Password reminding method, device and equipment

[0047] In order to enable those skilled in the art to better understand the technical solutions in this specification, the following will clearly and completely describe the technical solutions in the embodiments of this specification in conjunction with the drawings in the embodiments of this specification. Obviously, the described The embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without creative work should fall within the protection scope of this application.

[0048] In the prior art, platforms or websites that use password verification generally have a "recover password" or "change password" or "reset password" design, so that when the user forgets the password, a new password can be obtained. However, this design belongs to the user-initiated behavior of passively obtaining a new password. Since most users do not realize that they have forgotten their passwords, they only discover that they have forgotten the password during password verification. Therefore, it cannot meet the password verification requirements of scenes with quick demand or instant demand, such as when queuing to buy movie tickets. I forgot my password and need to verify the password.

[0049] In the embodiments of this specification, a password refers to a password consisting of one or more characters such as numeric characters and/or alphabetic characters and/or special characters. The combination of the password and/or the number of digits of the password does not constitute a limitation on this application.

[0050] Based on this, a new method is needed that can remind the user of the password before the user forgets the password, so as to meet the needs of password verification in quick demand scenarios or instant demand scenarios.

[0051] figure 1 The framework diagram of a password reminding method provided in the embodiment of this specification specifically includes:

[0052] Step S101: Obtain data to be processed, where the data to be processed includes password usage information, and/or user account value, and/or user password preference information, and/or password-based time information.

[0053] In the embodiment of this specification, the data to be processed is the data of the user who needs to perform password verification, and is used to reflect the historical information of the user's password verification. The data to be processed is data related to password verification. In the specific implementation process, the data to be processed is password usage information, and/or user account value, and/or user password preference information, and/or password-based time information, as well as user static information.

[0054] In the embodiment of this specification, in the to-be-processed data, the password usage information is based on an index formed based on the password usage behavior of the user in the password verification process. In the specific implementation process, the user’s password use behavior includes: the frequency of using the payment password, and/or the time when the password was last used, and/or the time when the password was forgotten the last time, and/or whether the password was forgotten the last time the password was used .

[0055] In the embodiment of this specification, the user's account value includes the number of cards bound to the account, and/or the transaction amount of the account, and/or the number of friends of the account, and/or the frequency of use of the account.

[0056] In the embodiments of this specification, in the data to be processed, the user’s password preference information refers to the user’s personal preference for using the password, which may specifically include the business scenario of the user’s use of the password, and/or the user’s security preference, and/or the user The transaction risk level of the password and/or the equipment used for password verification.

[0057] In the embodiments of this specification, the business scenario where the user uses the password refers to the business scenario where the user performs password verification. In the specific implementation process, the business environment for the user to use the password includes: non-immediate scenes or instantaneous scenes, non-immediate scenes, such as prepayment of utility bills; instantaneous scenes, such as queuing to buy movie tickets.

[0058] In the embodiments of this specification, the user’s security preference is a portrayal of the user. For example, some people are more cautious and habitually use passwords and change them. Some people are more casual, and the password may be very simple. This information can be passed through the user history. Operational behavior is described.

[0059] In the embodiments of this specification, the transaction risk level of the password used by the user refers to the risk level of the transaction. The risk level is generally determined by the corresponding model or strategy. For example, the transaction location is inconsistent with the user’s commonly used location, and the transaction equipment is commonly used by the user. Equipment inconsistencies and abnormal high-frequency operations are all high-risk transactions.

[0060] In the embodiments of this specification, the device condition used for password verification refers to whether the mobile terminal or the client is used when the password verification is performed.

[0061] In the embodiments of this specification, password-based time information refers to historical operations based on the user's use of the password, and/or payment activity, and/or payment mode. In the specific implementation process, the password-based time information includes: the number of days of the transaction, and/or the number of days of logging in or changing the password or changing the binding, and/or the means of payment verification, and/or the number of days of large-value transactions.

[0062] In the embodiment of this specification, in the data to be processed, the static information of the user is the basic attributes of the user's account, which is used to reflect the basic characteristics of the user or the account, including the user's age, and/or the opening time of the account, and/or the account Authentication time and/or account type. The type of account specifically includes whether the account is a corporate account or a personal account, and/or whether the account is for single use or multiple use.

[0063] Step S103: Input the to-be-processed data into a password reminder model to obtain the password forgotten probability corresponding to the to-be-processed data, where the password reminder model is based on a pre-trained password forgotten probability score obtained by a supervised learning method Model.

[0064] In the embodiment of this specification, the password reminder model is a model that scores the probability of password forgetting. The password reminder model is based on historical data, based on a model obtained by pre-training with a supervised learning method.

[0065] A supervised learning method is a machine learning task that infers functions from a labeled training data set.

[0066] In the embodiment of this specification, when the password reminder model is trained, the sample label data of the password reminder model includes black sample label data and white sample label data, where:

[0067] The black sample label data is the data of users who reset or search for passwords or lose their passwords in the process of using passwords in historical data;

[0068] The white sample label data is the data of the users who used the password and entered the password correctly in the historical data.

[0069] In an embodiment of this specification, the black sample label data is the data of the user who searches for the password through the port in the historical data and resets the password to perform business processing.

[0070] or

[0071] In historical data, the data of users lost in the process of searching for passwords,

[0072] or

[0073] In the historical data, the data of users lost in the process of using passwords.

[0074] In the specific implementation process, the password is searched through the port in the historical data. The port can be a payment port or a setting port;

[0075] The black label data is marked as 1, and the white label data is marked as 0.

[0076] In the embodiments of this specification, the statistical period of historical data can be selected from 3 months to 6 months, and the statistical period of historical data does not constitute a specific limitation to the application.

[0077] In the embodiment of this specification, the password reminder model is a model obtained based on a forget function and user-related information, where the forget function is a time-based function, and the user-related information includes static information of the user and/or password usage information, and / Or the user's account information, and/or the user's password preference information and/or password-based time information.

[0078] In the embodiment of this specification, the forgetting function and user-related information are respectively used as the input of the model to train the password reminder model. Among them, the forgetting function is used to reprocess and strengthen the time-related data, and is used to determine the degree of decay or weakening of the time-related data within a specific time length.

[0079] In the embodiment of this specification, the forgetting function x1=f(t), where t is time;

[0080] x2 is user-related information, then the password forgetting probability y=f(x1, x2), that is, the password forgetting probability is the probability obtained based on the forgetting function and user-related information.

[0081] Step S105: If the password forgetting probability is greater than or equal to the preset forgetting probability value, push a password modification reminder to the user.

[0082] Using the method provided in the foregoing steps, the password forgetting probability corresponding to the data to be processed can be obtained, and it is further necessary to determine whether a password modification reminder needs to be pushed to the user according to the preset forgetting probability value.

[0083] If the password forgotten probability is lower than the preset forgotten probability value, there is no need to push a password modification reminder to the user; if the password forgotten probability is greater than or equal to the preset forgotten probability value, a password modification reminder is pushed to the user to remind the user to modify Password reminder.

[0084] In the embodiment of the present specification, the selection of the preset forgetting probability value is based on ensuring that the user has a good experience and/or financial situation.

[0085] In an embodiment of this specification, the default forgetting probability value is 0.8.

[0086] After the user receives the pushed password modification reminder, he can decide independently whether he needs to modify the password, or he can set the system to require a password modification.

[0087] By adopting the data reminding method provided by the embodiment of this specification, the password modification reminder can be actively pushed during the user's login period, and the password modification reminder can be provided to the user to enhance the user's password verification experience.

[0088] figure 2 The schematic diagram of another data reminding method provided in the embodiment of this specification specifically includes:

[0089] Step S201: Obtain data to be processed, where the data to be processed includes password usage information, and/or user account value, and/or user password preference information, and/or password-based time information.

[0090] Step S203: Input the to-be-processed data into a password reminder model to obtain a password forgotten probability corresponding to the to-be-processed data, wherein the password reminder model is based on a pre-trained password forgotten probability score obtained by a supervised learning method Model.

[0091] Step S205: If the password forgetting probability is greater than or equal to the preset forgetting probability value, a password modification reminder is pushed to the user.

[0092] In the embodiment of this specification, the user who pushes the password modification reminder belongs to the user who easily forgets the password. In order to strengthen the user's memory of the password, thereby avoiding the situation of forgetting the password, after the password modification reminder is pushed to the user, it is further necessary to push the password to the user. Check reminder.

[0093] Step S207: Based on the current observation value and the user’s historical information, a password verification model is used to obtain a revenue value, wherein the password verification model is a model obtained by pre-training based on an enhanced learning method, and the current observation value includes the Password forgotten probability, and/or password preference information of the user.

[0094] In the embodiment of this specification, the current observation value is the user's password forgotten probability in the current transaction or the current transaction, and/or the user's password preference information.

[0095] Reinforcement learning is a machine learning method that enables the Agent to learn through experiments in an interactive environment and based on its actions and experience feedback errors.

[0096] The basic idea of ​​reinforcement learning is: tuple (s) composed of (state, behavior, reward, next state) t ,a t ,r t +1 ,s t+1 ) Is the sample for training, where s t Is the current state, a t Is the action executed in the current state, r t+1 Is the reward after executing the action, s t+1 For the next state.

[0097] In the embodiment of this specification, obtaining the password verification model includes:

[0098] Use historical information, the to-be-processed data and the password forgetting probability as state data;

[0099] Whether to use password verification as a decision variable;

[0100] Calculate the revenue function corresponding to the state transition function formed by the state data and the decision variable, and when the revenue function meets a preset condition, push a password verification reminder to the user.

[0101] In an embodiment of this specification, the status data specifically includes:

[0102] Preset historical information and current observations in the historical period, among which,

[0103] The historical information in the preset historical period includes password verification and result sequence,

[0104] The observed value includes the current transaction password forgotten probability and/or user preference information for using the password.

[0105] It should be noted that the preset historical period may be a certain preset time period, or may be an average password usage time period. In the specific implementation process, the preset historical period can be set in units of weeks or days. The preset historical period can be 1 week, or 30 days, or 90 days, or 180 days. The specific duration of the preset historical period does not constitute a limitation on this application.

[0106] In the embodiment of this specification, the password verification in the historical information refers to the decision whether to require the user to enter a password for verification at each time t, which is pushed to the user by the business end; and the result sequence in the historical information is the user The result of the password verification is the feedback information. The password verification and the result sequence are sequential in the entire time interval.

[0107] In an embodiment of this specification, the state transition function is the estimated value of the cryptographic verification result,

[0108] S t+1 = P t =P(a t |S t ,O t )

[0109] Where a t Indicates whether to use a password, O t Is the current observation, S t Is historical information, p t Is the probability of password forgetting.

[0110] In the examples of this specification, a t It is a time-related sequence, which can be in units of days or hours, depending on the business scenario.

[0111] The state transition function is the probability function of the action in the current state, and at the same time an estimated value of the password verification result. A probability value of 1 represents a successful password verification, and a probability value of 0 represents a password verification failure.

[0112] In an embodiment of this specification, the profit function is the profit or loss corresponding to the success or failure of password verification in the current business scenario,

[0113] r t =k t *p t

[0114] Where r t Is the revenue function, k t Is the risk level, p t Is the probability of password forgetting.

[0115] It should be particularly noted that the profit function takes into account the current risk level, and/or the user's sense of security preference, and/or the transaction scenario, and finally obtains the profit or loss corresponding to the success or failure of the password verification.

[0116] Based on the method provided by the embodiment of this specification, the corresponding value obtained from the revenue function is the revenue value, and the revenue of performing password verification reminder or not performing password verification reminder can be determined, so as to determine whether a password verification reminder needs to be pushed to the user.

[0117] Step S209: Based on the revenue value, it is determined whether a password verification reminder is required for the user.

[0118] The income value obtained in the foregoing steps is used to reflect the income of performing a password verification reminder or not performing a password verification reminder. According to the income value, it can be determined whether the user needs to be verified and reminded.

[0119] Step S211: If a password verification reminder needs to be issued to the user, a password verification reminder is pushed to the user.

[0120] The password verification reminding method provided in the embodiments of this specification requires a comprehensive balance of time and business scenarios in practical applications. In the specific implementation process, it can be applied to non-immediate, small payment scenarios, such as prepaid water and electricity. fee. The use of password verification reminders can strengthen the user's memory of the password, thereby avoiding or reducing the user's degree of forgetting the password in the future.

[0121] Using the method provided in the embodiment of this specification, it is possible to actively push the password modification reminder to the user, strengthen the user’s memory of the password, reduce the probability of password forgotten, and improve the user experience of the user using the password verification; the password verification reminder can strengthen the user’s The memory of the password, thereby avoiding or reducing the degree of user forgetting the password in the future.

[0122] The embodiment of this specification also provides a password reminding method, such as image 3 Shown. image 3 A framework diagram of a password reminding method provided in this embodiment of the specification, the password reminding method includes:

[0123] Step S301: Obtain data to be processed, where the data to be processed includes current observations and user historical information.

[0124] In the embodiment of this specification, the current observation value is the user's password forgotten probability in the current transaction or the current transaction, and/or the user's password preference information.

[0125] Step S303: Input the to-be-processed data into a password verification model to obtain a revenue value, wherein the password verification reminder model is a model obtained by pre-training based on an enhanced learning method, and the observed value this time includes the password forgetting probability , And/or the user's password preference information;

[0126] Step S305: Based on the revenue value, determine whether a password verification reminder is required for the user;

[0127] Step S307: If a password verification reminder needs to be issued to the user, a password verification reminder is pushed to the user.

[0128] The above content describes in detail a data reminding method. Correspondingly, the embodiment of this specification also provides a data reminding device, such as Figure 4 Shown. Figure 4 A schematic diagram of a data reminding device provided in this embodiment of the specification, the reminding device includes:

[0129] The acquiring module 401 acquires data to be processed, where the data to be processed includes password usage information, and/or user account value, and/or user password preference information, and/or password-based time information ;

[0130] The scoring module 403 inputs the to-be-processed data into a password reminder model to obtain the password forgotten probability corresponding to the to-be-processed data, wherein the password reminder model is based on the pre-trained password forgetting probability obtained by a supervised learning method Scoring model;

[0131] The password modification reminder module 405, if the password forgotten probability is greater than or equal to the preset forgotten probability value, pushes a password modification reminder to the user.

[0132] The reminder device includes:

[0133] The revenue module 407 uses a password verification model to obtain a revenue value based on the current observation value and the user’s historical information, wherein the password verification model is a model obtained by pre-training based on an enhanced learning method, and the current observation value includes all The password forgotten probability and/or the user’s preference information for using the password

[0134] The decision module 409, based on the income value, determines whether a password verification reminder is required for the user;

[0135] The password verification module 411, if a password verification reminder is required to the user, pushes a password verification reminder to the user.

[0136] Further, the obtaining module 401 further includes:

[0137] The data to be processed also includes static information of the user, where the static information includes the user's age, and/or occupation, and/or account type, and/or authentication duration, and/or activation time.

[0138] Further, the scoring module 403 specifically includes:

[0139] The password reminder model is a model obtained based on a forget function and user-related information, wherein the forget function is a time-based function, and the user-related information includes static information of the user, and/or password usage information, and/ Or the user’s account value, and/or the user’s password preference information, and/or password-based time information.

[0140] The sample data of the password reminder model includes black sample label data and white sample label data, where:

[0141] The black sample label data is data of users who have performed password reset or password search or lost in the process of using passwords in historical data;

[0142] The white sample label data is data of users who use passwords and input passwords in historical data.

[0143] The black sample label data is data of users who search for passwords through ports in historical data, and perform business processing by resetting passwords,

[0144] or

[0145] In historical data, the data of users lost in the process of searching for passwords,

[0146] or

[0147] In the historical data, the data of users lost in the process of using passwords.

[0148] Further, the decision module 407 specifically includes:

[0149] The training of the password verification model includes:

[0150] Use the user's historical information and current observations as state data, where the user's historical information is historical information within a preset historical period;

[0151] Whether to use password verification as a decision variable;

[0152] Calculate the profit function corresponding to the state transition function formed by the state data and the decision variable.

[0153] The state transition function is the estimated value of the cryptographic verification result,

[0154] S t+1 = P t =P(a t |S t ,O t )

[0155] Where a t Indicates whether to use a password, O t Is the current observation, S t Is historical information, p t Is the probability of password forgetting.

[0156] The revenue function is the revenue value corresponding to the success or failure of password verification in the current business scenario, and the revenue value is the gain or loss,

[0157] r t =k t *p t

[0158] Where r t Is the revenue function, k t Is the risk level, p t Is the probability of password forgetting.

[0159] The embodiment of this specification also provides another data reminding method. Correspondingly, the embodiment of this specification also provides another data reminding device, such as Figure 5 Shown. Figure 5 A schematic diagram of another data reminding device provided in the embodiment of this specification, the reminding device includes:

[0160] The obtaining module 501 obtains data to be processed, where the data to be processed includes current observations and user historical information;

[0161] The revenue module 503 inputs the to-be-processed data into a password verification model to obtain a profit value, wherein the password verification reminder model is a model obtained by pre-training based on an enhanced learning method, and the observation value this time includes password forgetting Probability, and/or password preference information of the user;

[0162] The decision module 505, based on the revenue value, determines whether a password verification reminder is required for the user;

[0163] The password verification module 507, if a password verification reminder is required to the user, pushes a password verification reminder to the user.

[0164] The revenue module 503 further includes:

[0165] The training of the password verification model includes:

[0166] Use the user's historical information and current observations as state data, where the user's historical information is historical information within a preset historical period;

[0167] Whether to use password verification as a decision variable;

[0168] Calculate the profit function corresponding to the state transition function formed by the state data and the decision variable.

[0169] The state transition function is the estimated value of the cryptographic verification result,

[0170] S t+1 = P t =P(a t |S t ,O t )

[0171] Where a t Indicates whether to use a password, O t Is the current observation, S t Is historical information, p t Is the probability of password forgetting.

[0172] The revenue function is the revenue value corresponding to the success or failure of password verification in the current business scenario, and the revenue value is the gain or loss,

[0173] r t =k t *p t

[0174] Where r t Is the revenue function, k t Is the risk level, p t Is the probability of password forgetting.

[0175] The embodiments of this specification provide an electronic device, including:

[0176] At least one processor; and,

[0177] A memory communicatively connected with the at least one processor; wherein,

[0178] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can:

[0179] Acquiring data to be processed, where the data to be processed includes password usage information, and/or user account value, and/or user password preference information, and/or password-based time information;

[0180] Input the to-be-processed data into a password reminder model to obtain a password forgotten probability corresponding to the to-be-processed data, wherein the password reminder model is a model for scoring the password forgetting probability obtained by pre-training based on a supervised learning method;

[0181] If the password forgetting probability is greater than or equal to the preset forgetting probability value, a password modification reminder is pushed to the user.

[0182] The embodiments of this specification provide still another electronic device, including:

[0183] At least one processor; and,

[0184] A memory communicatively connected with the at least one processor; wherein,

[0185] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can:

[0186] Acquiring data to be processed, where the data to be processed includes current observations and user historical information;

[0187] Input the to-be-processed data into a password verification model to obtain a revenue value, wherein the password verification reminder model is a model obtained by pre-training based on an enhanced learning method, and the observation value this time includes the password forgetting probability, and/ Or the user's preference information for using passwords;

[0188] Based on the revenue value, determine whether a password verification reminder is required for the user;

[0189] If a password verification reminder is required to the user, a password verification reminder is pushed to the user.

[0190] The foregoing describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than in the embodiments and still achieve desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0191] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, electronic equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and for related parts, please refer to the part of the description of the method embodiments.

[0192] The apparatus, electronic equipment, non-volatile computer storage medium and method provided in the embodiments of this specification correspond to each other. Therefore, the apparatus, electronic equipment, and non-volatile computer storage medium also have beneficial technical effects similar to the corresponding method. The beneficial technical effects of the method have been described in detail above, therefore, the beneficial technical effects of the corresponding device, electronic equipment, and non-volatile computer storage medium will not be repeated here.

[0193] In the 1990s, the improvement of a technology can be clearly distinguished between hardware improvements (for example, improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to method flow). However, with the development of technology, the improvement of many methods and procedures can be regarded as the direct improvement of the hardware circuit structure. Designers almost always get the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be realized by hardware entity modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user's programming of the device. It is programmed by the designer to "integrate" a digital system on a PLD without requiring the chip manufacturer to design and manufacture a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly realized by using "logic compiler" software, which is similar to the software compiler used in program development and writing, but before compilation The original code must also be written in a specific programming language, which is called Hardware Description Language (Hardware Description Language, HDL), and HDL is not only one, but there are many, such as ABEL (Advanced Boolean Expression Language) , AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (RubyHardware Description Language), etc. The most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. It should also be clear to those skilled in the art that only a little bit of logic programming of the method flow in the above-mentioned hardware description languages ​​and programming into an integrated circuit can easily obtain the hardware circuit that implements the logic method flow.

[0194] The controller can be implemented in any suitable manner. For example, the controller can take the form of a microprocessor or a processor and a computer-readable medium storing computer-readable program codes (such as software or firmware) executable by the (micro)processor. , Logic gates, switches, application specific integrated circuits (ASIC), programmable logic controllers and embedded microcontrollers. Examples of controllers include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicon Labs C8051F320, the memory controller can also be implemented as a part of the memory control logic. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, it is entirely possible to program the method steps to make the controller use logic gates, switches, application specific integrated circuits, programmable logic controllers and embedded The same function can be realized in the form of a microcontroller, etc. Therefore, such a controller can be regarded as a hardware component, and the devices included in it for implementing various functions can also be regarded as a structure within the hardware component. Or even, the device for realizing various functions can be regarded as both a software module for realizing the method and a structure within a hardware component.

[0195] The systems, devices, modules or units explained in the above embodiments may be implemented by computer chips or entities, or implemented by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cell phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or Any combination of these devices.

[0196] For the convenience of description, when describing the above device, the functions are divided into various units and described separately. Of course, when implementing one or more embodiments of this specification, the functions of each unit may be implemented in the same one or more software and/or hardware.

[0197] Those skilled in the art should understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of this specification may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0198] This specification is described with reference to flowcharts and/or block diagrams of methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and/or block in the flowchart and/or block diagram, and the combination of processes and/or blocks in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing equipment to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing equipment are generated for use In the process Figure one Process or multiple processes and/or boxes Figure one A device with functions specified in a block or multiple blocks.

[0199] These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing equipment to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction device. The device is implemented in the process Figure one Process or multiple processes and/or boxes Figure one Functions specified in a box or multiple boxes.

[0200] These computer program instructions can also be loaded on a computer or other programmable data processing equipment, so that a series of operation steps are executed on the computer or other programmable equipment to produce computer-implemented processing, so as to execute on the computer or other programmable equipment. Instructions are provided to implement the process Figure one Process or multiple processes and/or boxes Figure one Steps of functions specified in a box or multiple boxes.

[0201] In a typical configuration, the computing device includes one or more processors (CPU), input/output interfaces, network interfaces, and memory.

[0202] The memory may include non-permanent memory in computer readable media, random access memory (RAM) and/or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). Memory is an example of computer readable media.

[0203] Computer-readable media includes permanent and non-permanent, removable and non-removable media, and information storage can be realized by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disc (DVD) or other optical storage, Magnetic cassettes, magnetic tape storage or other magnetic storage devices or any other non-transmission media can be used to store information that can be accessed by computing devices. According to the definition in this article, computer-readable media does not include transitory media, such as modulated data signals and carrier waves.

[0204] It should also be noted that the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or equipment including a series of elements not only includes those elements, but also includes Other elements that are not explicitly listed, or include elements inherent to the process, method, commodity, or equipment. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, commodity or equipment that includes the element.

[0205] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The instructions can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0206] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, as for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for related parts, please refer to the part of the description of the method embodiment.

[0207] The above descriptions are only examples of this specification and are not intended to limit this application. For those skilled in the art, this application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included in the scope of the claims of this application.