Emergency management methods, devices, equipment, media and program products

Abstract

The present disclosure provides an emergency management method that can be applied to the field of data security technology or the financial field. The emergency management method includes: obtaining the first response status of the data provider; judging whether the first response status is abnormal based on the early warning model; when the first response status is abnormal, triggering an early warning and turning on the emergency status; storing the emergency business data in a cache queue based on the emergency status; obtaining the second response status of the data provider based on a restart model, wherein the restart model is associated with the early warning model; judging whether the second response status is abnormal based on the early warning model; when the second response status is normal, the early warning is restored and the emergency status is turned off; and retrieving the emergency business data from the cache queue to the normal queue. The present disclosure also provides an emergency management device, equipment, storage medium and program product.

Description

Technical Field

[0001] The present disclosure relates to the field of data security technology or the financial field, and specifically to an emergency management method, device, equipment, medium and program product. Background Art

[0002] In the prior art, when handling a business, it is often necessary to call the data information of an external data provider. When the data provider is in an abnormal state, it will affect the business handling process. For example, in the scenario of the bank system involving calling external data for approval rules, it is usually necessary to collect data from multiple parties to achieve a complete and accurate assessment of the customer. Common data providers include the People's Bank of China's credit reporting system, academic record system, bank credit card consumption records, court flyer records, etc. When the credit card limit approval system obtains data from any of them, due to the system failure of the data provider, it cannot accurately obtain customer information and thus affects the credit limit. It often adopts direct rejection, skipping a certain strategy or transferring to manual processing to avoid system impact. These practices may affect customer experience, reduce bank profits, be unfavorable to business expansion, increase the risk of bad capital, and a large backlog of applications, excessive pressure on business personnel, and customers waiting for approval results for too long. Summary of the invention

[0003] In view of the above problems, embodiments of the present disclosure provide an emergency management method, apparatus, device, medium, and program product.

[0004] According to the first aspect of the present disclosure, an emergency management method is provided, including: obtaining a first response status of a data provider; judging whether the first response status is abnormal based on an early warning model; when the first response status is abnormal, triggering an early warning and turning on an emergency status; storing emergency service data in a cache queue based on the emergency status; obtaining a second response status of the data provider based on a restart model, wherein the restart model is associated with the early warning model; judging whether the second response status is abnormal based on the early warning model; when the second response status is normal, restoring the early warning and turning off the emergency status; and retrieving the emergency service data from the cache queue to the normal queue.

[0005] According to an embodiment of the present disclosure, the early warning model includes an early warning parameter and a preset early warning threshold, wherein the early warning model is configured to determine that the response state of the data provider is abnormal when the early warning parameter is greater than or equal to the early warning threshold. The early warning threshold is determined based on the average probability of abnormal state of the data provider and a multiple parameter.

[0006] According to an embodiment of the present disclosure, the restart model is established based on a time series algorithm, wherein the method for establishing the restart model includes: obtaining historical data of warning parameters, wherein the historical data of warning parameters includes a sequence of time intervals from the previous M times of triggering the warning to the warning recovery, wherein M is an integer greater than or equal to 2; obtaining a recovery time prediction value and a recovery time volatility based on the historical data of warning parameters and the time series algorithm; and obtaining a retry time interval based on the recovery time prediction value and the recovery time volatility.

[0007] According to an embodiment of the present disclosure, after obtaining the retry time interval, the establishment method further includes: obtaining a retry times threshold value based on the recovery time prediction value and the retry time interval.

[0008] According to an embodiment of the present disclosure, when the first response state is abnormal, at least one of the user portrait model or the backup data is retrieved based on the emergency business data; and recommended business information is generated based on the user portrait model or at least one of the backup data.

[0009] According to an embodiment of the present disclosure, the user portrait model is constructed based on user collection data, and the user portrait model is configured to divide user types according to user feature dimensions, the user types are associated with recommended business types, and the recommended business types are associated with recommended business information, wherein the user collection data is acquired based on user authorization.

[0010] According to an embodiment of the present disclosure, the backup data includes user history data obtained from a data provider, wherein the user history data is obtained based on user authorization.

[0011] The second aspect of the present disclosure provides an emergency management device, including: a first acquisition module, configured to acquire a first response status of a data provider; a first judgment module, configured to determine whether the first response status is abnormal based on an early warning model; a first processing module, configured to trigger an early warning and turn on an emergency status when the first response status is abnormal; a storage module, configured to store emergency service data in a cache queue based on the emergency status; a second acquisition module, configured to acquire a second response status of a data provider based on a restart model, wherein the restart model is associated with the early warning model; a second judgment module, configured to determine whether the second response status is normal based on the early warning model; a second processing module, configured to restore the early warning and turn off the emergency status when the second response status is normal; and a calling module, configured to call the emergency service data from the cache queue to the normal queue.

[0012] A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above method.

[0013] The fourth aspect of the present disclosure also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the above method.

[0014] The fifth aspect of the present disclosure also provides a computer program product, including a computer program, which implements the above method when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0016] Figure 1 The application scenario diagram of the emergency management method, apparatus, device, medium and program product according to the embodiments of the present disclosure is schematically shown.

[0017] Figure 2 The flowchart of the emergency management method according to the embodiment of the present disclosure is schematically shown.

[0018] Figure 3 The flowchart of the method for establishing a restart model according to an embodiment of the present disclosure is schematically shown.

[0019] Figure 4 The flowchart of the compensatory feedback method according to the embodiment of the present disclosure is schematically shown.

[0020] Figure 5 The structural block diagram of the emergency management device according to an embodiment of the present disclosure is schematically shown.

[0021] Figure 6 A block diagram of an electronic device suitable for implementing an emergency management method according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0022] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0023] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0024] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0025] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0026] It should be noted that the emergency management method, device, system, and electronic device provided in the embodiments of the present disclosure can be used in the field of data security technology in data emergency management related aspects, and can also be used in various fields other than data security technology, such as the financial field, etc. The application field of the emergency management method, device, system, and electronic device provided in the embodiments of the present disclosure is not limited.

[0027] In the technical solution of the present disclosure, the acquisition, collection, storage, use, processing, transmission, provision, disclosure and application of user personal information and data involved are in compliance with the provisions of relevant laws and regulations, necessary confidentiality measures have been taken, and do not violate public order and good morals.

[0028] An embodiment of the present disclosure provides an emergency management method, including: obtaining a first response status of a data provider; determining whether the first response status is abnormal based on an early warning model; when the first response status is abnormal, triggering an early warning and turning on an emergency status; storing emergency business data in a cache queue based on the emergency status; obtaining a second response status of a data provider based on a restart model, wherein the restart model is associated with the early warning model; determining whether the second response status is abnormal based on the early warning model; when the second response status is normal, restoring the early warning and turning off the emergency status; and retrieving the emergency business data from the cache queue to a normal queue.

[0029] Figure 1 The application scenario diagram of the emergency management method, apparatus, device, medium and program product according to the embodiments of the present disclosure is schematically shown.

[0030] like Figure 1 As shown, the application scenario 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for a communication link between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0031] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only examples).

[0032] The terminal devices 101 , 102 , and 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0033] The server 105 may be a server that provides various services, such as a background management server (only an example) that provides support for websites browsed by users using the terminal devices 101, 102, and 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0034] It should be noted that the emergency management method provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the emergency management device provided in the embodiment of the present disclosure can generally be set in the server 105. The emergency management method provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105. Accordingly, the emergency management device provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105.

[0035] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0036] The following will be based on Figure 1 The scene described by Figure 2 to Figure 4 The emergency management method of the disclosed embodiment is described in detail.

[0037] Figure 2 The flowchart of the emergency management method according to the embodiment of the present disclosure is schematically shown.

[0038] like Figure 2 As shown, the emergency management of this embodiment may include operations S210 to S280.

[0039] In operation S210, a first response status of a data provider is acquired.

[0040] In operation S220, it is determined whether the first response state is abnormal based on the early warning model.

[0041] According to an embodiment of the present disclosure, the emergency management method is enabled based on the response status feedback of the external data provider. The response status of the data provider before the emergency status is turned on is the first response status. According to an embodiment of the present disclosure, whether the first response status is abnormal can be judged based on the early warning model. Among them, the early warning model includes an early warning parameter and a preset early warning threshold, and the early warning model is configured to determine that the response status of the data provider is abnormal when the early warning parameter is greater than or equal to the early warning threshold.

[0042] In the embodiments of the present disclosure, different external data providers can be monitored on a daily basis for their service response status, and early warning parameters and early warning thresholds can be set. Among them, the early warning parameter can represent the probability of abnormal state of the data provider per unit time, which can be the ratio of the number of abnormal state of the data provider per unit time to the total number of calls, or can be obtained by assigning values ​​to the reasons for abnormal state of the data provider (different values ​​can be assigned to different reasons), and can also be obtained by weighted calculation of the abnormal proportion of the state of the data provider per unit time and the value assigned to the abnormal reason. The early warning threshold represents the upper limit of the probability of abnormal state of the data provider that can be tolerated, which can be determined based on the average probability of abnormal state of the data provider and the multiple parameter. It can be understood that under normal circumstances, the probability of abnormal state of a certain external data provider is stable near the average value. For example, if 1,000 business requests are processed in one day, 10 requests for external data acquisition may fail when calling the data provider data, and the probability of abnormal state of the data provider is 1%. Under normal circumstances, the probability of abnormal state of the data provider is relatively stable. For example, if the probability of abnormal state of multiple days is continuously counted and the average value is calculated, the average value is 1%. Then the probability of abnormal state is the average probability of abnormal state of the data provider and is acceptable, and there is no need to trigger an early warning. In this case, for the request of failed data acquisition, it can be handled by informing the customer "the current system is faulty, please wait", "the data call failed, please submit a request separately", skipping the process or transferring to manual service. However, when the probability of failure of the data provider in a certain unit time increases sharply and exceeds a certain multiple of the average value, for example, within one day, 1000 business requests are processed, and 100 requests fail to obtain when calling the external data of the data provider. At this time, if the usual processing method is still used, it may face problems such as customer loss, excessive pressure on business personnel or increased business risks. Therefore, the multiple parameter can be set as the error allowable range control factor to adjust the average probability of abnormal state of the data provider to obtain the tolerance parameter of the probability of abnormal state of the data provider, that is, the early warning threshold. Among them, the multiple parameter may include a numerical value set based on experience, for example, it may be an integer greater than or equal to 1. In this case, the warning threshold may be the average probability of abnormal state of the data provider multiplied by the multiple parameter; the multiple parameter may also include a variance multiple, for example, a multiple of the variance of the abnormal probability of the data provider state calculated X times, for example, 2-3 times the abnormal probability variance, where X may be an integer greater than or equal to 2. In this case, the warning threshold may be the average probability of abnormal state of the data provider + the multiple parameter. It is understandable that the calculation method of the multiple parameter and the average probability of abnormal state of the data provider can be adjusted and determined based on the conventional calculation method of the error range and the error range setting requirements. When the cause of abnormal state of the data provider or the weighted item of the abnormal probability of the data provider state per unit time and the value of the abnormal cause is used as the warning parameter, the average probability of abnormal state of the data provider and the multiple parameter may also be calculated similarly.For example, by assigning a value to the abnormal cause according to the cause type as the average probability of abnormal state of the data provider, and setting the multiple parameter to a specific value, the warning threshold can be obtained when the abnormal cause or a weighted item containing the abnormal cause is used as the warning parameter.

[0043] According to an embodiment of the present disclosure, when the warning parameter reaches the warning threshold, it is determined that the first response state is abnormal, and operation S230 is performed.

[0044] In operation S230, when the first response state is abnormal, an early warning is triggered and an emergency state is activated.

[0045] According to the embodiments of the present disclosure, it can be understood that when the warning parameter does not reach the warning threshold, it means that the data provider system is operating normally, the first response status is normal, and the business system can obtain external data from the data provider and execute the business process normally.

[0046] In operation S240, the emergency service data is stored in a buffer queue based on the emergency status.

[0047] According to an embodiment of the present disclosure, after an early warning is triggered, the system emergency state can be turned on. After the emergency state is turned on, business requests can continue to be received and external data of the data provider can be called, wherein the business request data that failed to retrieve external data can be used as emergency business data and stored in the cache queue, and the emergency business data in the cache queue can be called back to the normal queue after the data provider status returns to normal.

[0048] In operation S250, a second response status of the data provider is acquired based on the restart model.

[0049] According to an embodiment of the present disclosure, a data call test can be performed on the data provider after the emergency state is turned on to avoid invalid waiting. The test response state, that is, the second response state, can be obtained based on the restart model.

[0050] In an embodiment of the present disclosure, the restart model may be associated with the warning model, for example, the restart model may be established based on the historical data of the warning parameters. Further, the restart model may be established based on a time series algorithm.

[0051] Figure 3 The flowchart of the method for establishing a restart model according to an embodiment of the present disclosure is schematically shown.

[0052] like Figure 3 As shown, the method for establishing a restart model in this embodiment at least includes operations S310 to S340.

[0053] In operation S310, historical data of early warning parameters are obtained.

[0054] According to an embodiment of the present disclosure, the warning parameter history data includes a time interval sequence from the previous M times of triggering the warning to the time of warning recovery.

[0055] In operation S320, a recovery time prediction value and a recovery time fluctuation rate are obtained based on the warning parameter historical data and a time series algorithm.

[0056] According to the embodiments of the present disclosure, a time series algorithm can be used to obtain a recovery time prediction value and a recovery time volatility by monitoring the time interval between the triggering and recovery of daily warning parameters. The time series algorithm can be a common time series algorithm, including a moving average method, an exponential smoothing method, an AR model, an MA model, an ARMA model, etc. The recovery time prediction value represents the time interval required from the triggering of the warning to the recovery of the warning. The recovery time volatility represents the degree of fluctuation of the time interval from the triggering of the warning to the recovery of the warning based on the historical data of the warning parameters. Taking the moving average method as an example, assuming that T 2 -T 1 , T 4 -T 3 are the time intervals between the last two warnings and the recovery to normal. The time interval between the next warning and recovery can be predicted to be: ((T 2 -T 1 )+(T 4 -T 3 ))×(1 / 2). Similarly, if the time interval from the first M times the warning is triggered to the time the warning is restored is T i -T i-1 , i satisfies i / 2=1,2,...,M, where T i is the i / 2th warning recovery time, T i-1 is the time of the i / 2th warning triggering, M is the number of rounds of triggering and restoring warnings and M is an integer greater than or equal to 2. The time interval T between the next warning and restoration can be predicted as: T = (1 / M) × ∑ (T i -T i-1 ), which is the recovery time prediction value (T). Further, the recovery time fluctuation rate (s^2) can be calculated, satisfying s^2=(1 / (M-1))×∑(T i -T)^2.

[0057] In operation S330, a retry time interval may be acquired based on the recovery time prediction value and the recovery time fluctuation rate.

[0058] According to an embodiment of the present disclosure, after obtaining the recovery time prediction value and the recovery time volatility, the retry time interval (ΔT) can be calculated. The retry time interval represents the time interval for initiating a call test during the triggering of an early warning and the early warning recovery. In a typical example, ΔT = T-2×s^2. It is understandable that the calculation method of the recovery time prediction value and the recovery time volatility can be set based on the system and business scenario requirements to obtain a suitable retry time interval.

[0059] In some specific embodiments, after obtaining the retry time interval, the restart model building method may further include operation S340.

[0060] In operation S340, a retry number threshold may be acquired based on the recovery time prediction value and the retry time interval.

[0061] According to a specific embodiment of the present disclosure, in order to avoid unnecessary data overhead caused by repeated retries when the data provider system failure is more serious, a retry threshold can be set. It represents the upper limit of the call test number. When the retry threshold is reached, the call test can be stopped. In a typical example, the retry threshold (N) can be calculated according to the following method: N = recovery time prediction value (T) ÷ retry time interval (ΔT) rounded.

[0062] In operation S260, it is determined whether the second response state is abnormal based on the early warning model.

[0063] According to an embodiment of the present disclosure, a message automatic monitoring method can be adopted to initiate a simulated transaction to the data provider for a call test at each retry time interval. It can be determined whether the second response status is abnormal based on the early warning model. If the response is still abnormal, the call test is initiated again after waiting for the retry time interval until the second response status is normal, and operation S270 is performed.

[0064] In operation S270, the warning is restored and the emergency state is closed.

[0065] In operation S280, the emergency service data is transferred from the buffer queue to the normal queue.

[0066] According to an embodiment of the present disclosure, when the data provider returns to normal, the emergency state is closed and the emergency service data can be transferred from the cache queue to the normal queue for subsequent service processing.

[0067] According to an embodiment of the present disclosure, it can be understood that when the restart model includes a retry number threshold, after determining that the second response state is still abnormal based on the early warning model, the emergency management method further includes operation S290.

[0068] In operation S290, it is determined whether the number of retries reaches a threshold.

[0069] If the retry times threshold is reached, execute operation S2901.

[0070] In operation S2901, retrying can be stopped, but the emergency state does not need to be closed. Further, the emergency service data is connected to the manual channel for manual processing.

[0071] If the retry times threshold is not reached, the process returns to operation S250.

[0072] The emergency management method provided by the embodiment of the present disclosure flexibly monitors the response status of the data provider based on the early warning model and the restart model. By storing the emergency business data within the abnormal time period of the data provider's response status in the cache queue, and calling it back to the normal queue for processing after the data provider returns to normal, it achieves timely and effective response to the emergency status, ensures the integrity of the data and the efficiency of the process, and avoids redundant operations caused by repeated business applications.

[0073] According to an embodiment of the present disclosure, when the data provider responds in an abnormal state, compensatory feedback may be provided to the service request corresponding to the emergency service data in the cache queue based on the user portrait model.

[0074] Figure 4 The flowchart of the compensatory feedback method according to the embodiment of the present disclosure is schematically shown.

[0075] like Figure 4 As shown, the compensatory feedback method of this embodiment includes operations S410 to S420.

[0076] In operation S410, when the first response state is abnormal, at least one of a user portrait model or backup data is retrieved based on the emergency service data.

[0077] In operation S420, recommended business information is generated based on at least one of the user portrait model or the backup data.

[0078] According to an embodiment of the present disclosure, a user portrait model is constructed based on user collection data. The user portrait model is configured to divide user types according to user feature dimensions. User types are associated with recommended service types, and recommended service types are associated with recommended service information. The user collection data is obtained based on user authorization, meeting the security requirements for user data acquisition.

[0079] In an embodiment of the present disclosure, user set data may be a set of user information that is input and recorded by the user in the business system. The set of user information may include multiple user feature dimensions, such as age, income, occupation, education, participation in promotional activities, etc. One user feature dimension or a combination of multiple user feature dimensions may be used as the basis for user type division, and dimension stratification may be set to finely divide user types. For example, based on age, user types may be divided into youth user groups, middle-aged user groups, elderly user groups, etc.; based on income, user types may be divided into high-income user groups, middle-income user groups, low-income user groups, etc.; based on age and income, user types may be divided into low-income young user groups, high-income middle-aged user groups, etc.; age may also be set as a primary feature dimension, and participation in promotional activities may be set as a secondary feature dimension, and user types may be divided into youth high activity participation user groups and youth low activity participation user groups. Different user types may correspond to different recommended business types, wherein the recommended business types may include the business types that each type of user group tends to handle, and may also include the discounts that users can enjoy when handling business. Based on the recommended business type, recommended business information can be provided to users who submit emergency business data. It can be understood that when the business system turns on the emergency state, the current user information of the corresponding user can be obtained based on the emergency business data, and the current user can be classified into a certain user type in the user portrait model based on the current user information, so as to obtain the recommended business type corresponding to the user type, and provide business information recommendation based on this recommended business type. For example, when the business request is a credit card limit adjustment, the system can return a reference recommended limit based on the user portrait, and give corresponding prompts to inform the user that the accurate limit will be returned after the data provider status is restored, so as to avoid long waiting for the customer. On the other hand, alternative business recommendations can also be made based on the user type of the user. For example, if the current user belongs to the youth user group, based on experience, the youth user tends to apply for micro-loan business, or is more active in responding to some promotional activities and participates more, and the micro-loan business or promotional activities can be pushed to the current user. Furthermore, a secondary rate stratification can be made for different user groups. If the current user belongs to the youth high activity participation user group, promotional activities can be pushed to it, and discounts can be given for handling fees.

[0080] According to an embodiment of the present disclosure, recommended service information may also be generated based on backup data, wherein the backup data may include user history data obtained from a data provider, and it should be noted that the user history data is obtained based on user authorization to ensure user data security.

[0081] In an embodiment of the present disclosure, necessary external data information of existing customers can be saved and updated in the business system so that there is a basis for finding when a failure occurs. For example, necessary external data information can be obtained from the data provider, and user history data can be the user data obtained when the data provider was last called. It can be understood that user history data is not necessarily limited to the historical data obtained by the current business system calling the data provider, and the user history data can also be obtained from the data provider when any business is handled for the current user and the business needs to call the data provider. Furthermore, the data provider can also be called regularly based on the business system maintenance requirements to update the existing user information to improve the timeliness and effectiveness of the data. In an embodiment of the present disclosure, the current user request can be evaluated based on the backup data to generate recommended business information.

[0082] The emergency management method provided by the embodiment of the present disclosure avoids customer loss caused by the inability to accept customer applications due to maintenance of the external system, improves customer satisfaction, and maintains customer stickiness.

[0083] Based on the above emergency management method, the present disclosure also provides an emergency management device. Figure 5 The device is described in detail.

[0084] Figure 5 The structural block diagram of the emergency management device according to an embodiment of the present disclosure is schematically shown.

[0085] like Figure 5 As shown, the emergency management device 500 of this embodiment includes a first acquisition module 510, a first judgment module 520, a first processing module 530, a storage module 540, a second acquisition module 550, a second judgment module 560, a second processing module 570 and a retrieval module 580.

[0086] The first acquisition module 510 is configured to acquire a first response status of a data provider.

[0087] The first judgment module 520 is configured to judge whether the first response state is abnormal based on the early warning model.

[0088] The first processing module 530 is configured to trigger an early warning and activate an emergency state when the first response state is abnormal.

[0089] The storage module is configured 540 to store the emergency service data into a cache queue based on the emergency status.

[0090] The second acquisition module 550 is configured to acquire a second response status of the data provider based on a restart model, wherein the restart model is associated with the early warning model.

[0091] The second judgment module 560 is configured to judge whether the second response state is normal based on the early warning model.

[0092] The second processing module 570 is configured to restore the early warning and close the emergency state when the second response state is normal.

[0093] The retrieving module 580 is configured to retrieve the emergency service data from the cache queue to the normal queue.

[0094] According to an embodiment of the present disclosure, any multiple modules among the first acquisition module 510, the first judgment module 520, the first processing module 530, the storage module 540, the second acquisition module 550, the second judgment module 560, the second processing module 570 and the retrieval module 580 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the first acquisition module 510, the first judgment module 520, the first processing module 530, the storage module 540, the second acquisition module 550, the second judgment module 560, the second processing module 570 and the retrieval module 580 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or by any one of the three implementation methods of software, hardware and firmware or by an appropriate combination of any of them. Alternatively, at least one of the first acquisition module 510, the first judgment module 520, the first processing module 530, the storage module 540, the second acquisition module 550, the second judgment module 560, the second processing module 570 and the retrieval module 580 can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be executed.

[0095] Figure 6 A block diagram of an electronic device suitable for implementing an emergency management method according to an embodiment of the present disclosure is schematically shown.

[0096] like Figure 6As shown, the electronic device 900 according to an embodiment of the present disclosure includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage part 908 into a random access memory (RAM) 903. The processor 901 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 901 may also include an onboard memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0097] In RAM 903, various programs and data required for the operation of electronic device 900 are stored. Processor 901, ROM 902 and RAM 903 are connected to each other via bus 904. Processor 901 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 902 and / or RAM 903. It should be noted that the program can also be stored in one or more memories other than ROM 902 and RAM 903. Processor 901 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0098] According to an embodiment of the present disclosure, the electronic device 900 may further include an input / output (I / O) interface 905, which is also connected to the bus 904. The electronic device 900 may further include one or more of the following components connected to the I / O interface 905: an input portion 906 including a keyboard, a mouse, etc.; an output portion 907 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 908 including a hard disk, etc.; and a communication portion 909 including a network interface card such as a LAN card, a modem, etc. The communication portion 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 910 as needed, so that a computer program read therefrom is installed into the storage portion 908 as needed.

[0099] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0100] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: 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), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a 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, an apparatus, or a device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 902 and / or RAM 903 described above and / or one or more memories other than ROM 902 and RAM 903.

[0101] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the emergency management method provided by the embodiment of the present disclosure.

[0102] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 901. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0103] In one embodiment, the computer program may be based on a tangible storage medium such as an optical storage device, a magnetic storage device, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of a signal on a network medium, and downloaded and installed through the communication part 909, and / or installed from a removable medium 911. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0104] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 909, and / or installed from the removable medium 911. When the computer program is executed by the processor 901, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0105] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0106] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two 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 box in the block diagram or flow chart, and the combination of the boxes in the block diagram 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.

[0107] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0108] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. An emergency management method, comprising: Get the first response status of the data provider; Determining whether the first response state is abnormal based on the early warning model; When the first response state is abnormal, an early warning is triggered and an emergency state is activated; storing the emergency service data in a cache queue based on the emergency status; When the first response state is abnormal, retrieving at least one of a user portrait model or backup data based on the emergency service data; and generating recommended service information based on at least one of the user portrait model or the backup data; Acquiring a second response state of the data provider based on a restart model, wherein the restart model is associated with the early warning model; Determining whether the second response state is abnormal based on the early warning model; When the second response state is normal, the warning is restored and the emergency state is closed; and Retrieving the emergency service data from the cache queue to the normal queue; The restart model is established based on a time series algorithm, and the method for establishing the restart model includes: Acquire historical data of warning parameters, wherein the historical data of warning parameters includes a time interval sequence from the last M times of triggering warnings to the time of warning recovery, where M is an integer greater than or equal to 2; Acquire the recovery time prediction value and the recovery time fluctuation rate based on the warning parameter historical data and the time series algorithm; and A retry time interval is obtained based on the recovery time prediction value and the recovery time fluctuation rate.

2. The method according to claim 1, wherein: The warning model includes warning parameters and preset warning thresholds. in, The early warning model is configured to determine that the response state of the data provider is abnormal when the early warning parameter is greater than or equal to the early warning threshold, The warning threshold is determined based on the average probability of abnormal state of the data provider and a multiple parameter.

3. The method according to claim 1, wherein: After obtaining the retry time interval, the establishment method further includes: A retry times threshold is obtained based on the recovery time prediction value and the retry time interval.

4. The method according to claim 1, wherein: The user portrait model is constructed based on user collection data, and the user portrait model is configured to divide user types according to user feature dimensions, the user type is associated with the recommended business type, and the recommended business type is associated with recommended business information, wherein the user collection data is obtained based on user authorization.

5. The method according to claim 1, wherein: The backup data includes user history data obtained from a data provider, wherein the user history data is obtained based on user authorization.

6. An emergency management device, comprising: A first acquisition module, configured to acquire a first response status of a data provider; A first judgment module, configured to judge whether the first response state is abnormal based on the early warning model; A first processing module, configured to trigger an early warning and start an emergency state when the first response state is abnormal; A storage module, configured to store the emergency service data into a cache queue based on the emergency state; When the first response state is abnormal, retrieving at least one of a user portrait model or backup data based on the emergency service data; and generating recommended service information based on at least one of the user portrait model or the backup data; A second acquisition module is configured to acquire a second response status of a data provider based on a restart model, wherein the restart model is associated with the early warning model; A second judgment module is configured to judge whether the second response state is normal based on the early warning model; A second processing module is configured to, when the second response state is normal, restore the warning and close the emergency state; A calling module, configured to call the emergency service data from the cache queue to a normal queue; The restart model is established based on a time series algorithm, and the method for establishing the restart model includes: Acquire historical data of warning parameters, wherein the historical data of warning parameters includes a time interval sequence from the last M times of triggering warnings to the time of warning recovery, where M is an integer greater than or equal to 2; Acquire the recovery time prediction value and the recovery time fluctuation rate based on the warning parameter historical data and the time series algorithm; and A retry time interval is obtained based on the recovery time prediction value and the recovery time fluctuation rate.

7. An electronic device comprising: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method according to any one of claims 1 to 5.

9. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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