Information sending method, device and equipment based on multi-level area terminal and medium

Abstract

The embodiment of the invention discloses an information sending method and device based on a multi-level area terminal, equipment and a medium. A specific embodiment of the method comprises the following steps: in response to a received product value issuing request, obtaining a user information set, a product use level information set, a product generation value information set, a user team information set and a product use anomaly detection information set from a storage module; determining a product value information set corresponding to the user information set by using a calculation module; using a sending module to send the product value encryption information set to an upper-level area terminal; in response to determining that the auditing information characterizes correct, for each piece of user information, executing a sending step: generating value packaging information; and sending the value packaging information to a user terminal by using a sending module. According to the embodiment, the product value issuing related information can be accurately and efficiently encrypted and sent to the corresponding user based on interaction among the multi-level area terminals.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to a method, device, electronic device, and computer-readable medium for sending information based on a multi-level regional terminal. Background Art

[0002] At present, with the increasing popularity of various value products, value products are increasingly used in people's daily lives. For the transmission of product value information corresponding to value products, the method usually adopted is: relevant personnel use a pre-set calculation script to determine the product value information set corresponding to each user in the area, and then send the product value information set directly to the terminal corresponding to each user.

[0003] However, when the above method is adopted, the following technical problems often occur:

[0004] When there are a large number of users in a region, the calculation time corresponding to the calculation script is relatively long, and the calculation script cannot effectively ensure the accuracy of product value information and information leakage, and often lacks the relevant steps to implement the audit through terminal interaction between multiple levels.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the invention

[0006] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0007] Some embodiments of the present disclosure propose a method, device, electronic device and computer-readable medium for sending information based on a multi-level regional terminal to solve one or more of the technical problems mentioned in the above background technology section.

[0008] In a first aspect, some embodiments of the present disclosure provide an information sending method based on a multi-level regional terminal, comprising: in response to receiving a product value issuance request corresponding to a target area, obtaining a user information set corresponding to the target area from a storage module, wherein there is a corresponding regional terminal for the target area, and the regional terminal comprises: a calculation module, a storage module and a sending module; obtaining a product usage level information set, a product generation value information set, a user team information set and a product usage anomaly detection information set corresponding to the user information set from the storage module; using the calculation module to determine the product value information set corresponding to the user information set according to the product usage level information set, the product generation value information set, the user team information set and the product usage anomaly detection information set; using the sending module Module, sends the encrypted product value information set corresponding to the above product value information set to the upper-level regional terminal corresponding to the above target area, wherein the above upper-level regional terminal includes the terminal backup data corresponding to each lower-level regional terminal; in response to determining that the audit information representation sent by the above upper-level regional terminal is correct, for each user information in the above user information set, executes a sending step: packages the product usage level information, product generation value information, user team information, the above user information and product value issuance rule information corresponding to the above user information to generate value packaging information; uses the above sending module to send the above value packaging information to the user terminal in a sending mode determined by the user corresponding to the above user information, wherein the above sending mode is one of the following: encrypted SMS link mode, encrypted email mode.

[0009] In a second aspect, some embodiments of the present disclosure provide an information sending device based on a multi-level regional terminal, comprising: a first acquisition unit, configured to, in response to receiving a product value issuance request corresponding to a target area, acquire a user information set corresponding to the target area from a storage module, wherein the target area has a corresponding regional terminal, and the regional terminal comprises: a calculation module, a storage module and a sending module; a second acquisition unit, configured to acquire a product usage level information set, a product generation value information set, a user team information set and a product usage anomaly detection information set corresponding to the user information set from the storage module; a determination unit, configured to determine a product value information set corresponding to the user information set by using the calculation module according to the product usage level information set, the product generation value information set, the user team information set and the product usage anomaly detection information set; The sending unit is configured to use the above-mentioned sending module to send the product value encrypted information set corresponding to the above-mentioned product value information set to the upper-level regional terminal corresponding to the above-mentioned target area, wherein the above-mentioned upper-level regional terminal includes each terminal backup data corresponding to each lower-level regional terminal; the execution unit is configured to respond to determining that the audit information representation sent by the above-mentioned upper-level regional terminal is correct, and for each user information in the above-mentioned user information set, execute a sending step: package the product usage level information, product generation value information, user team information, the above-mentioned user information and product value issuance rule information corresponding to the above-mentioned user information to generate value package information; use the above-mentioned sending module to send the above-mentioned value package information to the user terminal in a sending method determined by the user corresponding to the above-mentioned user information, wherein the above-mentioned sending method is one of the following: encrypted SMS link method, encrypted email method.

[0010] In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner in the first aspect.

[0011] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner in the first aspect is implemented.

[0012] The above-mentioned embodiments of the present disclosure have the following beneficial effects: through the information sending method based on multi-level regional terminals of some embodiments of the present disclosure, based on the interaction between multi-level regional terminals, the product value issuance related information can be accurately and efficiently encrypted and sent to the corresponding user. Specifically, the reason why the relevant information related to the issuance of sub-product values ​​is not accurate and efficient is that when there are a large number of users in the region, the corresponding calculation time of the calculation script is relatively long, and the calculation script cannot effectively guarantee the information leakage of product value information and the accuracy of product value information, and often lacks the relevant steps of realizing the audit through the terminal interaction between multiple levels. Based on this, the information sending method based on multi-level regional terminals of some embodiments of the present disclosure, first, in response to receiving the product value issuance request corresponding to the target area, obtain the user information set corresponding to the above target area from the storage module, wherein the above target area has a corresponding regional terminal, and the above regional terminal includes: a calculation module, a storage module and a sending module. Here, through the calculation module, the storage module and the sending module included in the regional terminal, the terminal functions can be distinguished, so as to ensure that the regional terminal can efficiently and accurately realize the generation of subsequent product value information through the coordination between the modules. Then, the product usage level information set, product generation value information set, user team information set and product usage anomaly detection information set corresponding to the above user information set are obtained from the above storage module, so as to facilitate the subsequent accurate generation of product value information. Then, using the above calculation module, according to the above product usage level information set, the above product generation value information set, the above user team information set and the above product usage anomaly detection information set, the product value information set corresponding to the above user information set can be accurately determined. Then, using the above sending module, the product value encrypted information set corresponding to the above product value information set is sent to the upper-level regional terminal corresponding to the above target area, wherein the upper-level regional terminal includes each terminal backup data corresponding to each lower-level regional terminal. Here, through the setting of multi-level regional terminals, the generation of product value information and the review of product value information can be distinguished to avoid generation and review at the same terminal, which not only wastes too many computing resources, but also may cause the information to not be accurately and objectively reviewed. In addition, through the setting of multi-level regional terminals, multi-level backup of terminal data can be guaranteed to reduce the storage pressure of low-level regional terminals, and also to ensure the information completeness of high-level regional terminals, so as to achieve more accurate review of product value information and generation of product usage anomaly detection information, and maintain the target products corresponding to each user.Finally, in response to determining that the audit information sent by the above-mentioned upper-level regional terminal is represented correctly, for each user information in the above-mentioned user information set, the sending step is performed: the first step is to package the product usage level information, product generation value information, user team information, the above-mentioned user information and product value distribution rule information corresponding to the above-mentioned user information to generate value packaging information. Here, after the upper-level regional terminal determines that the audit is correct, the packaging method is used to facilitate the subsequent sending to the user so that the user can see the complete product value distribution related information. The second step is to use the above-mentioned sending module to send the above-mentioned value packaging information to the user terminal in the sending method determined by the user corresponding to the above-mentioned user information, wherein the above-mentioned sending method is one of the following: encrypted SMS link method, encrypted email method. Here, based on the sending method selected by the user, during the sending process, the information security of the value packaging information is guaranteed by encryption to avoid information leakage. In summary, through the deployment of multi-level regional terminals, each process of the product value information can be executed in multiple modules in multiple terminals, ensuring the generation efficiency, accuracy and information security of the product value information. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0014] Figure 1 is a flowchart of some embodiments of the information sending method based on multi-level regional terminals according to the present disclosure;

[0015] Figure 2 is a schematic structural diagram of some embodiments of an information sending device based on a multi-level regional terminal according to the present disclosure;

[0016] Figure 3 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0017] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0018] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0019] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0020] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0021] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0022] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0023] refer to Figure 1 , shows a process 100 of some embodiments of the information sending method based on multi-level regional terminals according to the present disclosure. The information sending method based on multi-level regional terminals includes the following steps:

[0024] Step 101, in response to receiving a product value distribution request corresponding to a target area, obtaining a user information set corresponding to the target area from a storage module.

[0025] In some embodiments, in response to receiving a product value issuance request corresponding to a target area, the execution subject of the information transmission method based on the multi-level regional terminal (for example, a control system corresponding to the multi-level regional terminal) can obtain the user information set corresponding to the target area from the storage module. The target area can be an area to be processed for product value issuance. Product value issuance can be an operation of issuing product value to a user. In practice, for a credit investigation scenario, the corresponding product value issuance can be a recommendation fee for recommending a user to use a product. For example, if user A recommends a target product to user B, and user B makes a relevant value investment in the target product, the owner of the target product will pay the recommendation fee to user A. The product value issuance request can be a request to determine the product value issuance information corresponding to each user in the target area. The storage module can be a module for storing various product-related data. The user information in the user information set can be a user identifier corresponding to a user using the target product in the target area. The target area has a corresponding regional terminal, and the regional terminal includes: a calculation module, a storage module, and a sending module. The calculation module can be a module that supports various value calculations. The calculation module includes: a hardware calculation module and a software calculation module. The hardware computing module usually consists of a processor, memory, storage, power management, and circuit boards, etc., and requires an operating system such as Linux, WINCE, QNX, etc. to form a minimized computer system. For example, the Intel NUC Element computing module is a core board based on the X86 architecture designed by the target manufacturer, which is divided into two series: Element U and Element H. Element U uses a U series CPU, integrates onboard memory, and uses Intel's newly defined 300pin gold finger to connect to the IO board; while Element H uses an H series standard voltage CPU, has rich expansion capabilities, supports 16X PCIE, and is easy to expand high-performance independent graphics. The computing module usually consists of one or more classes, each of which is responsible for implementing a specific computing function. For example, a Java computing module can encapsulate a series of computing operations, accept input data, perform data verification and processing, perform specific computing operations (such as addition, subtraction, multiplication, division, logical operations, etc.), and finally return the calculation results. This modular design makes software development more flexible and efficient. The sending module can be a module that sends various data.

[0026] Step 102: Acquire, from the storage module, a product usage level information set, a product generation value information set, a user team information set, and a product usage anomaly detection information set corresponding to the user information set.

[0027] In some embodiments, the execution subject may obtain the product usage level information set, product generation value information set, user team information set and product usage anomaly detection information set corresponding to the user information set from the storage module. Among them, the product usage level information may be a characterization of the user value in the target product, and may also be a characterization of the length of time the user uses the target product. That is, the higher the corresponding product usage level information, the more value the corresponding user can add to the target product. Each user information has corresponding product usage level information, product generation value information, user team information and product usage anomaly detection information. The product generation value information may be the direct value value brought or generated by the user himself in the target product. The user team information may be the team information of the team to which the user belongs. For example, the user team information may be a team identification. The product usage anomaly detection information may be risk information that may exist when the user uses the target product. The product usage anomaly detection information may be information in numerical form. The higher the corresponding numerical value of the product usage anomaly detection information, the higher the corresponding risk level of the user using the target product.

[0028] Step 103, using the calculation module, according to the product usage level information set, the product generation value information set, the user team information set and the product usage anomaly detection information set, determine the product value information set corresponding to the user information set.

[0029] In some embodiments, the execution entity may utilize the calculation module to determine the product value information set corresponding to the user information set based on the product usage level information set, the product generation value information set, the user team information set, and the product usage anomaly detection information set. The product value information may be a product distribution value value.

[0030] In some optional implementations of some embodiments, the execution subject may utilize the calculation module to determine the product value information set corresponding to the user information set according to the product usage level information set, the product generation value information set, the user team information set, and the product usage anomaly detection information set, including the following steps:

[0031] For each piece of user information in the user information set, the following first generation step is performed using the calculation module:

[0032] Sub-step 1, according to the above-mentioned product usage level information, determine the product value issuance rule information corresponding to the above-mentioned user information. Among them, the product value issuance rule information can be a rule identifier for determining the issuance rule of the product value information. In practice, corresponding product value issuance rules are set according to different product usage level information. For example, for the product usage level information of product usage level A, the corresponding product value issuance rule is rule A. For the product usage level information of product usage level B, the corresponding product value issuance rule is rule B.

[0033] Sub-step 2: Determine the basic product value information corresponding to the user information according to the product value distribution rule information and the product generation value information. The basic product value information may be the product reward value issued by the target product to the user's own product work.

[0034] As an example, first, the execution entity may determine the value commission ratio corresponding to the product generation value information according to the rule calculation method corresponding to the product value distribution rule information, and then multiply the value commission ratio and the product generation value information to generate the basic product value information.

[0035] Sub-step 3, determining the online user information set and offline user information set corresponding to the above user team information. The online user information may be the online user of the user corresponding to the user information. The online user may be the superior user who leads the user corresponding to the user information to process and operate various aspects of the product value. The offline user may be the user who is led by the user corresponding to the user information to process and operate various aspects of the product value.

[0036] Sub-step 4, based on the online user information set, the offline user information set and the product usage anomaly detection information set, using the product value distribution rule information, determine the team value change information. The team value change information can be the value reward value brought by the team to the user.

[0037] Sub-step 5: generating the above-mentioned product value information according to the above-mentioned basic product value information and the above-mentioned team value change information.

[0038] As an example, the execution entity may add the basic product value information and the team value change information to generate product value information.

[0039] In some optional implementations of some embodiments, the execution subject may determine the team value change information based on the online user information set, the offline user information set, and the product usage anomaly detection information set, using the product value distribution rule information, including the following steps:

[0040] In the first step, for each online user information in the online user information set, according to the value information corresponding to the online user information, the team value deduction information corresponding to the online user information is determined by using the product value distribution rule information. The team value deduction information may be the deduction value of the team value deduction caused by the user distributing the value to the online user. The team value deduction information may be a negative value.

[0041] As an example, the execution entity can filter out the product value distribution sub-rule that should be rewarded under the value information corresponding to the online user information from the product value distribution rule information. Then, the team value deduction information is determined based on the product value distribution sub-rule and the corresponding value reward generated by the user.

[0042] In the second step, for each offline user information in the offline user information set, the following second generation step is performed:

[0043] Sub-step 1: According to the value information corresponding to the offline user information, the initial team value increase information corresponding to the offline user information is determined by using the product value distribution rule information. The team value increase information may be the value increase value caused by sending the team value brought by the offline user to the user. The initial team value increase information may be an integer value.

[0044] As an example, the execution entity can filter out the product value distribution sub-rule that should be rewarded under the value information corresponding to the user information from the product value distribution rule information. Then, the team value increase information is determined based on the product value distribution sub-rule and the corresponding value reward generated by the offline user.

[0045] Sub-step 2, obtaining the product usage anomaly detection information corresponding to the offline user information, wherein the product usage anomaly detection information corresponding to each offline user information in the offline user information set is predetermined based on the funnel detection model of the risk control link. The product usage anomaly detection information can be the size of the anomaly when the lower limit user uses the product.

[0046] Sub-step 3: generating team value increase information based on the above product usage anomaly detection information and the above initial team value increase information.

[0047] As an example, the execution entity may normalize the product usage anomaly detection information to generate a normalized value, and then multiply the product usage anomaly detection information and the initial team value increase information to generate team value increase information.

[0048] The third step is to add the obtained team value deduction information set and the obtained team value increase information set to generate team value change information.

[0049] In some optional implementations of some embodiments, the execution subject may use the calculation module to determine the product value information set corresponding to the user information set according to the product usage level information set, the product generation value information set and the user team information set, including the following steps:

[0050] The first step is to use the large model calling interface to call the large language model from the above-mentioned computing module.

[0051] The second step is to generate value generation prompt information representing the product value information set generated according to the product usage level information set, the product generation value information set and the user team information set, wherein the value generation prompt information can be a prompt word for generating the product value information.

[0052] The third step is to send the value generation prompt information to the large language model to generate a product value information set corresponding to the user information set.

[0053] Step 104: using the sending module, send the encrypted product value information set corresponding to the product value information set to the upper-level regional terminal corresponding to the target region.

[0054] In some embodiments, the execution subject may use the sending module to send the encrypted product value information set corresponding to the product value information set to the upper-level regional terminal corresponding to the target region, wherein the upper-level regional terminal includes each terminal backup data corresponding to each lower-level regional terminal.

[0055] Step 105, in response to determining that the verification information sent by the upper-level regional terminal is correct, for each user information in the user information set, a sending step is performed:

[0056] Step 1051, packaging the product usage level information, product value generation information, user team information, the user information and product value distribution rule information corresponding to the above user information to generate value packaging information.

[0057] In some embodiments, the above-mentioned execution entity may package the product usage level information, product value generation information, user team information, the above-mentioned user information and product value distribution rule information corresponding to the above-mentioned user information to generate value packaging information.

[0058] Step 1052: utilizing the sending module to send the value package information to the user terminal in a sending mode determined by the user corresponding to the user information.

[0059] In some embodiments, the execution subject may use the sending module to send the value package information to the user terminal in the sending method determined by the user corresponding to the user information. The sending method is one of the following: an encrypted SMS link method and an encrypted email method. The encrypted SMS link method may be a method of sending an encrypted link in the form of a SMS. The encrypted email method may be a method of sending an encrypted link in the form of an email.

[0060] In some optional implementations of some embodiments, after step 105, the steps further include:

[0061] In the first step, in response to determining that the audit information representation sent by the upper-level regional terminal is correct, the obtained value package information set is stored in the storage module, and the storage time of the value package information set is set in the storage module. When the storage time of the value package information set in the storage module reaches the storage time, the value package information set in the storage module will be deleted.

[0062] The second step is to use the sending module to send the value package information set to the upper level regional terminal.

[0063] The above-mentioned upper-level regional terminal performs the following processing steps on the above-mentioned value packaging information set:

[0064] Sub-step 1, obtaining the value audit record corresponding to the above value package information set, wherein the value audit record may be the process record information of the entire audit process of the upper-level regional terminal auditing whether the value package information set is correct.

[0065] Sub-step 2: storing the value packaging information set, the value audit record and the area information corresponding to the target area into the storage module included in the upper-level area terminal.

[0066] In some optional implementations of some embodiments, after step 105, the steps further include:

[0067] Periodically receiving the product usage anomaly detection information set for the user information set sent by the upper level regional terminal, wherein the periodic time can be set by relevant technical personnel based on actual experience.

[0068] And the product usage anomaly detection information set corresponding to the offline user information set in the upper-level regional terminal is generated by the following steps:

[0069] Sub-step 1, from the target user information set in the above-mentioned storage module, filter out the target user information whose corresponding user abnormality label is the target abnormality label, and obtain at least one abnormal user information. Among them, the target abnormality label can represent a label with abnormal value use. For example, the target abnormality label can be "1" or "0". The target user information set can be a user information set registered in at least one value transfer application. In practice, for the credit investigation scenario, the value transfer application can be an application related to the credit investigation business. For example, the value transfer application can be a target bank application. The user information can be relevant information of the user. For example, the user information can be a user identifier. There is a one-to-one correspondence between the historical value product call data sequence in the historical value product call data sequence set and the target user information in the target user information set. The historical value product call data sequence can be the value product call data sequence corresponding to the user in the historical time period. The value product call data can be the data of calling the value product. For example, the value product call data can include but is not limited to at least one of the following: the number of calls of the value product, the call time of the value product, the call method of the value product, the value borrowing value of the value product, the value return value of the value product, the value borrowing time of the value product, and the value return time of the value product. Among them, the target abnormal label can be a high abnormal label. The user abnormal label can be information that characterizes the abnormal degree of value corresponding to the user. For example, the user abnormal label can be but is not limited to at least one of the following: a low abnormal label, a medium abnormal label, and a high abnormal label. Abnormal user information can be user information of users with high abnormal value. The abnormal degree of value can be the abnormal degree of value flow. A low abnormal label can characterize that the user's value flow is abnormally low. A medium abnormal label can characterize that the user's value flow is moderately abnormal. A high abnormal label can characterize that the user's value flow is abnormally high. In practice, for credit investigation scenarios, value flow can be but is not limited to at least one of the following: loan, repayment, and transfer.

[0070] Sub-step 2: Generate at least one target abnormality indicator based on at least one historical value product call data sequence corresponding to the at least one abnormal user information. The at least one target abnormality indicator may be at least one indicator for determining the abnormality of the corresponding value of the user. For example, the at least one target abnormality indicator may include but is not limited to at least one of the following: number of borrowings, change in number of loans, change in number of repayments, and overdue status.

[0071] Sub-step 3: Generate a first risk control link funnel detection model for historical call data based on the above-mentioned at least one target abnormal indicator. The first risk control link funnel detection model can be a model generated based on historical call data, which characterizes the funnel-shaped risk control detection of each link. The first risk control link funnel detection model can include: various indicator detection rules.

[0072] As an example, the execution subject may sequentially sort each target abnormal indicator in at least one target abnormal indicator according to the number of indicators corresponding to each target abnormal indicator to obtain a target abnormal indicator sequence. Then, an indicator detection rule corresponding to each target abnormal indicator in the target abnormal indicator sequence is generated to obtain an indicator detection rule sequence. Finally, the indicator detection rule sequence is determined as the vulnerability detection model of the first risk control link.

[0073] Sub-step 4, according to the funnel detection model of the first risk control link, perform user anomaly detection on the offline user information set to obtain the first user anomaly detection information set. The offline user information set is a user information subset after removing the at least one abnormal user information from the target user information set. There is a one-to-one correspondence between the first user anomaly detection information in the first user anomaly detection information set and the offline user information in the offline user information set. The first user anomaly detection information can be anomaly detection information in numerical form or anomaly detection information in label form. The higher the numerical value, the greater the anomaly of the corresponding user. The first user anomaly detection information can characterize the value anomaly level corresponding to the user.

[0074] As an example, the above-mentioned execution entity can use the funnel detection model of the first risk control link as the anomaly detection model, perform user anomaly detection on the offline user information set, and obtain the first user anomaly detection information set.

[0075] Sub-step 5, for each offline user information in the offline user information set, determine the team anomaly detection information corresponding to the offline user information according to the user team information corresponding to the offline user information. The team anomaly detection information may be detection information that the team corresponding to the offline user has an anomaly. In practice, the team anomaly detection information may be information of a numerical type. The larger the corresponding numerical value, the greater the probability of representing a team anomaly.

[0076] As an example, the execution subject may determine the team anomaly detection information based on the team value value change information, wherein the team value value change information may represent the value change of the overall total value corresponding to the entire team.

[0077] Sub-step 6: generating a product usage anomaly detection information set for the offline user information set based on the first user anomaly detection information set and the team anomaly detection information set.

[0078] As an example, the execution entity may perform corresponding weighted sum processing on the first user anomaly detection information set and the team anomaly detection information set to generate a product usage anomaly detection information set for the offline user information set.

[0079] In some optional implementations of some embodiments, the execution entity may generate a product usage anomaly detection information set for the offline user information set according to the first user anomaly detection information set and the team anomaly detection information set, including the following steps:

[0080] The first step is to obtain the future abnormal indicator prediction model corresponding to each target abnormal indicator in the above-mentioned at least one target abnormal indicator from the above-mentioned target terminal, and obtain at least one future abnormal indicator prediction model. Among them, the future abnormal indicator prediction model can be a neural network model that predicts the future abnormal prediction information of the corresponding target abnormal indicator. In practice, the future abnormal indicator prediction model can be a recurrent neural network model. The future abnormal indicator prediction model can be a pre-trained model. The specific training method will not be repeated. Among them, the above-mentioned at least one future abnormal indicator prediction model is obtained by terminal retrieval based on the target terminal.

[0081] The second step is to generate a second risk control link funnel detection model for the at least one future abnormal indicator prediction model. The second risk control link funnel detection model can be a model generated based on future data, representing the funnel-shaped risk control detection of each link.

[0082] As an example, the above-mentioned execution entity can combine at least one future abnormal indicator prediction model according to the indicator number corresponding to each target abnormal indicator to generate a funnel detection model for the second risk control link.

[0083] The third step is to perform user anomaly detection on the offline user information set according to the funnel detection model of the second risk control link to obtain a second user anomaly detection information set. Among them, the second user anomaly detection information in the second user anomaly detection information set has a one-to-one correspondence with the offline user information in the offline user information set. The second user anomaly detection information can represent the value anomaly level of the corresponding user.

[0084] As an example, the above-mentioned execution entity can use the funnel detection model of the second risk control link as the anomaly detection model, perform user anomaly detection on the offline user information set, and obtain the second user anomaly detection information set.

[0085] The fourth step is to obtain a current value product call data set for the target user information set, wherein the current value product call data may be the value product call data corresponding to the target user information at the current time.

[0086] The fifth step is to filter out characteristic information related to the at least one target abnormal indicator from the current value product call data set to obtain a filtered call data set.

[0087] The sixth step is to call the computing resources corresponding to the current graphics processor, perform clustering processing on the filtered calling data set, and obtain a first user information cluster.

[0088] Step 7: Call the computing resources corresponding to the current graphics processor to perform clustering processing on the current value product call data set to obtain the second user information cluster. As an example, the execution subject can use the K-means algorithm to perform clustering processing on the current value product call data set to obtain the second user information cluster. Among them, each user information in the second user information cluster has at least one common feature. For example, the at least one feature includes but is not limited to at least one of the following: user region feature, user indicator information, user portrait feature.

[0089] Step 8: For each offline user information in the offline user information set, the computing resource corresponding to the current central processor is called to execute the following first generation step:

[0090] Sub-step 1: determining the first user information cluster in the first user information cluster set corresponding to the offline user information as the first target user information cluster.

[0091] Sub-step 2: determining the first user information quantity of abnormal user information included in the first target user information cluster.

[0092] Sub-step 3: determining a first ratio between the number of the first user information and the number of the first user information clusters, wherein the number of the first user information clusters is the number of user information corresponding to the first target user information cluster.

[0093] Sub-step 4: determining the second user information cluster in the second user information cluster set corresponding to the offline user information as the second target user information cluster.

[0094] Sub-step 5: determining the number of second user information of abnormal user information included in the second target user information cluster.

[0095] Sub-step 6, in response to determining a second ratio between the second user information number and the second user information cluster number, wherein the second user information cluster number is the user information number corresponding to the second target user information cluster.

[0096] Sub-step 7: generating the third user abnormality detection information according to the first ratio and the second ratio.

[0097] As an example, the execution entity may add the first ratio and the second ratio to generate an added value as the third user abnormality detection information.

[0098] The tenth step is to generate the product usage anomaly detection information set based on the first user anomaly detection information set, the second user anomaly detection information set, the obtained third user anomaly detection information set and the team anomaly detection information set.

[0099] As an example, the above-mentioned execution entity can generate the above-mentioned product usage anomaly detection information set by weighted summation based on the above-mentioned first user anomaly detection information set, the above-mentioned second user anomaly detection information set, the obtained third user anomaly detection information set and the above-mentioned team anomaly detection information set.

[0100] Optionally, the generating the third user abnormality detection information according to the first ratio and the second ratio may include the following steps:

[0101] The first step is to set the indicator importance value corresponding to the at least one target abnormal indicator as a preset value. For example, the preset value may be a value of "1". The indicator importance value may represent the degree of influence of at least one target abnormal indicator on the value risk control abnormality detection.

[0102] The second step is to generate the important value of the indicator corresponding to the indicator set corresponding to the current value product calling data set as the target indicator important value. The above indicator set includes: at least one target abnormality indicator. The indicator set can be each indicator involved in the current value product calling data set. The target indicator important value can represent the corresponding indicator in the indicator set, representing the degree of influence on the value risk control abnormality detection. The larger the target indicator important value, the greater the corresponding degree of influence on the value risk control abnormality detection.

[0103] As an example, the above-mentioned execution entity can use the self-attention mechanism to generate the important value of the indicator corresponding to the indicator set corresponding to the above-mentioned current value product call data set as the important value of the target indicator.

[0104] The third step is to use the above-mentioned preset value as the ratio weight corresponding to the above-mentioned first ratio, and the above-mentioned target indicator important value as the ratio weight of the above-mentioned second ratio, perform weighted processing on the above-mentioned first ratio and the above-mentioned second ratio, and generate third user anomaly detection information.

[0105] Optionally, generating the product usage anomaly detection information set according to the first user anomaly detection information set, the second user anomaly detection information set, the obtained third user anomaly detection information set and the team anomaly detection information set may include the following steps:

[0106] For each first user anomaly detection information in the first user anomaly detection information set, the following third generation step is performed:

[0107] Sub-step 1, determining the second user anomaly detection information in the second user anomaly detection information set corresponding to the first user anomaly detection information as the second target user anomaly detection information, and determining the third user anomaly detection information in the third user anomaly detection information set corresponding to the first user anomaly detection information as the third target user anomaly detection information, and determining the team anomaly detection information in the team anomaly detection information set corresponding to the first user anomaly detection information as the target team anomaly detection information.

[0108] Sub-step 2, determine the risk control detection weight information set, wherein the above-mentioned risk control detection weight information set includes: the risk control detection weight information corresponding to the above-mentioned first user anomaly detection information set, the risk control detection weight information corresponding to the above-mentioned second user anomaly detection information set, the risk control detection weight information corresponding to the above-mentioned third user anomaly detection information set, and the risk control detection weight information corresponding to the team anomaly detection information. Among them, the risk control detection weight information set can characterize the importance corresponding to the first user anomaly detection information set, the importance corresponding to the second user anomaly detection information set, the importance corresponding to the third user anomaly detection information set, and the importance corresponding to the team anomaly detection information. Among them, the anomaly detection weight information set can also indirectly characterize the importance of historical data, the importance of current data, and the importance of future data. In practice, the anomaly detection weight information set can be various pre-set weight values.

[0109] Sub-step 3, based on the above-mentioned risk control detection weight information set, the above-mentioned first user anomaly detection information, the above-mentioned second target user anomaly detection information, the above-mentioned third target user anomaly detection information and the target team anomaly detection information are fused to generate fused anomaly detection information as the initial product use anomaly detection information.

[0110] As an example, the above-mentioned execution entity performs weighted summation processing on the above-mentioned first user anomaly detection information, the above-mentioned second target user anomaly detection information, the above-mentioned third target user anomaly detection information and the target team anomaly detection information according to the above-mentioned risk control detection weight information set to generate initial product usage anomaly detection information.

[0111] As another example, the above-mentioned execution entity can perform label information fusion on the above-mentioned first user anomaly detection information, the above-mentioned second target user anomaly detection information, the above-mentioned third target user anomaly detection information and the target team anomaly detection information according to the above-mentioned risk control detection weight information set to generate initial product usage anomaly detection information.

[0112] Optionally, the generating of the product usage anomaly detection information set for the offline user information set according to the first user anomaly detection information set and the team anomaly detection information set may include the following steps:

[0113] The first step is to determine the indicator important information corresponding to each target abnormal indicator in the above-mentioned at least one target abnormal indicator, and obtain at least one indicator important information. Among them, the information corresponding to the above-mentioned at least one indicator important information is integrated into a preset value. Among them, the indicator important information can characterize the importance of the target abnormal indicator. The indicator important information can be a value between 0 and 1. At least one indicator important information can be preset manually or generated by a self-attention mechanism. The information integration can be after the value corresponding to the at least one indicator important information. The preset value can be the value "1".

[0114] The second step is to obtain an indicator combination information set for at least one of the above target abnormal indicators, wherein each indicator combination information in the indicator combination information sequence includes: a target abnormal indicator group, and the sum of the important indicator information corresponding to the above target abnormal indicator group is greater than the target value. The target abnormal indicator group sequence corresponding to the indicator combination information sequence is sorted according to the sum of the important indicator information. In practice, the target value can be the value "0.5".

[0115] The third step is to divide the user information of each offline user in the offline user information set into user information hierarchies according to the first user anomaly detection information set to generate offline user information groups and obtain an offline user information group sequence. The offline user information groups in the offline user information group sequence can be sorted in descending order according to the user information level. The higher the user information level, the lower the abnormal value of each offline user information in the corresponding offline user information group.

[0116] As an example, the execution subject may determine the detection information interval in which each first user abnormality detection information is located to generate a user information level corresponding to the detection interval. According to the obtained user information level set, each offline user information in the offline user information set is hierarchically divided into user information levels to generate offline user information groups, and obtain an offline user information group sequence.

[0117] The fourth step is to determine each offline user information group in the offline user information group sequence and execute the following fourth generation step:

[0118] Sub-step 1: determine the target abnormal indicator group in the target abnormal indicator group sequence corresponding to the offline user information group as the matching abnormal indicator group.

[0119] Sub-step 2, generating a third risk control link funnel detection model for the above-mentioned matching abnormality indicator group. The third risk control link funnel detection model may be a model preset for risk control funnel form detection based on each matching abnormality indicator in the matching abnormality indicator group. The third risk control link funnel detection model may include: indicator rules corresponding to each matching abnormality indicator in the matching abnormality indicator group.

[0120] Sub-step 3, in response to determining that the predetermined time period has been reached, using the third risk control link funnel detection model, perform user anomaly detection on the offline user information set to obtain a first initial product usage anomaly detection information set. The predetermined time period may be a pre-set cycle time. The predetermined time period may be the duration of updating the corresponding anomaly detection information of the user.

[0121] As an example, the above-mentioned execution entity can use the funnel detection model of the third risk control link as the anomaly detection model, perform user anomaly detection on the offline user information set, and obtain the first initial product usage anomaly detection information set.

[0122] Sub-step 4, determining the team anomaly detection information corresponding to the offline user information group as the target team anomaly detection information.

[0123] Sub-step 5, using a predetermined association table between team anomalies and product usage anomalies, determine the product usage anomaly information corresponding to the above target team anomaly detection information as the second initial product usage anomaly information.

[0124] Sub-step 6: performing weighted sum processing on the first initial product usage anomaly detection information set and the second initial product usage anomaly detection information set to obtain a product usage anomaly detection information set.

[0125] The above "in some optional implementations of some embodiments" as an invention point solves "how to accurately generate a product usage anomaly detection information set based on the above first user anomaly detection information set and team anomaly detection information set while calling various computing resources". Based on this, the present disclosure uses at least one future anomaly indicator prediction model, a second risk control environment vulnerability detection model and a clustering algorithm, and utilizes the computing resources corresponding to the graphics processor and the central processing unit to accurately generate a product usage anomaly detection information set while appropriately calling the corresponding computing resources.

[0126] The above-mentioned embodiments of the present disclosure have the following beneficial effects: through the information sending method based on multi-level regional terminals of some embodiments of the present disclosure, based on the interaction between multi-level regional terminals, the product value issuance related information can be accurately and efficiently encrypted and sent to the corresponding user. Specifically, the reason why the relevant information related to the issuance of sub-product values ​​is not accurate and efficient is that when there are a large number of users in the region, the corresponding calculation time of the calculation script is relatively long, and the calculation script cannot effectively guarantee the information leakage of product value information and the accuracy of product value information, and often lacks the relevant steps of realizing the audit through the terminal interaction between multiple levels. Based on this, the information sending method based on multi-level regional terminals of some embodiments of the present disclosure, first, in response to receiving the product value issuance request corresponding to the target area, obtain the user information set corresponding to the above target area from the storage module, wherein the above target area has a corresponding regional terminal, and the above regional terminal includes: a calculation module, a storage module and a sending module. Here, through the calculation module, the storage module and the sending module included in the regional terminal, the terminal functions can be distinguished, so as to ensure that the regional terminal can efficiently and accurately realize the generation of subsequent product value information through the coordination between the modules. Then, the product usage level information set, product generation value information set, user team information set and product usage anomaly detection information set corresponding to the above user information set are obtained from the above storage module, so as to facilitate the subsequent accurate generation of product value information. Then, using the above calculation module, according to the above product usage level information set, the above product generation value information set, the above user team information set and the above product usage anomaly detection information set, the product value information set corresponding to the above user information set can be accurately determined. Then, using the above sending module, the product value encrypted information set corresponding to the above product value information set is sent to the upper-level regional terminal corresponding to the above target area, wherein the upper-level regional terminal includes each terminal backup data corresponding to each lower-level regional terminal. Here, through the setting of multi-level regional terminals, the generation of product value information and the review of product value information can be distinguished to avoid generation and review at the same terminal, which not only wastes too many computing resources, but also may cause the information to not be accurately and objectively reviewed. In addition, through the setting of multi-level regional terminals, multi-level backup of terminal data can be guaranteed to reduce the storage pressure of low-level regional terminals, and also to ensure the information completeness of high-level regional terminals, so as to achieve more accurate review of product value information and generation of product usage anomaly detection information, and maintain the target products corresponding to each user.Finally, in response to determining that the audit information sent by the above-mentioned upper-level regional terminal is represented correctly, for each user information in the above-mentioned user information set, the sending step is performed: the first step is to package the product usage level information, product generation value information, user team information, the above-mentioned user information and product value distribution rule information corresponding to the above-mentioned user information to generate value packaging information. Here, after the upper-level regional terminal determines that the audit is correct, the packaging method is used to facilitate the subsequent sending to the user so that the user can see the complete product value distribution related information. The second step is to use the above-mentioned sending module to send the above-mentioned value packaging information to the user terminal in the sending method determined by the user corresponding to the above-mentioned user information, wherein the above-mentioned sending method is one of the following: encrypted SMS link method, encrypted email method. Here, based on the sending method selected by the user, during the sending process, the information security of the value packaging information is guaranteed by encryption to avoid information leakage. In summary, through the deployment of multi-level regional terminals, each process of the product value information can be executed in multiple modules in multiple terminals, ensuring the generation efficiency, accuracy and information security of the product value information.

[0127] Further references Figure 2 As an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of an information sending device based on a multi-level regional terminal. These device embodiments are similar to Figure 1 Corresponding to the method embodiments shown, the information sending device based on multi-level area terminals can be specifically applied to various electronic devices.

[0128] like Figure 2As shown, an information sending device 200 based on a multi-level regional terminal includes: a first acquisition unit 201, a second acquisition unit 202, a determination unit 203, a sending unit 204 and an execution unit 205. The first acquisition unit 201 is configured to, in response to receiving a product value issuance request corresponding to a target area, obtain a user information set corresponding to the target area from a storage module, wherein the target area has a corresponding regional terminal, and the regional terminal includes: a calculation module, a storage module and a sending module; the second acquisition unit 202 is configured to obtain a product usage level information set, a product generation value information set, a user team information set and a product usage anomaly detection information set corresponding to the user information set from the storage module; the determination unit 203 is configured to use the calculation module to determine the product value information set corresponding to the user information set according to the product usage level information set, the product generation value information set, the user team information set and the product usage anomaly detection information set; the sending unit 204 is configured to use the The sending module sends the encrypted product value information set corresponding to the above-mentioned product value information set to the upper-level regional terminal corresponding to the above-mentioned target area, wherein the above-mentioned upper-level regional terminal includes the terminal backup data corresponding to each lower-level regional terminal; the execution unit 205 is configured to respond to determining that the audit information representation sent by the above-mentioned upper-level regional terminal is correct, and for each user information in the above-mentioned user information set, execute the sending step: package the product usage level information, product generation value information, user team information, the above-mentioned user information and product value issuance rule information corresponding to the above-mentioned user information to generate value packaging information; use the above-mentioned sending module to send the above-mentioned value packaging information to the user terminal in the sending method determined by the user corresponding to the above-mentioned user information, wherein the above-mentioned sending method is one of the following: encrypted SMS link method, encrypted email method.

[0129] It can be understood that the units described in the information sending device 200 based on the multi-level regional terminal are similar to those described in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the information sending device 200 based on the multi-level regional terminal and the units contained therein, and will not be described in detail here.

[0130] Reference below Figure 3 , which shows a structural schematic diagram of an electronic device (eg, an electronic device) 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0131] like Figure 3As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0132] Typically, the following devices may be connected to the I / O interface 305: input devices 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 308 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 309. The communication devices 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0133] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0134] It should be noted that the computer-readable medium in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In some embodiments of the present disclosure, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0135] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0136] The above-mentioned computer-readable medium may be included in the above-mentioned electronic device; or it may exist independently without being assembled into the electronic device. The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the electronic device, the electronic device: in response to receiving a product value issuance request corresponding to the target area, obtains the user information set corresponding to the above-mentioned target area from the storage module, wherein there is a corresponding regional terminal for the above-mentioned target area, and the above-mentioned regional terminal includes: a calculation module, a storage module and a sending module; obtains the product usage level information set, the product generation value information set, the user team information set and the product usage anomaly detection information set corresponding to the above-mentioned user information set from the above-mentioned storage module; uses the above-mentioned calculation module to determine the product value information set corresponding to the above-mentioned user information set according to the above-mentioned product usage level information set, the above-mentioned product generation value information set, the above-mentioned user team information set and the above-mentioned product usage anomaly detection information set; The above-mentioned sending module is used to send the product value encrypted information set corresponding to the above-mentioned product value information set to the upper-level regional terminal corresponding to the above-mentioned target area, wherein the above-mentioned upper-level regional terminal includes each terminal backup data corresponding to each lower-level regional terminal; in response to determining that the audit information representation sent by the above-mentioned upper-level regional terminal is correct, for each user information in the above-mentioned user information set, a sending step is performed: the product usage level information, product generation value information, user team information, the above-mentioned user information and product value issuance rule information corresponding to the above-mentioned user information are packaged to generate value packaging information; the above-mentioned sending module is used to send the above-mentioned value packaging information to the user terminal in the sending method determined by the user corresponding to the above-mentioned user information, wherein the above-mentioned sending method is one of the following: encrypted SMS link method, encrypted email method.

[0137] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0138] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0139] The units described in some embodiments of the present disclosure may be implemented by software or by hardware. The units described may also be provided in a processor, for example, may be described as: a processor comprising a first acquisition unit, a second acquisition unit, a determination unit, a sending unit, and an execution unit. The names of these units do not, in some cases, constitute limitations on the units themselves, for example, the first acquisition unit may also be described as "a unit that, in response to receiving a request for issuance of a product value corresponding to a target area, obtains from a storage module a user information set corresponding to the above target area".

[0140] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0141] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. A method for sending information based on a multi-level regional terminal, comprising: In response to receiving a product value distribution request corresponding to a target area, obtaining a user information set corresponding to the target area from a storage module, wherein the target area has a corresponding regional terminal, and the regional terminal includes: a calculation module, a storage module, and a sending module; Acquire a product usage level information set, a product generation value information set, a user team information set, and a product usage anomaly detection information set corresponding to the user information set from the storage module; Determine, by means of the calculation module, a product value information set corresponding to the user information set according to the product usage level information set, the product generation value information set, the user team information set and the product usage anomaly detection information set; Using the sending module, the encrypted product value information set corresponding to the product value information set is sent to the upper-level regional terminal corresponding to the target area, wherein the upper-level regional terminal includes each terminal backup data corresponding to each lower-level regional terminal; In response to determining that the audit information sent by the upper-level regional terminal is correct, for each user information in the user information set, a sending step is performed: Packing the product usage level information, product value generation information, user team information, the user information and product value distribution rule information corresponding to the user information to generate value packaging information; The sending module is used to send the value package information to the user terminal in a sending mode determined by the user corresponding to the user information, wherein the sending mode is one of the following: an encrypted SMS link mode, an encrypted email mode.

2. The method according to claim 1, wherein: The method further comprises: In response to determining that the audit information representation sent by the upper-level regional terminal is correct, storing the obtained value package information set in the storage module, and setting the storage time of the value package information set in the storage module; Using the sending module, sending the value package information set to the upper-level regional terminal; and The upper level regional terminal performs the following processing steps on the value packaging information set: Obtaining the value audit record corresponding to the value packaging information set; The value packaging information set, the value audit record and the area information corresponding to the target area are stored in a storage module included in the upper-level area terminal.

3. The method according to claim 1, wherein: The using the calculation module to determine the product value information set corresponding to the user information set according to the product usage level information set, the product generation value information set, the user team information set and the product usage anomaly detection information set includes: For each piece of user information in the user information set, the following first generation step is performed using the calculation module: Determine product value distribution rule information corresponding to the user information according to the product usage level information; Determining basic product value information corresponding to the user information according to the product value distribution rule information and the product generated value information; Determine an online user information set and an offline user information set corresponding to the user team information; According to the online user information set, the offline user information set and the product usage anomaly detection information set, the team value change information is determined using the product value distribution rule information; The product value information is generated according to the basic product value information and the team value change information.

4. The method according to claim 3, wherein: The determining of team value change information based on the online user information set, the offline user information set and the product use anomaly detection information set and using the product value distribution rule information includes: For each online user information in the online user information set, according to the value information corresponding to the online user information, using the product value distribution rule information, determine the team value deduction information corresponding to the online user information; For each offline user information in the offline user information set, the following second generating step is performed: According to the value information corresponding to the offline user information, using the product value distribution rule information, determine the initial team value increase information corresponding to the offline user information; Acquire product usage anomaly detection information corresponding to the offline user information, wherein the product usage anomaly detection information corresponding to each offline user information in the offline user information set is predetermined based on a funnel detection model of a risk control link; generating team value increase information according to the product usage anomaly detection information and the initial team value increase information; The obtained team value deduction information set and the obtained team value increase information set are added together to generate team value change information.

5. The method according to claim 1, wherein: The using the calculation module to determine the product value information set corresponding to the user information set according to the product usage level information set, the product generation value information set and the user team information set includes: Using the large model calling interface, the large language model is retrieved from the computing module; Generate a representation to generate value generation prompt information of a product value information set according to a product usage level information set, a product generation value information set and a user team information set; The value generation prompt information is sent to the large language model to generate a product value information set corresponding to the user information set.

6. The method according to claim 4, wherein: The method further comprises: Periodically receiving a product usage anomaly detection information set for the user information set sent by the upper-level regional terminal; And the product usage anomaly detection information set corresponding to the offline user information set in the upper-level regional terminal is generated by the following steps: Filtering out target user information whose corresponding user abnormality label is a target abnormality label from the target user information set in the storage module, and obtaining at least one abnormal user information; generating at least one target abnormality indicator according to at least one historical value product call data sequence corresponding to the at least one abnormal user information; Generating a first risk control link funnel detection model for historical call data according to the at least one target abnormality indicator; According to the funnel detection model of the first risk control link, performing user anomaly detection on the offline user information set to obtain a first user anomaly detection information set; For each offline user information in the offline user information set, determining the team anomaly detection information corresponding to the offline user information according to the user team information corresponding to the offline user information; A product usage anomaly detection information set for the offline user information set is generated according to the first user anomaly detection information set and the team anomaly detection information set.

7. An information sending device based on a multi-level regional terminal, comprising: A first acquisition unit is configured to, in response to receiving a product value distribution request corresponding to a target area, acquire a user information set corresponding to the target area from a storage module, wherein the target area has a corresponding regional terminal, and the regional terminal includes: a calculation module, a storage module, and a sending module; A second acquisition unit is configured to acquire, from the storage module, a product usage level information set, a product generation value information set, a user team information set, and a product usage anomaly detection information set corresponding to the user information set; a determination unit configured to determine, by using the calculation module, a product value information set corresponding to the user information set according to the product usage level information set, the product generation value information set, the user team information set, and the product usage anomaly detection information set; A sending unit is configured to send the encrypted product value information set corresponding to the product value information set to the upper-level regional terminal corresponding to the target area by using the sending module, wherein the upper-level regional terminal includes each terminal backup data corresponding to each lower-level regional terminal; The execution unit is configured to, in response to determining that the audit information representation sent by the upper-level regional terminal is correct, execute a sending step for each user information in the user information set: package the product usage level information, product generation value information, user team information, the user information and product value issuance rule information corresponding to the user information to generate value packaging information; use the sending module to send the value packaging information to the user terminal in a sending method determined by the user corresponding to the user information, wherein the sending method is one of the following: an encrypted SMS link method, an encrypted email method.

8. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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