A method for processing large-capacity user information

Abstract

The present invention relates to the technical field of account data processing, and specifically discloses a method for processing large-capacity user information, wherein the method obtains user information according to a registration request containing a registration time, and obtains user information indexed by a user account; inserts the user information indexed by the user account into an information database, and obtains a first address; inserts the first address of the user account and its corresponding user information into an index table; upon receiving an operation request containing a user account, locates a target area in the index table according to the time information in the user account, and obtains a first address; reads user information according to the obtained first address; and modifies the user information based on the operation request. The present invention generates an index table according to a user account containing time information and a first address when storing user information; converts operations on the information database into operations on a smaller index table, which greatly improves the running speed and facilitates popularization and use.

Description

Technical Field

[0001] The present invention relates to the technical field of account data processing, and in particular to a method for processing large-capacity user information. Background Art

[0002] With the development of computer technology and network technology, there are more and more network services. These network services will involve the user information management process. For some particularly large service providers, there is sufficient funds to add many sub-nodes. The user information is managed through the sub-nodes, so that the user information managed by each sub-node is not too large, thus ensuring the running speed.

[0003] However, some small and micro service providers are unable to provide many sub-nodes, and only a few devices support the processing of user information. As a result, each device faces a large amount of user information, the processing process is cumbersome, and the running speed is very slow. From the user's perspective, the processing process of their own information will be very long and the processing speed will be very slow, affecting the experience. Summary of the invention

[0004] The purpose of the present invention is to provide a method for processing large-capacity user information to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for processing large amounts of user information, the method comprising:

[0007] Receiving a registration request including registration time sent by a user, and generating a user account including time information according to the registration time;

[0008] Acquire user information according to the user account, and obtain user information with the user account as an index;

[0009] Insert the user information indexed by the user account into the information database and obtain the first address;

[0010] Inserting the first address of the user account and its corresponding user information into the index table; wherein the index table and the information database are in a mapping relationship, and the index table includes an account item and an address item;

[0011] Receive an operation request containing a user account sent by a user, locate the target area in the index table according to the time information in the user account, and obtain the first address;

[0012] Read user information according to the obtained first address;

[0013] The user information is modified based on the operation request.

[0014] As a further limitation of the technical solution of the present invention: the step of receiving a registration request containing a registration time sent by a user and generating a user account containing time information according to the registration time includes:

[0015] Receive the registration request sent by the user and randomly determine the verification method;

[0016] Obtaining verification questions according to the verification method, and sending the verification questions to the user;

[0017] Receiving a verification answer from the user, and comparing the verification answer with a reference answer;

[0018] When the comparison is successful, the success time is obtained, and the success time is input into the trained account generation model to obtain a user account containing time information; wherein the trained account generation model at least includes a random number generation sub-model.

[0019] As a further limitation of the technical solution of the present invention: the step of obtaining user information according to the user account to obtain user information indexed by the user account includes:

[0020] Establish a connection channel with the terminal where the user account is located and perform security verification on the terminal environment;

[0021] When the security verification is passed, the user information receiving port is opened;

[0022] The user information is acquired according to the user information receiving port, the user account is inserted into the user information and used as an index, and the user information with the user account as the index is obtained.

[0023] As a further limitation of the technical solution of the present invention: the step of inserting the first address of the user account and its corresponding user information into the index table comprises:

[0024] Read the index table, determine the node account according to the preset offset, extract the time information in the node account, and generate a node schedule; the node schedule includes a time information item and an offset item;

[0025] Extracting time information from a user account, determining the interval of the time information in the node timetable, and reading the corresponding endpoint offset;

[0026] The index table is intercepted according to the endpoint offset to obtain a sub-segment of the index table, and the first address of the user account and its user information is inserted into the sub-segment.

[0027] As a further limitation of the technical solution of the present invention: the step of receiving an operation request containing a user account from a user, locating a target area in the index table according to time information in the user account, and obtaining a first address comprises:

[0028] Receiving an operation request containing a user account sent by a user, and extracting time information from the user account;

[0029] Traversing the node schedule according to the time information in the user account, determining the interval of the time information in the user account in the node schedule, and reading the corresponding endpoint offset;

[0030] The index table is intercepted according to the endpoint offset to obtain a sub-segment of the index table, and the sub-segment is traversed based on the user account to obtain the first address.

[0031] As a further limitation of the technical solution of the present invention: the step of reading user information according to the acquired first address includes:

[0032] Read the first address obtained as the start character;

[0033] Read the next first address of the first address as a terminator;

[0034] The user information in the information database is located and read according to the start character and the end character.

[0035] As a further limitation of the technical solution of the present invention: the step of modifying the user information based on the operation request includes:

[0036] Read the operation records in the user information, and calculate the user's operation frequency within a preset time period based on the operation records;

[0037] Sort the operation requests according to the operation frequency to obtain a request cache table;

[0038] The user information is modified based on the operation requests in the cache table in turn.

[0039] As a further limitation of the technical solution of the present invention: the step of modifying the user information based on the operation requests in the cache table in sequence comprises:

[0040] Extract the user account in the operation request, and obtain the interaction data between the user account and the contact account; wherein the contact account is another user account with which the user account has interaction data;

[0041] classifying the contact accounts according to the interaction data;

[0042] An update instruction is sent to the contact account according to a preset update speed; wherein contact accounts of different levels correspond to different update speeds.

[0043] As a further limitation of the technical solution of the present invention: the step of grading the contact accounts according to the interaction data includes:

[0044] Obtaining interaction data between the user account and different contact accounts in sequence, classifying the interaction data according to the sender in the interaction data, and obtaining active interaction data and passive interaction data;

[0045] Calculate the number of active interaction data and passive interaction data respectively, and calculate the ratio between the number of active interaction data and the number of passive interaction data;

[0046] The ratio is compared with a preset ratio range, and the contact accounts are graded according to the comparison result.

[0047] As a further limitation of the technical solution of the present invention: the step of modifying the user information based on the operation requests in the cache table in sequence further includes:

[0048] Obtain the number of operation requests from the same user account within a preset time period in real time;

[0049] When the number of operation requests is greater than a preset number threshold, an excess margin is calculated according to the number of operation requests and the number threshold, and the preset update speed is corrected according to the excess margin.

[0050] Compared with the prior art, the beneficial effects of the present invention are: the present invention generates an index table based on the user account containing time information and the first address when storing user information; the operations on the information database are converted into operations on a smaller index table, which greatly improves the operating speed and facilitates promotion and use. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0052] Figure 1 A flowchart of a method for processing large amounts of user information is shown.

[0053] Figure 2 A first sub-flow chart of a method for processing large-capacity user information is shown.

[0054] Figure 3 A second sub-flow chart of the method for processing large-capacity user information is shown.

[0055] Figure 4 A third sub-flow chart of the method for processing large-capacity user information is shown.

[0056] Figure 5 A fourth sub-flow chart of the method for processing large-capacity user information is shown.

[0057] Figure 6 A fifth sub-flow chart of the method for processing large-volume user information is shown.

[0058] Figure 7 A sixth sub-flow chart of the method for processing large-capacity user information is shown.

[0059] Figure 8 A seventh sub-flow chart of the method for processing large-capacity user information is shown.

[0060] Fig. 9 An eighth sub-flow chart of the method for processing large-capacity user information is shown. DETAILED DESCRIPTION

[0061] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0062] Example 1

[0063] Figure 1 A flowchart of a method for processing large amounts of user information is shown. In an embodiment of the present invention, a method for processing large amounts of user information includes steps S100 to S700:

[0064] Step S100: receiving a registration request including registration time sent by a user, and generating a user account including time information according to the registration time;

[0065] Step S100 is the registration process. In existing network application apps, account-related content is involved. Users who use the app generally have a unique account. When a user uses the app for the first time, he or she can send a registration request. At this time, the background of the app generates a public number containing the registration time. The public number can be understood as our common account.

[0066] Step S200: Obtain user information according to the user account, and obtain user information indexed by the user account;

[0067] In the registration process, in addition to generating a public address containing the registration time, the background of the App also needs to complete personal information. The personal information is the user information in the technical solution of the present invention. Common user information includes nicknames, avatars, signatures, etc. Of course, user information may also include other content, even some files uploaded by users, etc., which can all be regarded as user information. These user information are often stored as a data packet, and the user account is the "name" of the data packet, which is the above process of obtaining user information indexed by the user account.

[0068] Step S300: inserting the user information indexed by the user account into the information database, and obtaining the first address;

[0069] The process of storing the user information indexed by the user account in the information database does not necessarily have to be stored in a certain order. On the contrary, with the rapid development of cloud storage technology today, the user information corresponding to two user accounts registered before and after is likely to be stored in a location far away. Therefore, in the storage process, it is also necessary to obtain address information.

[0070] Step S400: inserting the first address of the user account and its corresponding user information into the index table; wherein the index table and the information database are in a mapping relationship, and the index table includes an account item and an address item;

[0071] Step S400 is the index table generation process. In layman's terms, the index table is to connect each user's information and the user account and its address into data pairs, and then count these data pairs into a table, which is the above-mentioned index table;

[0072] Step S500: receiving an operation request sent by a user and containing a user account, locating a target area in the index table according to time information in the user account, and obtaining a first address;

[0073] Step S600: Reading user information according to the acquired first address;

[0074] Step S700: Modify the user information based on the operation request.

[0075] Steps S500 to S700 are application steps. The user sends an operation request containing a user account. The background locates the target area in the index table according to the time information in the user account, and then obtains the first address with the help of the index table to query the user information. The user information is modified according to the user's operation request. It is worth mentioning that the modification means modifying the user information to the user's target information, and the correctness is judged by the user.

[0076] Figure 2The first sub-flow chart of the method for processing large-capacity user information is shown, wherein the step of receiving a registration request containing a registration time sent by a user and generating a user account containing time information according to the registration time includes steps S101 to S104:

[0077] Step S101: receiving a registration request sent by a user and randomly determining a verification method;

[0078] Step S102: obtaining a verification question according to the verification method, and sending the verification question to the user;

[0079] Step S103: receiving the user's verification answer, and comparing the verification answer with the reference answer;

[0080] Step S104: When the comparison is successful, the success time is obtained, and the success time is input into the trained account generation model to obtain a user account containing time information; wherein the trained account generation model at least includes a random number generation sub-model.

[0081] Step S101-Step S104 describes a specific registration process. During the registration process, some people may maliciously register through software. In this regard, the present invention adopts a verification code method to determine whether the registrant is a natural person; the above content is different from the prior art in that, in addition to the random changes in the verification questions, the verification method also changes randomly; for example, some adopt the form of moving the picture to a specified position, and some adopt the method of reading information from a blurred picture, which will not be described in detail.

[0082] Figure 3 The second sub-flow chart of the method for processing large-capacity user information is shown, wherein the step of obtaining user information according to the user account and obtaining user information indexed by the user account includes steps S201 to S203:

[0083] Step S201: Establishing a connection channel with the terminal where the user account is located and performing security verification on the terminal environment;

[0084] Step S202: When the security verification is passed, the user information receiving port is opened;

[0085] Step S203: acquiring user information according to the user information receiving port, inserting the user account into the user information and using it as an index, and obtaining user information with the user account as an index.

[0086] The above content adds a security verification process in the information acquisition stage. Since the user information in the technical solution of the present invention is not limited to images or texts, etc., its content is very diverse and it is easy for some inappropriate content to appear. The purpose of security verification is to shield some inappropriate content in user information.

[0087] Figure 4 The third sub-flow chart of the method for processing large-capacity user information is shown, wherein the step of inserting the first address of the user account and its corresponding user information into the index table includes steps S401 to S403:

[0088] Step S401: reading the index table, determining the node account according to the preset offset, extracting the time information in the node account, and generating a node schedule; the node schedule includes a time information item and an offset item;

[0089] Step S402: extracting time information from the user account, determining the interval of the time information in the node time table, and reading the corresponding endpoint offset;

[0090] Step S403: intercepting the index table according to the endpoint offset to obtain a sub-segment of the index table, and inserting the first address of the user account and its user information into the sub-segment.

[0091] For some apps with a large number of users, the data in the index table is very large. Although in theory, the storage address of any user information can be found in the index table by traversal, in actual operation, the traversal process takes a long time, and when the number of users reaches a certain limit, at certain moments, the background may receive operation requests sent by many users at the same time. For the feedback of these operation requests, the first thing to do is to query the corresponding user information, and then proceed to the next step. It can be imagined that if each query process is performed in a traversal manner, the feedback efficiency will be extremely low.

[0092] Therefore, in the above content, the technical solution of the present invention provides a method of querying through positioning through nodes; the offset is a preset value, which can be set to 1Kb, and the corresponding node address can be 0Kb, 1Kb, 2Kb,..., and so on; the user accounts at these nodes are read, and then the time information in the user account is extracted to obtain the node schedule; when the user wants to insert new user information into the index table, the two parties to be compared are the time information in the new user account and the node schedule, which greatly improves the comparison efficiency; after determining the interval, the facing subject is the sub-segment of the index table. The index table sub-segment in the above example is 1Kb in size, and the insertion process is very simple.

[0093] Figure 5The fourth sub-flow chart of the method for processing large-capacity user information is shown, wherein the step of receiving an operation request containing a user account sent by a user, locating a target area in the index table according to the time information in the user account, and obtaining the first address includes steps S501 to S503:

[0094] Step S501: receiving an operation request containing a user account sent by a user, and extracting time information from the user account;

[0095] Step S502: traverse the node schedule according to the time information in the user account, determine the interval of the time information in the user account in the node schedule, and read the corresponding endpoint offset;

[0096] Step S503: intercepting the index table according to the endpoint offset to obtain a sub-segment of the index table, traversing the sub-segment based on the user account to obtain the first address.

[0097] The process from step S501 to step S503 is somewhat similar to that from step S401 to step S403, except that step S501 to step S503 is a data reading process, and step S401 to step S403 is a data adding process.

[0098] Figure 6 The fifth sub-flow chart of the method for processing large-capacity user information is shown, wherein the step of reading user information according to the acquired first address includes steps S601 to S603:

[0099] Step S601: read the first address obtained as the start character;

[0100] Step S602: reading the next first address of the first address as a terminator;

[0101] Step S603: Locate and read the user information in the information database according to the start character and the end character.

[0102] The first address is an endpoint, and the user information requires two endpoints to be determined. The address in the index table is the first address of the user information, that is, the starting point of the user information. It is easy to think that the end point of the user information is the starting point of the next user information. Therefore, the next address of the first address is read as the terminator; it is worth mentioning that in the index table, the first address and the next address of the first address are two adjacent elements in the address item. This reading process does not involve traversal of the entire index table, and the reading process is very fast.

[0103] Figure 7 A sixth sub-flow chart of the method for processing large-capacity user information is shown, wherein the step of modifying the user information based on the operation request comprises:

[0104] Step S701: reading the operation records in the user information, and calculating the operation frequency of the user within a preset time period according to the operation records;

[0105] Step S702: sorting the operation requests according to the operation frequency to obtain a request cache table;

[0106] Step S703: modify the user information based on the operation requests in the cache table in sequence.

[0107] During certain specific time periods, such as lunch breaks, the background may receive a large number of operation requests. For these operation requests, there must be a sequence, and the judgment standard of the sequence is determined according to the frequency of the operation. If a user frequently modifies user information, the background can put his request in the front row, which can play an incentive role and make the connection between the App and the user closer and closer. Of course, the background can also put his request in the back row to give people who do not frequently send operation requests a better operation experience, thereby acquiring new users. There is no difference between the two solutions, and the present invention does not make specific limitations.

[0108] Example 2

[0109] Figure 8 The seventh sub-flow chart of the method for processing large-capacity user information is shown. Based on the first embodiment, the embodiment of the present invention provides a specific technical solution, further describing the process of modifying user information. The step of modifying the user information based on the operation request in the cache table in sequence includes steps S7011 to S7013:

[0110] Step S7011: extract the user account in the operation request, and obtain the interaction data between the user account and the contact account; wherein the contact account is another user account with which the user account has interaction data;

[0111] Step S7012: classifying the contact accounts according to the interaction data;

[0112] Step S7013: sending an update instruction to the contact account according to a preset update speed; wherein contact accounts of different levels correspond to different update speeds.

[0113] The above content provides a specific correction process. First, it should be noted that the user's operation request is diverse. For example, the user's operation request is to change the avatar. After the avatar is changed, the user information changes. Who first discovers this change is the problem to be solved by the above content. The technical solution of the present invention faces a large amount of user information. After a user's information changes, it is obviously not realistic to display it in real time on other users' terminals. Therefore, it is necessary to display it selectively.

[0114] The recipients of user information changes are the user's friends, but some of the user's friends are very closely connected with the user, while some are not so close. Sending update instructions to different friends according to different update speeds makes the propagation process of user information changes spread out in circles like a drop of water falling into a lake, which can greatly alleviate the computing pressure.

[0115] Fig. 9 The eighth sub-flow chart of the method for processing large-capacity user information is shown, wherein the step of grading the contact accounts according to the interaction data comprises:

[0116] Step S70121: sequentially obtain interaction data between the user account and different contact accounts, classify the interaction data according to the sender in the interaction data, and obtain active interaction data and passive interaction data;

[0117] Step S70122: Calculate the number of active interaction data and the number of passive interaction data respectively, and calculate the ratio between the number of active interaction data and the number of passive interaction data;

[0118] Step S70123: Compare the ratio with a preset ratio range, and classify the contact accounts according to the comparison result.

[0119] The above content provides a specific user classification process. From a computer perspective, it is difficult to obtain changes in user emotions. Processing data is what computers are good at, and interactive data can well reflect the relationship between users and their friends. However, there is a difference in the above content. It does not judge the relationship between the two parties by the number of interactive data items, but by the equality of the interaction between the two parties. In layman's terms, unilateral data exchange cannot explain the quality of a relationship. Two-way data exchange is more meaningful.

[0120] In addition, in a preferred embodiment of the present invention, the step of modifying the user information based on the operation requests in the cache table in sequence further includes:

[0121] Obtain the number of operation requests from the same user account within a preset time period in real time;

[0122] When the number of operation requests is greater than a preset number threshold, an excess margin is calculated according to the number of operation requests and the number threshold, and the preset update speed is corrected according to the excess margin.

[0123] The purpose of the above content is that if a user repeatedly modifies his / her profile picture, the corresponding update speed will also slow down until the user has determined a certain profile picture and it meets the user's expectations, then it will be updated in other account information.

[0124] The functions that can be achieved by the above-mentioned method for processing large-capacity user information are all completed by a computer device, which includes one or more processors and one or more memories, and the one or more memories store at least one program code. The program code is loaded and executed by the one or more processors to implement the method for processing large-capacity user information.

[0125] The processor takes out instructions from the memory one by one, analyzes the instructions, and then completes the corresponding operations according to the instruction requirements, generating a series of control commands, so that the various parts of the computer can automatically, continuously and coordinately move to become an organic whole, realize the input of programs, the input of data, and the calculation and output of results. The arithmetic operations or logical operations generated in this process are all completed by the operator; the memory includes a read-only memory (ROM), which is used to store computer programs, and a protection device is provided outside the memory.

[0126] Exemplarily, the computer program may be divided into one or more modules, one or more modules are stored in a memory and executed by a processor to implement the present invention. One or more modules may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program in a terminal device.

[0127] Those skilled in the art will understand that the description of the above service equipment is merely an example and does not constitute a limitation on the terminal equipment. It may include more or fewer components than described above, or a combination of certain components, or different components, for example, it may include input and output devices, network access devices, buses, etc.

[0128] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire user terminal.

[0129] The above-mentioned memory can be used to store computer programs and / or modules. The above-mentioned processor realizes various functions of the above-mentioned terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as an information collection template display function, a product information release function, etc.), etc.; the data storage area can store data created according to the use of the berth status display system (such as product information collection templates corresponding to different product types, product information that different product providers need to release, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0130] If the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable medium. Based on this understanding, the present invention implements all or part of the modules / units in the above-mentioned embodiment system, and can also be completed by instructing the relevant hardware through a computer program. The above-mentioned computer program can be stored in a computer-readable medium, and the computer program can realize the functions of the above-mentioned various system embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0131] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0132] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for processing large amounts of user information, characterized in that: The method comprises: Receiving a registration request including registration time sent by a user, and generating a user account including time information according to the registration time; Acquire user information according to the user account, and obtain user information with the user account as an index; Insert the user information indexed by the user account into the information database and obtain the first address; Inserting the first address of the user account and its corresponding user information into the index table; wherein the index table and the information database are in a mapping relationship, and the index table includes an account item and an address item; Receive an operation request containing a user account sent by a user, locate the target area in the index table according to the time information in the user account, and obtain the first address; Read user information according to the obtained first address; modifying the user information based on the operation request; The step of inserting the first address of the user account and its corresponding user information into the index table comprises: Read the index table, determine the node account according to the preset offset, extract the time information in the node account, and generate a node schedule; the node schedule includes a time information item and an offset item; Extracting time information from a user account, determining the interval of the time information in the node timetable, and reading the corresponding endpoint offset; intercepting the index table according to the endpoint offset to obtain a sub-segment of the index table, and inserting the first address of the user account and its user information into the sub-segment; The step of receiving an operation request containing a user account from a user, locating a target area in the index table according to time information in the user account, and obtaining a first address comprises: Receiving an operation request containing a user account sent by a user, and extracting time information from the user account; Traversing the node schedule according to the time information in the user account, determining the interval of the time information in the user account in the node schedule, and reading the corresponding endpoint offset; The index table is intercepted according to the endpoint offset to obtain a sub-segment of the index table, and the sub-segment is traversed based on the user account to obtain the first address; The step of reading user information according to the acquired first address includes: Read the first address obtained as the start character; Read the next first address of the first address as a terminator; The user information in the information database is located and read according to the start character and the end character.

2. The method for processing large amounts of user information according to claim 1, characterized in that: The step of receiving a registration request containing a registration time sent by a user and generating a user account containing time information according to the registration time includes: Receive the registration request sent by the user and randomly determine the verification method; Obtaining verification questions according to the verification method, and sending the verification questions to the user; Receiving a verification answer from the user, and comparing the verification answer with a reference answer; When the comparison is successful, the success time is obtained, and the success time is input into the trained account generation model to obtain a user account containing time information; wherein the trained account generation model at least includes a random number generation sub-model.

3. The method for processing large-volume user information according to claim 1, characterized in that: The step of obtaining user information based on the user account to obtain user information indexed by the user account includes: Establish a connection channel with the terminal where the user account is located and perform security verification on the terminal environment; When the security verification is passed, the user information receiving port is opened; The user information is acquired according to the user information receiving port, the user account is inserted into the user information and used as an index, and the user information with the user account as an index is obtained.

4. The method for processing large-volume user information according to claim 1, characterized in that: The step of modifying the user information based on the operation request comprises: Read the operation records in the user information, and calculate the user's operation frequency within a preset time period based on the operation records; Sort the operation requests according to the operation frequency to obtain a request cache table; The user information is modified based on the operation requests in the cache table in turn.

5. The method for processing large-volume user information according to claim 4, characterized in that: The step of modifying the user information based on the operation request in the cache table in sequence comprises: Extract the user account in the operation request, and obtain the interaction data between the user account and the contact account; wherein the contact account is another user account with which the user account has interaction data; classifying the contact accounts according to the interaction data; An update instruction is sent to the contact account according to a preset update speed; wherein contact accounts of different levels correspond to different update speeds.

6. The method for processing large-volume user information according to claim 5, characterized in that: The step of grading the contact accounts according to the interaction data comprises: Obtaining interaction data between the user account and different contact accounts in sequence, classifying the interaction data according to the sender in the interaction data, and obtaining active interaction data and passive interaction data; Calculate the number of active interaction data and passive interaction data respectively, and calculate the ratio between the number of active interaction data and the number of passive interaction data; The ratio is compared with a preset ratio range, and the contact accounts are graded according to the comparison result.

7. The method for processing large-volume user information according to claim 5, characterized in that: The step of modifying the user information based on the operation requests in the cache table in sequence further includes: Obtain the number of operation requests from the same user account within a preset time period in real time; When the number of operation requests is greater than a preset number threshold, an excess margin is calculated according to the number of operation requests and the number threshold, and the preset update speed is corrected according to the excess margin.

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