current touch information, and a false touch warning is sent out to stop the touch information processing.

[0057] After receiving the false touch analysis instruction, obtain the touch position of the real-time touch event and touch strength , calculate the operation complexity change coefficient Bh of the real-time touch event, send out a false touch warning, and stop the touch information processing, which can remind the user to pay attention to the current operation status and avoid operation errors or interface confusion caused by false touches. Stopping the touch information processing can prevent the false touch operation from being further processed by the system, thereby reducing unnecessary interference and trouble, and helping to maintain the stability of the application.

[0058] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0059] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0060] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An efficient processing system based on big data information, characterized by: include: The behavior habit analysis module records user touch events, analyzes the operation complexity Cz and time complexity Sz of the same type of touch events in the same application, calculates the comprehensive complexity Zf of the same type of touch events in the same application, and determines the complexity of the user's touch habits in a specific application. ; Application information processing division module to obtain the complexity of users' touch habits in specific applications , divide the touch information processing requirements of different applications and take corresponding touch information processing measures; The false touch analysis module calculates the real-time application touch complexity Ycf of the application during the use of the application. If the real-time application touch complexity Ycf exceeds the touch habit complexity corresponding to the application, , then send out an error touch analysis instruction; The false touch warning module obtains the touch position of the real-time touch event after receiving the false touch analysis instruction and touch strength , calculate the operation complexity change coefficient Bh of the real-time touch event, send out a false touch warning, and stop touch information processing.

2. The system for efficient processing of big data information according to claim 1, characterized in that: Get the touch position of the same type of touch event in the same application and touch strength , calculate the operation complexity Cz of the same type of touch event of the same application: in, i Indicates the time sequence number of the same type of touch events in the same application. , n The total number of touch events of the same type that occurred for the same application.

3. The system for efficient processing of big data information according to claim 1, characterized in that: Get the duration of the same type of touch event for the same application and frequency , calculate the time complexity Sz of the same type of touch event for the same application: The calculation formula of the time complexity Sz of the same type of touch event of the same application is as above.

4. The system for efficient processing of big data information according to claim 3 is characterized in that: Get the operation complexity Cz and time complexity Sz of the same type of touch event in the same application, and calculate the comprehensive complexity Zf of the same type of touch event in the same application: Among them, e is a natural constant.

5. The system for efficient processing of big data information according to claim 4 is characterized in that: Get the comprehensive complexity of different types of touch events for different applications , calculate the complexity of the user's touch habits in a specific application : in, j Indicates the order of different types of touch events in the same application. Single click is numbered 1, double click is numbered 2, long press is numbered 3, and sliding is numbered 4. .

6. The system for efficient processing of big data information according to claim 5, characterized in that: Get the complexity of the user's touch habits in a specific application , the touch information processing requirements of different applications are divided into: when When the touch habit of the current application is fed back, the complexity is low and the normal touch accuracy and response speed are adopted; when When the touch habit complexity of the current application is medium, the touch accuracy or response speed is improved when using the application; when When the touch habits of the current application are complex, the user is prompted to improve touch accuracy and response speed when using the application. in, Touch custom complexity for all apps The mean of .

7. The system for efficient processing of big data information according to claim 1, characterized in that: The calculation method of real-time application touch complexity Ycf and the complexity of user touch habits in specific applications The calculation method is the same.

8. The system for efficient processing of big data information according to claim 1, characterized in that: After receiving the false touch analysis instruction, obtain the touch position of the real-time touch event and touch strength , calculate the operation complexity change coefficient Bh of real-time touch events: in, Indicates the touch position of a real-time touch event The touch position of the previous sequential touch event, Indicates real-time touch strength The touch intensity of the previous sequential touch event.

9. The system for efficient processing of big data information according to claim 8, characterized in that: If the operation complexity variation coefficient Bh If it is less than 0.1, it means that there is false touch information in the current touch information, and a false touch warning is sent out to stop the touch information processing.

Images