Value-added service abnormal distribution monitoring method and device, equipment and medium

Abstract

The invention provides a value-added service abnormal distribution monitoring method and device, equipment and a medium, and the method comprises the steps: obtaining the request information of a target user for a target value-added service, and generating a target user portrait of the target user according to the request information; determining a first matching result of the portrait of the target user and a preset portrait library; when the first matching result indicates that the abnormal user portrait similar to the target user portrait does not exist in the preset portrait library, determining a service request attribute of the target user; determining a second matching result of the service request attribute and a preset early warning rule; and generating early warning information of abnormal distribution of the value-added service according to the second matching result. Therefore, automatic monitoring and early warning of abnormal distribution of the value-added service can be realized, so that the timeliness and accuracy of processing abnormal distribution of the value-added service are effectively improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of insurance value-added service distribution, and particularly relates to a value-added service abnormal distribution monitoring method, device, equipment and medium. BACKGROUND

[0002] With the rapid development of the insurance industry, the value-added service products derived from insurance are increasing, and effective management of insurance derived products becomes particularly important. However, in the process of value-added service distribution, there may be abnormal situations such as "high-frequency distribution of value-added services in a short time", which brings potential risks and challenges to insurance companies. At present, these abnormal situations are mainly handled by manual investigation, but this method has the disadvantages of lag and difficulty in detection. SUMMARY

[0003] The present disclosure aims to at least partially solve one of the technical problems in the related art.

[0004] To this end, the purpose of the present disclosure is to propose a value-added service abnormal distribution monitoring method, device, computer equipment and storage medium, thereby realizing automatic monitoring and early warning of value-added service abnormal distribution, and effectively improving the timeliness and accuracy of handling value-added service abnormal distribution.

[0005] To achieve the above purpose, the value-added service abnormal distribution monitoring method according to the first aspect of the present disclosure comprises:

[0006] obtaining request information of a target user for a target value-added service, and generating a target user portrait of the target user according to the request information;

[0007] determining a first matching result of the target user portrait and a preset portrait library;

[0008] when the first matching result indicates that there is no abnormal user portrait similar to the target user portrait in the preset portrait library, determining a service request attribute of the target user;

[0009] determining a second matching result of the service request attribute and a preset early warning rule;

[0010] generating early warning information of value-added service abnormal distribution according to the second matching result.

[0011] To achieve the above purpose, the value-added service abnormal distribution monitoring device according to the second aspect of the present disclosure comprises:

[0012] an obtaining module, configured to obtain request information of a target user for a target value-added service, and generate a target user portrait of the target user according to the request information;

[0013] The first determining module is configured to determine a first matching result of the target user portrait and a preset portrait library.

[0014] The second determining module is configured to determine a service request attribute of the target user when the first matching result indicates that there is no abnormal user portrait similar to the target user portrait in the preset portrait library.

[0015] The third determining module is configured to determine a second matching result of the service request attribute and a preset warning rule.

[0016] The generating module is configured to generate warning information of abnormal distribution of value-added services according to the second matching result.

[0017] The computer device provided in the third aspect of the present disclosure includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the monitoring method of abnormal distribution of value-added services provided in the first aspect of the present disclosure when executing the program.

[0018] The fourth aspect of the present disclosure provides a non-transitory computer readable storage medium having a computer program stored thereon, and the program is executed by a processor to implement the monitoring method of abnormal distribution of value-added services provided in the first aspect of the present disclosure.

[0019] The fifth aspect of the present disclosure provides a computer program product, and when the instructions in the computer program product are executed by a processor, the monitoring method of abnormal distribution of value-added services provided in the first aspect of the present disclosure is executed.

[0020] The monitoring method, device, computer device, and storage medium provided by the present disclosure can realize automatic monitoring and warning of abnormal distribution of value-added services by obtaining request information of a target user for a target value-added service, generating a target user portrait of the target user according to the request information, determining a first matching result of the target user portrait and a preset portrait library, determining a service request attribute of the target user when the first matching result indicates that there is no abnormal user portrait similar to the target user portrait in the preset portrait library, determining a second matching result of the service request attribute and a preset warning rule, and generating warning information of abnormal distribution of value-added services according to the second matching result. Thus, the timeliness and accuracy of processing abnormal distribution of value-added services can be effectively improved.

[0021] Additional aspects and advantages of the present disclosure will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0022] The above-mentioned and / or additional aspects and advantages of the present disclosure will become apparent and easy to understand from the following description of the embodiments taken together with the accompanying drawings, in which:

[0023] Figure 1 is a flowchart of a monitoring method for abnormal value-added service distribution according to an embodiment of the present disclosure;

[0024] Figure 2 is a schematic diagram of value-added service distribution according to the present disclosure;

[0025] Figure 3 is a schematic diagram of abnormal value-added service distribution warning according to the present disclosure;

[0026] Figure 4 is a flowchart of a method for monitoring abnormal value-added service distribution based on a warning rule according to the present disclosure;

[0027] Figure 5 is a structural diagram of a monitoring device for abnormal value-added service distribution according to an embodiment of the present disclosure;

[0028] Figure 6 shows a block diagram of an exemplary computer device suitable for implementing embodiments of the present disclosure. DETAILED DESCRIPTION

[0029] The embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, in which the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by reference to the drawings are exemplary and are used only to explain the present disclosure, and cannot be understood as limiting the present disclosure. On the contrary, the embodiments of the present disclosure include all changes, modifications and equivalents falling within the spirit and scope of the appended claims.

[0030] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data for analysis, stored data, displayed data, etc.) and signals involved in the present disclosure are authorized by the user or fully authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0031] Figure 1 is a flowchart of a monitoring method for abnormal value-added service distribution according to an embodiment of the present disclosure.

[0032] It should be noted that the execution subject of the monitoring method for the abnormal distribution of value-added services in the embodiment is a monitoring device for the abnormal distribution of value-added services. The device can be implemented in software and / or hardware. The device can be configured in a computer device, which can include but is not limited to a terminal, a server, and the like. For example, the terminal can be a mobile phone, a palm computer, and the like.

[0033] As shown in Figure 1 The monitoring method for the abnormal distribution of value-added services includes the following steps.

[0034] S101: Obtain the request information of the target user for the target value-added service, and generate the target user portrait of the target user according to the request information.

[0035] The target user can refer to a user who requests a target value-added service.

[0036] The target value-added service can refer to a value-added service that needs to be monitored for service abnormal distribution. For example, it can be a value-added service in an insurance business.

[0037] The request information can refer to relevant information used by the target user to request the target value-added service.

[0038] The target user portrait can be used to indicate relevant characteristics of the target user requesting the target value-added service.

[0039] In the embodiment of the disclosure, when the request information of the target user for the target value-added service is obtained, and the target user portrait of the target user is generated according to the request information, reliable data support can be provided for subsequent determination of the first matching result.

[0040] S102: Determine the first matching result of the target user portrait and the preset portrait library.

[0041] The preset portrait library can be a portrait library constructed for users who have been confirmed to be abnormal in requesting value-added services.

[0042] Optionally, in some embodiments, the preset portrait library is constructed based on the following manner: determining an abnormal request user for the target value-added service; generating an abnormal user portrait corresponding to each abnormal request user; and constructing the preset portrait library based on a plurality of abnormal user portraits. In this way, it can be ensured that the obtained preset portrait library accurately indicates the user portrait of the abnormal request value-added service, thereby providing reliable execution basis for determining the first matching result.

[0043] The abnormal request user can refer to a user who requests a value-added service through abnormal means.

[0044] That is to say, after the request information of the target user for the target value-added service is acquired and the target user portrait of the target user is generated according to the request information in the embodiments of the present disclosure, the first matching result of the target user portrait and the preset portrait library can be determined, so as to determine whether the target user meets the product distribution condition of the target value-added service.

[0045] S103: determining the service request attribute of the target user when the first matching result indicates that there is no abnormal user portrait similar to the target user portrait in the preset portrait library.

[0046] The service request attribute can be used for the related attribute of the target user requesting the target value-added service.

[0047] Optionally, in some embodiments, the service request attribute includes: a service cumulative request number, a service request channel, and a service request location. Thus, the indication comprehensiveness of the obtained service request attribute can be ensured.

[0048] The service cumulative request number can be the number of times that the target user accumulatively requests the target value-added service within a specified time range.

[0049] The service request channel can be the channel used by the target user when requesting the target value-added service. For example, it can be a service provider gift, a gift of another service, and the like, which is not limited.

[0050] The service request location can be used to describe the location of the target user when requesting the target value-added service. For example, it can be used to indicate the province, city, and the like where the user is located, which is not limited.

[0051] When the first matching result indicates that there is no abnormal user portrait similar to the target user portrait in the preset portrait library, the service request attribute of the target user is determined in the embodiments of the present disclosure, which can provide reliable data support for subsequent determination of the second matching result.

[0052] S104: determining the second matching result of the service request attribute and the preset warning rule.

[0053] The preset warning rule can be a rule configured in advance for determining whether value-added service abnormal distribution warning is needed. The preset warning rule can be flexibly configured according to the application scenario, which is not limited.

[0054] Optionally, in some embodiments, the preset early warning rule comprises: a preset number threshold, a channel management list, and a management location list; wherein the second matching result of the service request attribute and the preset early warning rule comprises: a third matching result of the service cumulative request number and the preset number threshold; a fourth matching result of the service request channel and the channel management list; a fifth matching result of the service request location and the management location list; and the third matching result, the fourth matching result, and the fifth matching result are combined as the second matching result. In this way, the indication comprehensiveness and flexibility of the obtained second matching result can be effectively improved.

[0055] The preset number threshold refers to a threshold configured in advance for the service cumulative request number.

[0056] The channel management list refers to a list of request channels that need to be managed, which is configured in advance.

[0057] The management location list refers to a list of locations that need to be managed, which is configured in advance.

[0058] That is, in the embodiments of the present disclosure, after determining the service request attribute, the second matching result can be obtained by matching the service request attribute with the preset early warning rule, thereby providing a reliable triggering condition for generating the early warning information of the abnormal distribution of the value-added service.

[0059] S105: generating the early warning information of the abnormal distribution of the value-added service according to the second matching result.

[0060] The early warning information can be used to indicate the ID of the target user, the number of winning times, the triggering event, and the like.

[0061] Optionally, in some embodiments, when the early warning information of the abnormal distribution of the value-added service is generated according to the second matching result, at least one of the following is included:

[0062] When the third matching result indicates that the service cumulative request number is greater than the preset number threshold, the early warning information is generated.

[0063] When the fourth matching result indicates that the service request channel belongs to the channel management list, the early warning information is generated.

[0064] When the fifth matching result indicates that the service request location belongs to the management location list, the early warning information is generated.

[0065] In this way, whether the corresponding early warning information needs to be generated can be accurately and quickly determined according to the attribute characteristics of different dimensions.

[0066] In this embodiment, the system acquires the target user's request information for the target value-added service and generates a target user portrait based on the request information. It then determines a first matching result between the target user portrait and a preset portrait library. When the first matching result indicates that there is no abnormal user portrait similar to the target user portrait in the preset portrait library, it determines the target user's service request attributes. Finally, it determines a second matching result between the service request attributes and preset warning rules. Based on the second matching result, it generates warning information for abnormal allocation of value-added services. This enables automated monitoring and warning of abnormal allocation of value-added services, effectively improving the timeliness and accuracy of handling such cases.

[0067] Optionally, in some embodiments, the following steps may also be taken: determining a statistical value for the warning information corresponding to the target user, wherein the warning information is used to indicate the cumulative number of warning messages generated for the target user; and sending the warning information to the warning information recipient when the statistical value reaches a preset warning threshold. Thus, warning information can be sent to the warning information recipient based on a preset warning threshold, effectively avoiding the increased workload of the warning information recipient caused by frequent sending of warning information.

[0068] Among them, the recipient of the early warning information can refer to the manager of the value-added service.

[0069] In summary, the most significant improvement of the proposed solution lies in the use of an automated early warning mechanism to achieve real-time monitoring and rapid response to abnormal situations in the distribution of value-added services, thereby significantly improving the efficiency and accuracy of investigation, reducing operating costs, and effectively preventing potential risks.

[0070] like Figure 2 As shown, Figure 2 Based on the value-added service distribution diagram presented in this disclosure, the core logic of this solution lies in implementing abnormal distribution warnings for customers participating in lucky draw activities and generating value-added service orders. For example... Figure 3 As shown, Figure 3 Based on the abnormal value-added service distribution warning diagram proposed in this disclosure, the system supports custom configuration of warning rules, including controlled provinces, channels, and warning thresholds, in order to achieve refined control over different regions, distribution channels, and threshold conditions.

[0071] For example, if a customer is detected placing frequent orders due to winning prizes within a short period, an alert mechanism will be activated, pushing key data such as customer information and prize-winning channels to branch office operations personnel in real time for rapid verification and processing. This technical solution not only significantly shortens the problem identification and processing cycle and reduces operating costs, but also effectively prevents risks, thereby improving service quality and user experience.

[0072] The scheme is developed by using Java programming language and uses redis-Cell module as a cache solution to record high-frequency data of order distribution efficiently and realize the anti-disturbance do-not-disturb mechanism. By setting personalized threshold values for different provinces and channels and assigning specific dimension alarm information receivers, real-time monitoring and rapid response capability for value-added service distribution are ensured. In addition, the scheme can introduce a configuration center to realize dynamic configuration of early warning strategies and realize non-stop service update of early warning strategies.

[0073] For example, as shown in Figure 4 Figure 4 is a method flow diagram for monitoring abnormal distribution of value-added services in all-weather according to the early warning rules, which includes the following steps:

[0074] Step 1: Different requesters call the prize drawing interface opened by the application system, and the request message contains the user ID of the requester, and the message needs to be encrypted. The user ID is used to identify the number of winning times within a period of time.

[0075] Step 2: The message interceptor processes the original message, decrypts the message, and authenticates the request.

[0076] Step 3: The authenticated request enters the product distribution stage, and the system checks whether the request meets the product distribution conditions. If the distribution conditions are not met, the process is directly ended; if the conditions are met, the next step is continued.

[0077] Step 4: The system checks the request for channel / province / threshold control. For example, the recorded winning times are compared with the set threshold to determine whether the early warning mechanism is triggered. If other control conditions are not met, the process is also ended; if the conditions are met, the early warning information is recorded, and the do-not-disturb mechanism is prepared for judgment.

[0078] Step 5: The system checks whether the request meets the do-not-disturb condition. If the do-not-disturb condition is met, the process is ended.

[0079] Step 6: Once the early warning is triggered, the system automatically generates early warning information, including user ID, winning times, trigger time, and other key data, and prepares to send to the corresponding operation and management personnel.

[0080] The monitoring method for abnormal distribution of value-added services proposed in the present disclosure can flexibly configure early warning rules, continuously monitor the mechanism, automatically trigger and record the process, and integrate the notification function of instant messaging tools. These features together ensure real-time monitoring and rapid response to abnormal distribution of value-added services, greatly improving the efficiency and accuracy of problem troubleshooting, reducing operating costs, and effectively preventing potential business risks. ​

[0081] Figure 5 FIG. 1 is a structural schematic diagram of a monitoring device for abnormal distribution of value-added services according to an embodiment of the present disclosure.

[0082] As shown in Figure 5 FIG. 1, the monitoring device 50 for abnormal distribution of value-added services comprises:

[0083] The acquisition module 501 is configured to acquire request information of a target user for a target value-added service, and generate a target user portrait of the target user according to the request information.

[0084] The first determination module 502 is configured to determine a first matching result of the target user portrait and a preset portrait library.

[0085] The second determination module 503 is configured to determine a service request attribute of the target user when the first matching result indicates that there is no abnormal user portrait similar to the target user portrait in the preset portrait library.

[0086] The third determination module 504 is configured to determine a second matching result of the service request attribute and a preset early warning rule.

[0087] The generation module 505 is configured to generate early warning information of abnormal distribution of value-added services according to the second matching result.

[0088] It should be noted that the foregoing explanation and description of the monitoring method for abnormal distribution of value-added services also apply to the monitoring device for abnormal distribution of value-added services of the present embodiment, which will not be described here again.

[0089] In the present embodiment, the request information of the target user for the target value-added service is acquired, and the target user portrait of the target user is generated according to the request information. The first matching result of the target user portrait and the preset portrait library is determined. The service request attribute of the target user is determined when the first matching result indicates that there is no abnormal user portrait similar to the target user portrait in the preset portrait library. The second matching result of the service request attribute and the preset early warning rule is determined. The early warning information of abnormal distribution of value-added services is generated according to the second matching result. Thus, the automatic monitoring and early warning of abnormal distribution of value-added services can be realized, thereby effectively improving the timeliness and accuracy of processing abnormal distribution of value-added services.

[0090] Figure 6 FIG. 2 shows a block diagram of an exemplary computer device suitable for implementing embodiments of the present disclosure. Figure 6 The computer device 12 shown is merely an example and should not impose any limitation on the functions and use range of the embodiments of the present disclosure.

[0091] As shown in Figure 6As shown, the computer device 12 is in the form of a general-purpose computing device. The components of the computer device 12 can include, but are not limited to, one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 to the processing unit 16.

[0092] The bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration bus (e.g., an Accelerated Graphics Port, or AGP bus) and a local bus using any of a variety of bus architectures (e.g., Industrial Standard Architecture (ISA), Micro Channel Architecture (MCA), Enhanced ISA (EISA), Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus).

[0093] The computer device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by the computer device 12 and includes both volatile and non- volatile media, removable and non-removable media.

[0094] The memory 28 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The computer device 12 can further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, a storage system 34 can be provided for reading from and writing to non-removable, non-volatile magnetic media (e.g., a "hard drive"). Figure 6 Not shown is a removable / non-removable, volatile / non-volatile computer system readable medium such as a program cartridge or diskette, a tape, etc. It is appreciated that the storage system 34 can include other similar

[0095] Although Figure 6A disk drive, a floppy disk drive, a CD-ROM drive, a DVD-ROM drive, or other removable media drive, can be provided, as shown in FIG. 1, for reading from and writing to a removable n on-volatile magnetic media (e.g., a "floppy disk"), and to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media). In such cases, each will include a drive mechanism and optical or other storage media interface for accessing data media with the bus 18. The storage 28 can include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the disclosure.

[0096] The program / utility 40, having a set (at least one) of program modules 42, can be stored in memory 28 by way of example, and not limitation, as well as an operating system, one or more application programs, other program modules, and program data, each or some combination thereof, can include implementation of a network environment. The program modules 42 generally carry out the functions and / or methodologies of embodiments of the disclosure as described herein.

[0097] The computer device 12 can also communicate with one or more external devices 14 such as a keyboard, a pointing device, a display 24, etc.; one or more devices that enable a human user to interact with the computer device 12; and / or one or more devices that enable the computer device 12 to communicate with one or more other computer devices. Such communication can be via the input / output (I / O) interface(s) 22. Furthermore, the computer device 12 can communicate with one or more networks (such as a Local Area Network (LAN), a Wide Area Network (WAN), and / or the public networks, such as the Internet) through a network adapter 20. As shown, the network adapter 20 communicates with the other components of the computer device 12 through the bus 18. It should be appreciated that, although not shown, other hardware and / or software modules could be used in conjunction with the computer device 12. Such can include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc.

[0098] The processing unit 16 performs various function applications and data processing by running programs stored in the system memory 28, such as implementing the monitoring method of the abnormal distribution of value-added services mentioned in the foregoing embodiments.

[0099] To achieve the above-mentioned embodiments, the present disclosure further proposes a non-transitory computer-readable storage medium having stored thereon a computer program, which, when executed by a processor, implements the monitoring method for abnormal distribution of value-added services as proposed in the foregoing embodiments of the present disclosure.

[0100] To achieve the above-mentioned embodiments, the present disclosure further proposes a computer program product, which, when executed by a processor, executes the monitoring method for abnormal distribution of value-added services as proposed in the foregoing embodiments of the present disclosure.

[0101] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in the present disclosure comply with relevant laws and regulations and do not violate public order and good customs.

[0102] It should be noted that the personal information from the user should be collected for legal and reasonable purposes, and should not be shared or sold outside these legal uses. In addition, such collection / sharing should be carried out after the user's informed consent is received, including but not limited to informing the user to read the user agreement / user notice before the user uses the function, and signing the agreement / authorization including authorization of relevant user information. In addition, any necessary steps should be taken to protect and secure access to such personal information data and ensure that other people with access to personal information data comply with their privacy policies and processes.

[0103] The present disclosure contemplates that user-selectable options for allowing or disabling access to or use of personal information data can be provided to the user. In addition, the present disclosure contemplates that user-selectable options can be provided to the user that specifically express the user's preferences about the use of personal information data. For example, a user-selectable option can be provided to the user that states "do not allow any third-party access to my personal information data" or "allow third-party access to some of my personal information data but not all of it."

[0104] In the foregoing embodiment description, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any suitable manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0105] Moreover, the terms "first", "second", "third", etc. are used herein only to describe different steps or categories of steps in a claim for patent purposes, and are not to be construed as implying or implying relative importance or a number of indicated technical features. Thus, features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise explicitly specified.

[0106] Any process or method descriptions or descriptions of the flow diagrams described herein, or otherwise described herein, can be understood as representing the modules, segments, or portions of code that include executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the present disclosure includes additional implementations in which the functions described are performed in different orders, including substantially simultaneously, or in reverse order, as will be understood by those skilled in the art of the embodiments of the present disclosure.

[0107] The logic and / or steps represented in the flow diagrams or otherwise described herein, for example, can be considered as a list of executable instructions for implementing the logic function, which can be specifically embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus or device, such as a computer-based system, a system including a processor, or other system that can take instructions from an instruction execution system, apparatus or device and execute them. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate or transport a program for use by or in connection with an instruction execution system, apparatus or device, or in conjunction with these instruction execution systems, apparatus or devices. More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connections having one or more wires (electronic devices), portable computer diskette (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disc read-only memory (CDROM). In addition, a computer-readable medium can even be paper or other suitable medium on which the program can be printed, as the program can be electronically obtained, for example, by optical scanning of the paper or other medium, followed by electronic conversion, interpretation or processing, if necessary, in other suitable manner, and then stored in a computer memory.

[0108] It should be understood that portions of the present disclosure can be realized with hardware, software, firmware or a combination thereof. In the above embodiments, a plurality of steps or methods can be realized with software or firmware stored in a memory and executed by a suitable instruction execution system. As such, if realized with hardware and in another embodiment, any one or a combination of the following technologies known in the art can be used: discrete logic circuit with logic gate circuit for implementing logic functions on data signals, application specific integrated circuit with suitable combination logic gate circuit, programmable gate array (PGA), field programmable gate array (FPGA), etc.

[0109] Those skilled in the art of the present technology can understand that all or part of the steps carried out by the above-mentioned embodiment method can be completed by a program instructing the relevant hardware, and the program can be stored in a computer readable storage medium. When the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

[0110] In addition, each functional unit in each embodiment of the present disclosure can be integrated into one processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above-mentioned integrated module can be realized in the form of hardware or in the form of a software functional module. When the integrated module is realized in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer readable storage medium.

[0111] The above-mentioned storage medium can be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present disclosure have been shown and described above, it should be understood that the above-mentioned embodiments are exemplary and cannot be understood as limiting the present disclosure, and those skilled in the art can make changes, modifications, replacements and variations to the above-mentioned embodiments within the scope of the present disclosure.

Claims

1. A method for monitoring abnormal allocation of value-added services, characterized in that, include: Obtain the target user's request information for the target value-added service, and generate the target user's target user profile based on the request information; Determine the first matching result between the target user's portrait and the preset portrait library; When the first matching result indicates that there is no abnormal user portrait similar to the target user portrait in the preset portrait library, the service request attribute of the target user is determined. Determine the second matching result between the service request attributes and the preset early warning rules; Based on the second matching result, an early warning message for abnormal allocation of value-added services is generated.

2. The method as described in claim 1, characterized in that, The preset portrait library is constructed based on the following method: Identify users who made unusual requests for the target value-added service; Generate an abnormal user profile corresponding to each of the abnormal requesting users; Based on multiple abnormal user portraits, the preset portrait library is constructed.

3. The method as described in claim 1, characterized in that, The service request attributes include: Total number of service requests; Service request channels; Service request location.

4. The method as described in claim 3, characterized in that, The preset early warning rules include: preset frequency thresholds, a list of control channels, and a list of control locations; The determination of the second matching result between the service request attribute and the preset early warning rule includes: Determine a third matching result between the cumulative number of service requests and a preset threshold number; Determine the fourth matching result between the service request channel and the list of control channels; Determine the fifth matching result between the service request location and the list of controlled locations; The third matching result, the fourth matching result, and the fifth matching result are combined to form the second matching result.

5. The method as described in claim 4, characterized in that, The step of generating an early warning message for abnormal allocation of value-added services based on the second matching result includes at least one of the following: The warning message is generated when the third matching result indicates that the cumulative number of service requests exceeds the preset threshold. The warning information is generated when the fourth matching result indicates that the service request channel belongs to the list of controlled channels; The warning information is generated when the fifth matching result indicates that the service request location belongs to the list of controlled locations.

6. The method as described in claim 1, characterized in that, The method further includes: Determine the statistical value of the warning information corresponding to the target user, wherein the warning information is used to indicate the cumulative number of warning messages generated for the target user; When the statistical value reaches the preset warning threshold, the warning information is sent to the warning information recipient.

7. A monitoring device for abnormal allocation of value-added services, characterized in that, include: The acquisition module is used to acquire the target user's request information for the target value-added service, and generate the target user's target user portrait based on the request information; The first determining module is used to determine the first matching result between the target user's portrait and the preset portrait library; The second determining module is used to determine the service request attribute of the target user when the first matching result indicates that there is no abnormal user portrait similar to the target user portrait in the preset portrait library; The third determining module is used to determine the second matching result between the service request attributes and the preset early warning rules; The generation module is used to generate early warning information for abnormal allocation of value-added services based on the second matching result.

8. A computer device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, in, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the steps of the method according to any one of claims 1-6.

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