Order processing method and device, electronic equipment, storage medium and program product

Abstract

The invention provides an order processing method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of internet medical treatment. The order processing method comprises the steps of determining a plurality of attribute values of an acquisition operation based on a monitoring result of the acquisition operation of a to-be-processed order, and generating a pre-operation attribute value of the to-be-processed order based on the plurality of attribute values; performing risk control verification on a user account logging in the processing equipment based on the pre-operation attribute value; when it is detected that the user account passes risk control verification, it is confirmed that the processing device continues to process the to-be-processed order; and when it is detected that the user account does not pass risk control verification, releasing the to-be-processed order to a corresponding order grabbing area. Through the technical scheme disclosed by the invention, not only are behaviors of handing over an account to an irregular institution and using a plug-in to grasp an order of a doctor avoided, but also the occurrence of an unauthorized to-be-processed order is reduced, so that the reliability of order processing is ensured, and the credibility and satisfaction of a user to a related platform are improved.

Description

Background Art

[0002] With the rapid development of Internet medical care, Internet hospitals have become one of the important ways for people to seek medical treatment. Take online drug purchase as an example. Users need prescriptions to purchase prescription drugs. Internet hospitals provide a convenient platform for users and doctors to communicate online and issue prescriptions. Internet hospitals match users with qualified doctors based on the patient's condition. Online doctors take orders from users by grabbing orders, diagnose and treat users, and issue prescription suggestions.

[0003] At present, although doctors can receive consultation orders from users more quickly by grabbing orders through the platform, some doctors give their accounts to informal institutions. These institutions grab orders through plug-ins and other means, and automatically conduct mechanical questions and answers and prescribe prescriptions through pre-written programs. This leads to some orders that are not in the doctor's field of treatment, and unauthorized orders to be processed, which brings great risks to the serious consultation of the Internet hospital platform and creates a very bad user experience for users.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The purpose of the present disclosure is to provide an order processing method, an order processing device, an electronic device, a computer-readable storage medium and a computer program product, which can at least to some extent improve the risk problem in the related art when processing pending orders.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0007] According to one aspect of the present disclosure, there is provided an order processing method, including: monitoring a processing device's acquisition operation on an order to be processed; determining multiple attribute values ​​of the acquisition operation based on a monitoring result, so as to generate pre-operation attribute values ​​for the order to be processed based on the multiple attribute values; performing a risk control check on a user account that logs into the processing device based on the pre-operation attribute values; detecting that the user account has passed the risk control check, confirming that the processing device continues to process the order to be processed; detecting that the user account has not passed the risk control check, releasing the order to be processed to a corresponding order grabbing area.

[0008] In some embodiments of the present disclosure, multiple attribute values ​​of the acquisition operation are determined based on monitoring results to generate pre-operation attribute values ​​for the pending order based on the multiple attribute values, including: determining the consistency attribute value of the acquisition operation based on the monitoring results as a first attribute value; determining the frequency attribute value of the processing device's refresh operation on the grab order area based on the monitoring results as a second attribute value; determining the parallel operation attribute value of the acquisition operation based on the monitoring results as a third attribute value; and obtaining the pre-operation attribute value based on the first attribute value, the second attribute value, and the third attribute value.

[0009] In some embodiments of the present disclosure, a consistency attribute value of the acquisition operation is determined based on the monitoring result as a first attribute value, including: determining the processing field to which the pending order belongs; determining whether the pending order is obtained by the processing device in an order grabbing area corresponding to the processing field based on the monitoring result; if the order is obtained by grabbing an order in the order grabbing area corresponding to the processing field, the first attribute value is configured to 1; if the order is not obtained by grabbing an order in the order grabbing area corresponding to the processing field, the first attribute value is configured to 0.

[0010] In some embodiments of the present disclosure, determining whether the pending order is obtained by the processing device in the order grabbing area corresponding to the processing field based on the monitoring result includes: detecting whether the background has recorded the order grabbing mark of the processing device for the pending order based on the monitoring result; if there is the order grabbing mark, detecting whether the order grabbing mark is consistent with the field mark of the order grabbing area and the field mark of the processing device; determining whether the pending order is obtained by the processing device in the order grabbing area based on the detection result.

[0011] In some embodiments of the present disclosure, the frequency attribute value of the processing device's refresh operation on the grab order zone is determined based on the monitoring result as the second attribute value, including: the monitoring result includes a first monitoring result, and the second attribute value of the refresh operation of the grab order zone is calculated based on the first monitoring result, wherein the first monitoring result is generated based on the operation of the processing device to refresh the grab order zone within a sliding time window.

[0012] In some embodiments of the present disclosure, the second attribute value of the order grabbing zone refresh operation is calculated based on the first monitoring result, including: monitoring the operation of the processing device to refresh the order grabbing zone based on multiple sliding time windows of different lengths, obtaining the refresh frequency of the order grabbing zone in the corresponding sliding time window, and the average frequency of the order grabbing zone in the sliding time windows of multiple different lengths; and obtaining the second attribute value based on the refresh frequency and the average frequency.

[0013] In some embodiments of the present disclosure, obtaining the second property value based on the refresh frequency and the average frequency includes: calculating the second property value based on a first calculation formula.

[0014] Among them, the first calculation formula is F1 is the second attribute value, μ i is the refresh frequency of the order grabbing area in the i-th sliding time window, μ avg is the average frequency, and N1 is the number of the sliding time windows.

[0015] In some embodiments of the present disclosure, the further step includes: detecting that the second attribute value is greater than a first risk threshold, marking the login account of the processing device as a risky script doctor.

[0016] In some embodiments of the present disclosure, the parallel operation attribute value of the acquisition operation is determined based on the monitoring result as a third attribute value, including: the monitoring result includes a second monitoring result, monitoring the processing actions of the processing device on the pending orders at multiple times as the second monitoring result; based on the second monitoring result, detecting the number of the processing actions at the same time; and determining the third attribute value based on the number of the processing actions.

[0017] In some embodiments of the present disclosure, the order to be processed is a consultation order of an Internet hospital, and the action sequence of the processing device for processing the consultation order includes grabbing the order, receiving the consultation, user reply and prescribing.

[0018] In some embodiments of the present disclosure, determining the third attribute value based on the number of the processing actions includes: calculating the third attribute value based on a second calculation formula.

[0019] Among them, the second calculation formula is F2 is the third attribute value, N2 is the number of the multiple moments, T i The number of processing actions described below.

[0020] In some embodiments of the present disclosure, a risk control check is performed on the user account that logs into the processing device based on the pre-operation attribute value, including: configuring a first weight for the second attribute value, and configuring a second weight for the third attribute value; if the first attribute value is configured to 1, then based on the second attribute value, the first weight, the third attribute value and the second weight, the pre-operation attribute value is obtained; and a risk control check is performed based on the relationship between the pre-operation attribute value and the second risk threshold.

[0021] In some embodiments of the present disclosure, it also includes: if the first attribute value is configured as 0, determining that the processing device has not passed the risk control verification.

[0022] In some embodiments of the present disclosure, the further step includes: detecting that the processing device has not passed the risk control check, and feeding back an error code indicating a failed consultation to the processing device.

[0023] In some embodiments of the present disclosure, it also includes: detecting that the processing device has not passed the risk control verification, generating a risk record for the user account; detecting that the number of risk records reaches a quantity threshold, determining the user account as a risk account.

[0024] According to another aspect of the present disclosure, there is provided an order processing device, comprising: a detection module, for monitoring the acquisition operation of a processing device on an order to be processed; a determination module, for determining multiple attribute values ​​of the acquisition operation based on the monitoring result, so as to generate pre-operation attribute values ​​for the order to be processed based on the multiple attribute values; a verification module, for performing a risk control verification on a user account that logs in to the processing device based on the pre-operation attribute values; a confirmation module, for detecting that the user account has passed the risk control verification, and confirming that the processing device continues to process the order to be processed; and a release module, for detecting that the user account has not passed the risk control verification, and releasing the order to be processed to a corresponding order grabbing area.

[0025] According to another aspect of the present disclosure, there is provided an electronic device, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any one of the above-mentioned order processing methods by executing the executable instructions.

[0026] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, any one of the above-mentioned order processing methods is implemented.

[0027] According to another aspect of the present disclosure, a computer program product is provided, on which a computer program is stored, and when the computer program is executed by a processor, any one of the above-mentioned order processing methods is implemented.

[0028] The order processing solution provided by the embodiments of the present disclosure immediately starts the risk control verification mechanism when it detects that a processing device has obtained a pending order. By analyzing the pre-operation attribute values ​​related to the pending order, based on these pre-operation attribute values, a risk control verification is performed on the user account that logs into the processing device. If the risk control verification fails, it indicates that the account is risky and the account is not allowed to process orders. On the one hand, it is conducive to combating the behavior of doctors handing over accounts to irregular institutions and using plug-ins to grab orders. On the other hand, it is conducive to reducing the occurrence of unauthorized pending orders to ensure the reliability of order processing, which in turn helps to improve users' trust and satisfaction with related platforms.

[0029] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0031] Figure 1 A schematic diagram showing the structure of an order processing system in an embodiment of the present disclosure;

[0032] Figure 2 A flowchart showing an order processing method in an embodiment of the present disclosure is shown;

[0033] Figure 3 A flowchart showing another order processing method in an embodiment of the present disclosure;

[0034] Figure 4 A schematic diagram showing an order processing solution in an embodiment of the present disclosure;

[0035] Figure 5 A flowchart showing another order processing method in an embodiment of the present disclosure is shown;

[0036] Figure 6 A schematic diagram showing an order processing device according to an embodiment of the present disclosure;

[0037] Figure 7 A schematic diagram of an electronic device in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0038] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and to fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0039] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0040] With the rapid development of Internet medical care, Internet hospitals have become one of the important ways for people to seek medical treatment. Taking online drug purchase as an example, users need prescriptions to purchase prescription drugs. Internet hospitals provide a convenient platform for users and doctors to communicate online and issue prescriptions by receiving medical treatment orders. Internet hospitals match users with qualified doctors based on the patient's condition. Online doctors obtain medical treatment orders by grabbing orders, provide diagnosis and treatment for users, and issue prescription suggestions.

[0041] The doctor's processing equipment can obtain user consultation orders by grabbing orders from the platform. However, some doctors use black market methods such as plug-ins to hand over their accounts to black market teams to accept orders in an illegal manner, and use scripts to mechanically answer questions and prescribe medicine. These orders are not within the scope of the doctor's available consultation orders. The use of black market methods to overstep authority to accept consultation orders poses a great risk to the serious consultation of the Internet hospital platform and a very bad user experience to users. Since there is no avoidance of risky doctor behavior, there is an urgent need for an order processing solution to reduce the probability of order brushing and ensure the compliance, healthy development and user experience of Internet hospitals.

[0042] Based on the above-mentioned defects, in the present disclosure, when it is detected that a processing device has obtained a pending order, the risk control verification mechanism is immediately started. By analyzing the pre-operation attribute values ​​related to the pending order, the user account that logs into the processing device is subjected to risk control verification based on these pre-operation attribute values. If the risk control verification fails, it indicates that the account is at risk and the account is not allowed to process orders. On the one hand, it is conducive to combating the behavior of doctors handing over accounts to irregular institutions and using plug-ins to grab orders. On the other hand, it is conducive to reducing the occurrence of unauthorized pending orders to ensure the reliability of order processing, which in turn is conducive to improving users' trust and satisfaction with relevant platforms.

[0043] To facilitate understanding, several terms involved in this application are first explained below.

[0044] Internet Hospital: A new type of medical institution that uses Internet technology to provide medical services, with features such as remote diagnosis and treatment and smart medicine.

[0045] Fake orders: In scenarios such as Internet hospitals, fake orders refer to doctors or related personnel creating the illusion of transactions or services through false means. For example, doctors hand over their accounts to irregular institutions, which use plug-ins to grab orders and then conduct fake consultations, mechanical Q&A, and prescriptions. In fact, they do not really provide effective medical services to patients. Their purpose may be to obtain improper benefits, such as increasing the number of orders received by doctors and the rate of favorable comments, so as to obtain more exposure and rewards on the platform.

[0046] In e-commerce and other fields, fake orders refer to merchants hiring people to falsely purchase goods and give positive reviews in order to increase the store's sales and credibility.

[0047] Figure 1 1 is a schematic diagram of the structure of a computer system provided by an exemplary embodiment of the present application. The system includes: a plurality of terminals 120 and a server cluster 140, wherein the terminal 120 is a processing device, and the server cluster 140 is used to execute the order processing method.

[0048] The terminal 120 may be a mobile terminal such as a mobile phone, a game console, a tablet computer, an e-book reader, smart glasses, an MP4 (Moving Picture Experts Group Audio Layer IV) player, a smart home device, an AR (Augmented Reality) device, a VR (Virtual Reality) device, or the terminal 120 may also be a personal computer (PC), such as a laptop computer and a desktop computer.

[0049] The terminal 120 may be installed with an application for providing order processing.

[0050] The terminal 120 is connected to the server cluster 140 via a communication network. Optionally, the communication network is a wired network or a wireless network.

[0051] The server cluster 140 is a server, or is composed of several servers, or is a virtualization platform, or is a cloud computing service center. The server cluster 140 is used to provide background services for the application program that provides order processing. Optionally, the server cluster 140 undertakes the main computing work, and the terminal 120 undertakes the secondary computing work; or, the server cluster 140 undertakes the secondary computing work, and the terminal 120 undertakes the main computing work; or, the terminal 120 and the server cluster 140 adopt a distributed computing architecture for collaborative computing.

[0052] In some optional embodiments, server cluster 140 is used to store order processing program information.

[0053] Optionally, the logistics user terminals of the application programs installed in different terminals 120 are the same, or the logistics user terminals of the application programs installed on the two terminals 120 are logistics user terminals of the same type of application programs on different control system platforms. Based on the different terminal platforms, the specific forms of the logistics user terminals of the application programs may also be different, for example, the logistics user terminals of the application programs may be mobile phone logistics user terminals, PC logistics user terminals, or global wide area network (World Wide Web, Web) logistics user terminals, etc.

[0054] Those skilled in the art will appreciate that the number of the terminals 120 may be more or less. For example, there may be only one terminal, or there may be dozens or hundreds of terminals, or a greater number. The embodiment of the present application does not limit the number and device type of the terminals.

[0055] Optionally, the system may also include a management device ( Figure 1 (not shown), the management device is connected to the server cluster 140 via a communication network. Optionally, the communication network is a wired network or a wireless network.

[0056] Optionally, the above-mentioned wireless network or wired network uses standard communication technology and / or protocol. The network is usually the Internet, but it can also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a dedicated network or any combination of a virtual private network). In some embodiments, the data exchanged through the network is represented by technologies and / or formats including Hyper Text Mark-up Language (HTML), Extensible Markup Language (XML), etc. In addition, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), Internet Protocol Security (IPsec) can also be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technologies can also be used to replace or supplement the above-mentioned data communication technologies.

[0057] Exemplarily, in the present disclosure, the order processing system includes a task center, a scheduling center, and a configuration center.

[0058] The order processing method in this example implementation will be described in more detail below with reference to the accompanying drawings and embodiments.

[0059] like Figure 2 As shown, an order processing method according to an embodiment of the present disclosure is applied to the server of the platform, including:

[0060] Step S202, monitoring the processing device's acquisition operation on the order to be processed.

[0061] In some embodiments, the server backend can monitor the acquisition operation of the pending orders by monitoring the order submission time in the message queue.

[0062] In some embodiments, monitoring code may also be inserted into the order grabbing software of the processing device to monitor the acquisition operation of the order to be processed.

[0063] Step S204: determining multiple attribute values ​​of the acquisition operation based on the monitoring result, so as to generate a pre-operation attribute value for the order to be processed based on the multiple attribute values.

[0064] Among them, the multiple attribute values ​​can be understood as a series of key indicators and characteristic values ​​used to perform risk control verification on the user account that logs into the processing device after the processing device obtains the pending order and before processing the pending order.

[0065] In some embodiments, taking the Internet hospital as an example, the processing device is a terminal for processing Internet medical treatment orders, the user account is a doctor's qualification account, and the processing field is the department to which the doctor belongs.

[0066] In some embodiments, pre-operation attribute values ​​may include attribute values ​​of consistency operations, where consistency operations include but are not limited to professional field consistency and operating habit consistency, among which professional field consistency is used to detect whether the department to which orders previously processed by the doctor's account belong is consistent with the department of the current order to be processed, and operating habit consistency includes consistency in the time distribution of the doctor's answers to questions, the frequency of prescribing, the way of communicating with patients, etc.

[0067] In some embodiments, the pre-operation attribute value may also include an attribute value generated based on the refresh frequency of the order grabbing area. A reasonable refresh frequency range of the order grabbing area is determined based on the operation data of a large number of normal doctors. If an account continuously refreshes the order grabbing area in a short period of time, exceeding the refresh frequency range, it may be using a plug-in program or being manipulated by an informal organization in an attempt to grab the order as quickly as possible. This abnormal behavior will interfere with the normal order of the platform and bring risks to patients.

[0068] In some embodiments, pre-operation attribute values ​​may also include attribute values ​​generated based on parallel behavior detection, such as detecting whether a doctor account is processing multiple orders at the same time and there are obvious conflicts in time between these orders, or detecting whether there are conflicts in professional fields between the orders processed by the doctor account.

[0069] In some embodiments, the order processing solution can also be applied to the field of takeout order grabbing.

[0070] Step S206: Perform risk control verification on the user account that logs into the processing device based on the pre-operation attribute value.

[0071] The pre-operation attribute value reflects the operation attribute of the processing device related to the acquisition operation of the order to be processed. Based on the pre-operation attribute value, whether the acquisition operation is reasonable can be measured.

[0072] In some embodiments, the pre-operation attribute value may be input into a risk assessment model for risk assessment to determine whether the user account is at risk.

[0073] Step S208: Detect that the user account has passed the risk control verification, and confirm that the processing device continues to process the pending order.

[0074] In some embodiments, if the user account passes the risk control verification, it means that the account is compliant in processing the order. At this time, a specified signal can be sent to the processing device, allowing the processing device to continue processing the pending order.

[0075] Step S210: If it is detected that the user account has not passed the risk control verification, the pending order will be released to the corresponding order grabbing area.

[0076] In some embodiments, if the user account fails the risk control check, it means that the account may be risky and is not suitable for processing the current order. At this time, the pending order will be released to the corresponding order grabbing area.

[0077] In some embodiments, orders in the order grabbing area will be displayed to other eligible doctor accounts, and these doctors can choose to grab the orders based on their own professional areas and schedules.

[0078] In this embodiment, by monitoring the order acquisition operation of the processing device and performing risk control verification based on the pre-operation attribute values, when it is detected that a processing device has acquired an order to be processed, the risk control verification mechanism is immediately started. Through the detection results, multiple attribute values ​​of the order acquisition operation can be obtained, and pre-operation attribute values ​​are generated based on these attribute values. The pre-operation attribute values ​​related to the order to be processed are analyzed, and based on these pre-operation attribute values, a risk control verification is performed on the user account that logs into the processing device. If the risk control verification fails, it indicates that the account is risky and the account is not allowed to process orders. On the one hand, it is beneficial to combat the behavior of doctors handing over accounts to irregular institutions and using plug-ins to grab orders. On the other hand, it is beneficial to reduce the occurrence of unauthorized pending orders to ensure the reliability of order processing, which in turn is beneficial to improving users' trust and satisfaction with related platforms.

[0079] like Figure 3 As shown, in some embodiments of the present disclosure, multiple attribute values ​​of the acquisition operation are determined based on the monitoring result, so as to generate a pre-operation attribute value for the order to be processed based on the multiple attribute values, including:

[0080] Step S302: determining a consistency attribute value of the acquisition operation based on the monitoring result as a first attribute value.

[0081] In some embodiments, when it is detected based on the monitoring results that the processing device obtains an order to be processed, the consistency attribute value of the processing device for the order to be processed is obtained, that is, the attribute value of the consistency operation. The consistency operation may include whether the way the processing device obtains the order is based on the standard operating procedure. Through the monitoring results, the consistency attribute value reflecting the degree of consistency of the processing device's operation on the order to be processed can be obtained as the first attribute value.

[0082] Step S304: determining the frequency attribute value of the refresh operation of the order grabbing area by the processing device based on the monitoring result as the second attribute value.

[0083] In some embodiments, the monitoring results include the results of monitoring the operation of the processing device refreshing the order grabbing area. The frequency attribute value of the order grabbing area refresh operation includes but is not limited to the attribute values ​​obtained by monitoring the refresh frequency, refresh duration, and behavior patterns during the refresh process. If the processing device frequently and abnormally refreshes the order grabbing area, it may indicate the presence of improper order grabbing behavior. The frequency attribute value is obtained by analyzing these data as the second attribute value.

[0084] Step S306: Determine the parallel operation attribute value of the acquisition operation based on the monitoring result as the third attribute value.

[0085] In some embodiments, the parallel operation attribute value is used to detect whether the processing device is performing multiple operations that may conflict with each other at the same time. In the Internet hospital scenario, doctors should usually focus on processing one order at a time. If the processing device performs multiple operations in parallel such as refreshing the order grabbing area, seeing patients, replying to patients and prescribing, it indicates abnormal operation.

[0086] Step S308: obtaining a pre-operation attribute value based on the first attribute value, the second attribute value, and the third attribute value.

[0087] In some embodiments, the first attribute value, the second attribute value, and the third attribute value are comprehensively calculated based on risk control rules to obtain pre-operation attribute values. The pre-operation attribute values ​​can reflect the overall risk level of the processing equipment before processing the pending order, so as to perform risk control verification based on the pre-operation attribute values, thereby facilitating ensuring the seriousness and compliance of the consultation process of the Internet hospital platform.

[0088] In some embodiments, the risk identification of Internet doctors' behavior of refreshing the order-grabbing area can be analyzed from multiple dimensions, including the consistency of the doctor's operation data, the frequency of the doctor's refreshing the order-grabbing area, the doctor's refresh time, the speed of interaction between refreshing the order-grabbing area and receiving the patient, etc., and finally the doctor's risk score is calculated as a pre-operation attribute value to provide abnormal prompts for doctors with a higher risk of cheating.

[0089] In this embodiment, multi-dimensional attribute values ​​are obtained by performing multi-dimensional monitoring on the acquisition operation of the processing device as pre-operation attribute values. Based on the pre-operation attribute values, possible improper operation behaviors can be effectively identified, such as institutions using plug-ins to grab orders, mechanical questions and answers, and prescriptions, etc. This helps to maintain the seriousness of consultations on the Internet hospital platform and ensure that the doctor's diagnosis and treatment process is based on professional knowledge rather than mechanical processing through scripts, thereby ensuring the system security and stable operation of the platform while improving the user experience.

[0090] In some embodiments of the present disclosure, determining a consistency attribute value of an acquisition operation based on a monitoring result as a first attribute value includes:

[0091] Determine the processing area to which the pending order belongs.

[0092] Among them, the processing field can be the doctor's treatment field, that is, one treatment field can correspond to one order-grabbing area.

[0093] Based on the monitoring results, determine whether the order to be processed is obtained by the processing device in the order-grabbing area corresponding to the processing field; if it is obtained by grabbing the order in the order-grabbing area corresponding to the processing field, the first attribute value is configured to 1; if it is not obtained by grabbing the order in the order-grabbing area corresponding to the processing field, the first attribute value is configured to 0.

[0094] In some embodiments, in order to prevent doctors from accepting orders that do not belong to them by unauthorized treatment, a doctor's operation consistency risk score OptRiskScore is established in the order grabbing area as the first attribute value. The data consistency operation score refers to the verification of whether the order that the doctor grabs is refreshed from the doctor's order grabbing area during a single doctor's treatment operation, thereby ensuring the consistency and continuity of the doctor's refresh and treatment operations. The calculation of OptRiskScore is shown in formula (1).

[0095]

[0096] Among them, if it is detected that the doctor did not refresh the order from the order grabbing area, then the doctor’s risk score is 0, and the doctor will be intercepted when seeing the patient, so as to ensure the consistency of the doctor’s operation.

[0097] In this embodiment, the server constructs a verification mechanism for grabbing orders, and ensures the compliance of the user operation process by dispatching orders based on the order sequence of user requests. If the order is not refreshed from the grabbing order area, the doctor cannot see the patient, thereby ensuring data consistency between multiple scattered interfaces. When dispatching orders, it will ensure that orders from different departments are dispatched to suitable doctors in different departments. Therefore, the doctor can only see the orders refreshed from his own grabbing order area, preventing the illegal acquisition of orders through black production methods for seeing patients.

[0098] In some embodiments of the present disclosure, determining whether the to-be-processed order is obtained by grabbing an order in an order grabbing area corresponding to a processing field by a processing device based on the monitoring result includes:

[0099] Based on the monitoring results, it is detected whether the background records the order grabbing mark of the processing device for the order to be processed; if there is an order grabbing mark, it is detected whether the order grabbing mark is consistent with the field mark of the order grabbing area and the field mark of the processing device; based on the detection results, it is determined whether the order to be processed is obtained by the processing device in the order grabbing area.

[0100] Among them, the order grabbing mark refers to a mark generated when a processing device (such as a doctor's terminal device, etc.) performs an order grabbing operation. That is to say, by detecting the order grabbing mark, it can be confirmed whether the processing device has actually performed the order grabbing operation.

[0101] In some embodiments, the implementation process of the verification mechanism for grabbing orders includes: when the doctor end A refreshes the grab order area, if order O1 and order O2 are refreshed from the grab order area, then the server end will record the doctor's refresh records to order O1 and order O2 in the background, such as writing cache marks AO1 and AO2 as order grabbing identifiers. When the doctor end A receives order O1, it verifies whether the doctor has ever refreshed order O1. At this time, by constructing a cache identifier AO1, if the identifier exists, the doctor's identity authentication is passed, so the doctor can receive the order normally. At this time, if the doctor end B receives order O1 through illegal channels, it detects whether the cache identifier BO1 exists. If BO1 does not exist, it can be determined that the doctor end B cannot receive this order, and returns an error message to the doctor, informing the doctor that the order has been snatched away, thereby preventing the doctor from obtaining orders through illegal means and directly receiving orders by calling the interface through scripts.

[0102] In this embodiment, by detecting whether the background has recorded the order grabbing mark of the processing device for the order to be processed based on the monitoring results, the order grabbing mark can be a mark automatically generated and recorded by the server when the processing device successfully grabs the order, so as to detect whether the acquired order is obtained through the order grabbing behavior. If the order grabbing mark is detected, then check whether the order grabbing mark is consistent with the field mark of the order grabbing area and the field mark of the processing device. By comparing the marks, it can be determined whether the order belongs to the field corresponding to the order grabbing area, and whether the processing device is qualified to process orders in this field, which is conducive to preventing unfair competition and illegal operations.

[0103] In some embodiments of the present disclosure, determining the frequency attribute value of the refresh operation of the order grabbing area by the processing device based on the monitoring result as the second attribute value includes:

[0104] The monitoring result includes a first monitoring result, and a second attribute value of the order grabbing area refresh operation is calculated based on the first monitoring result, wherein the first monitoring result is generated based on the operation of refreshing the order grabbing area of ​​the processing device within the sliding time window.

[0105] In some embodiments, in terms of the refresh frequency on the doctor's side, the number of times the doctor's side refreshes the order grabbing area within the configured time period is monitored, and abnormal behavior is discovered by calculating the consistency of the refresh frequency. If the doctor's refresh frequency is too high for a period of time and remains at a constant frequency, the refresh frequency risk factor on the doctor's side is considered to be high.

[0106] In this embodiment, a sliding time window is configured to monitor the operation of the processing device refreshing the order grabbing area within a continuous time range so as to promptly detect abnormal behavior. A second attribute value is calculated based on the first monitoring result, i.e., the operation data of the processing device refreshing the order grabbing area within the sliding time window. This attribute value can be used to measure the rationality and abnormality of the operation of the processing device refreshing the order grabbing area, and is conducive to promptly detecting abnormal behavior.

[0107] In some embodiments of the present disclosure, calculating the second attribute value of the order grabbing area refresh operation based on the first monitoring result includes:

[0108] Based on multiple sliding time windows of different lengths, the operation of the processing device to refresh the order grabbing area is monitored respectively, and the refresh frequency of the order grabbing area in the corresponding sliding time window and the average frequency of the order grabbing area in the multiple sliding time windows of different lengths are obtained; the second attribute value is obtained based on the refresh frequency and the average frequency.

[0109] In some embodiments, Figure 4 As shown, based on the first monitoring result, data analysis is performed on the frequency of the doctor's side refreshing the order-grabbing area. If the doctor's side continuously refreshes the order-grabbing area, and the refresh frequency per minute remains basically consistent and uninterrupted for a long time, it is obviously not something that the doctor can do manually. By using sliding time windows of different lengths to scan the time series records of the doctor refreshing the order-grabbing area, the mean and variance of the doctor's refresh order-grabbing area in different sliding time windows are calculated. If the mean of multiple consecutive time periods is maintained within a relatively stable range, it can be regarded as a high suspicion of cheating on the doctor's side.

[0110] In some embodiments of the present disclosure, obtaining the second attribute value based on the refresh frequency and the average frequency includes: calculating the second attribute value based on a first calculation formula, where the first calculation formula is shown in formula (2):

[0111]

[0112] Among them, F1 is the second attribute value, μ i is the average refresh frequency of the order grabbing area in the i-th sliding time window, μ avg is the average frequency, and N1 is the number of sliding time windows.

[0113] In some embodiments, the frequency risk score value F1, i.e., the second attribute value, is between 0 and 100, where 100 indicates that the refresh frequencies in all time windows are completely consistent, and 0 indicates that the refresh frequencies are completely inconsistent. For example, three sliding time windows are configured, and their average refresh frequencies are μ1, μ2, and μ3, respectively, and the overall average frequency is μ avg , then the frequency risk score value F1 is as shown in formula (3).

[0114] F1= (1 - (|μ1 - μ avg | + |μ2 - μ avg | + |μ2 - μ avg |) / (3 *μ avg )) * 100 (3)

[0115] In some embodiments of the present disclosure, the further step includes: detecting that the second attribute value is greater than the first risk threshold, marking the login account of the processing device as a risk script doctor.

[0116] Among them, the first risk threshold refers to the threshold for measuring whether the doctor's account is running based on a script. The first risk threshold can be set based on factors such as the system's normal operating experience, historical data, and risk tolerance.

[0117] In this embodiment, by detecting the consistency of the refresh frequency of the doctor's side in different time windows, if the second attribute value is high, it indicates that the refresh consistency of the doctor's side is very high, and there is a greater risk of being a risky script doctor.

[0118] In some embodiments of the present disclosure, determining the parallel operation attribute value of the acquisition operation as the third attribute value based on the monitoring result includes:

[0119] The monitoring results include a second monitoring result, which monitors the processing actions of the processing equipment on the order to be processed at multiple times as the second monitoring result; detects the number of processing actions at the same time based on the second monitoring result; and determines the third attribute value based on the number of processing actions.

[0120] In this embodiment, at different time points, the processing actions of the processing device on the orders to be processed are continuously monitored to obtain a second monitoring result. For each monitored moment, the number of processing actions simultaneously performed by the processing device at that moment is determined. If the processing device performs multiple actions simultaneously at the same moment, the third attribute value is determined based on the number of processing actions detected at the same moment. Based on the third attribute value, it can be determined whether a processing device has abnormal operation behavior of processing multiple orders simultaneously, which is conducive to preventing improper operation behavior from disrupting the normal order of the platform and ensuring that all processing devices process orders in a fair environment.

[0121] In some embodiments of the present disclosure, the order to be processed is a consultation order of an Internet hospital, and the action sequence of the processing device for processing the consultation order includes grabbing the order, receiving the consultation, user reply and prescribing.

[0122] In some embodiments of the present disclosure, determining the third attribute value based on the number of processing actions includes: calculating the third attribute value based on a second calculation formula, where the second calculation formula is shown in formula (4).

[0123]

[0124] Among them, F2 is the third attribute value, N2 is the number of multiple moments, T i The number of actions to be processed.

[0125] In some embodiments, the doctor can only perform one action of refreshing the order grabbing area, seeing patients, user replying or prescribing at the same time. If the doctor refreshes the order grabbing area, seeing patients, replying and prescribing at least two of the actions at the same time, it can be regarded as the doctor's end cheating the software. Therefore, data monitoring and identification are performed on the key links of the doctor's operation path. The doctor's actions of refreshing the order grabbing area, seeing patients, user replying and prescribing are recorded as a1, a2, a3 and a4 respectively. The data of the doctor's actions a1, a2, a3 and a4 at N2 seconds at T1, T2...Tn are collected, and the repetition risk score of the doctor's action operation, that is, the third attribute value F2, is calculated. If the doctor performs 4 actions at the same time, the risk score is high. If the execution of these actions is scattered, the risk score is low.

[0126] In this embodiment, the doctor's parallel operation risk score is calculated by the second calculation formula as the third attribute value. If certain processing devices attempt to quickly obtain orders or perform improper operations by performing multiple actions at the same time, the platform can quickly identify and mark them as high risk. This helps prevent doctors from handing over their accounts to irregular institutions and prevents these institutions from using plug-ins to grab orders and conduct mechanical questions and answers and prescribe medicines, thereby reducing the damage caused to the platform and patients by fraudulent behavior.

[0127] In some embodiments of the present disclosure, risk control verification is performed on a user account of a login processing device based on a pre-operation attribute value, including:

[0128] A first weight is configured for the second attribute value, and a second weight is configured for the third attribute value; if the first attribute value is configured to 1, a pre-operation attribute value is obtained based on the second attribute value, the first weight, the third attribute value, and the second weight; and a risk control check is performed based on the relationship between the pre-operation attribute value and the second risk threshold.

[0129] In some embodiments, the doctor's risk score is used as a pre-operation attribute value, which may include three indicators, namely, the doctor's operation consistency risk score (first attribute value), the order frequency risk score (second attribute value), and the doctor's operation parallelism risk score (third attribute value). The doctor's comprehensive risk score is calculated by weighted calculation of the doctor's risk score. If it exceeds the specified threshold, risk control interception will be carried out and the doctor's service will be removed from the shelves.

[0130] In some embodiments of the present disclosure, it also includes: if the first attribute value is configured as 0, it is determined that the processing device has not passed the risk control verification.

[0131] In some embodiments, the physician risk score is calculated as shown in formula (5).

[0132] RiskScore=OptRiskScore*(x1F1+x2F2) (5)

[0133] Among them, RiskScore is the pre-operation attribute value, OptRiskScore is the first attribute value, F1 is the second attribute value, F2 is the third attribute value, x1 is the first weight, and x2 is the second weight.

[0134] In some embodiments of the present disclosure, the further step includes: detecting that the processing device has not passed the risk control check, and feeding back an error code indicating a failed consultation to the processing device.

[0135] In some embodiments of the present disclosure, it also includes: detecting that the processing device has not passed the risk control verification, generating a risk record for the user account; detecting that the number of risk records reaches a quantity threshold, and determining the user account as a risk account.

[0136] Among them, risk records include information collected and reported on doctors refreshing the order-grabbing area and their behaviors during consultations.

[0137] In this embodiment, taking the Internet hospital as an example, risk records of user accounts are generated based on the risk doctor identification model and the number of risk records is detected. Risky doctors can be identified by analyzing the doctors' behavior, avoiding compliance risks and unfairness of order brushing caused by potential illegal behaviors of doctors. On the basis of risk control verification based on multi-dimensional pre-operation attribute values, if the number of times the risk control verification of the user account fails reaches a quantitative threshold, the doctor account can be determined as a risky doctor, and the doctor account can be further blacklisted or cancelled.

[0138] like Figure 5 As shown, an order processing method according to another embodiment of the present disclosure includes:

[0139] Step S502, placing the received medical treatment order into the order grabbing area, receiving the refresh operation of the doctor terminal on the order grabbing area and sending the order grabbed by the doctor terminal based on the refresh operation to the doctor terminal.

[0140] In some embodiments, in an Internet hospital, after a user consults and places an order, the order is placed in multiple doctors' order grabbing areas through the order dispatching system. The doctor refreshes the order grabbing area, and the system returns the order refreshed to the doctor. The doctor then starts the consultation between the user and the doctor through the consultation order.

[0141] Step S504: When it is detected that the doctor terminal has obtained the medical consultation order, the operation consistency risk score, the refresh frequency risk score of the order grabbing area and the operation parallelism risk score related to the medical consultation order are calculated based on the risk control model.

[0142] Among them, the consistency risk score corresponds to the consistency attribute value, the refresh frequency risk score corresponds to the frequency attribute value, and the operation parallelism risk score corresponds to the parallel operation attribute value.

[0143] Step S506, calculating the pre-operation attribute value based on the operation consistency risk score, the refresh frequency risk score of the order grabbing area, and the operation parallelism risk score.

[0144] In some embodiments, a risk control verification model is constructed in the doctor's consultation process to construct a doctor's risk score. If the doctor's risk score is greater than a specified threshold, the doctor is prohibited from seeing patients, thereby preventing the doctor from defaulting on the consultation order.

[0145] Step S508, if the pre-operation attribute value is greater than or equal to the risk threshold, the risk control check fails and an error code is returned to the doctor terminal.

[0146] Step S510: If the pre-operation attribute value is less than the risk threshold, the risk control verification is successful and a signal allowing processing is sent to the doctor terminal.

[0147] Step S512: If the risk control verification fails, a risk record for the doctor's account is generated.

[0148] Step S514: If it is detected that the number of risk records reaches a threshold, the doctor account is identified as a risky doctor and the platform intervenes.

[0149] In some embodiments, the risky doctor identification model identifies risky doctors by analyzing the doctors' behavior and by establishing a risky doctor identification mechanism to identify risky doctors, thereby enabling earlier intervention on platform doctors, such as doctor education or service removal.

[0150] In this embodiment, the doctor risk behavior analysis based on Internet business judges the consistency of the doctor's operations and collects and reports the doctor's behavior when refreshing the order grabbing area and receiving patients, providing the necessary basic data for the doctor's behavior analysis, such as the doctor's behavior in the order grabbing area, reception information, etc.

[0151] Among them, the platform is an Internet hospital platform.

[0152] In some embodiments, in the field of rider delivery, when the rider's processing device (usually a mobile terminal such as a mobile phone) obtains a pending order, the system begins to perform risk control verification on the user account (i.e., the rider account) that logs into the processing device based on the pre-operation attribute values ​​related to the pending order.

[0153] Pre-operational attribute values ​​include, but are not limited to:

[0154] The rider’s recent frequency of orders. If the rider frequently receives orders in a short period of time, there may be an abnormality.

[0155] The matching degree between the rider’s location information and the orders, such as whether the rider frequently receives orders in unreasonable locations.

[0156] The behavioral characteristics of the device, such as whether the device has abnormal operating modes, such as quickly switching order status.

[0157] If it is detected that the user account has passed the risk control verification, that is, it is judged that the rider's operation is normal and there is no suspicion of fake orders, and it is confirmed that the processing device (the rider's mobile phone) can continue to process the pending order, the rider can deliver the order according to the normal process, including going to the pickup location and delivering the goods to the destination.

[0158] If it is detected that the user account has not passed the risk control verification, it is judged that the rider may have engaged in fake orders. At this time, the pending order will be released to the corresponding order grabbing area, allowing other normal riders to have the opportunity to obtain the order. At the same time, the system can further investigate and process the rider account, such as temporarily restricting its order acceptance authority, recording abnormal behavior, etc., to prevent it from continuing to engage in fake orders.

[0159] It should be noted that the above figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It is easy to understand that the processes shown in the above figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0160] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0161] Refer to the following Figure 6 The order processing device 600 according to this embodiment of the present disclosure is described. Figure 6 The order processing device 600 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.

[0162] The order processing device 600 is in the form of a hardware module. The components of the order processing device 600 may include but are not limited to: a detection module 602, which is used to monitor the processing device's acquisition operation of the pending order; a determination module 604, which is used to determine multiple attribute values ​​of the acquisition operation based on the monitoring results, so as to generate pre-operation attribute values ​​for the pending order based on the multiple attribute values; a verification module 606, which is used to perform risk control verification on the user account that logs into the processing device based on the pre-operation attribute value; a confirmation module 608, which is used to detect that the user account has passed the risk control verification and confirm that the processing device continues to process the pending order; a release module 610, which is used to detect that the user account has not passed the risk control verification and release the pending order to the corresponding order grabbing area.

[0163] Refer to the following Figure 7 An electronic device 700 according to this embodiment of the present disclosure is described. Figure 7 The electronic device 700 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0164] like Figure 7 As shown, the electronic device 700 is in the form of a general computing device. The components of the electronic device 700 may include but are not limited to: at least one processing unit 710, at least one storage unit 720, and a bus 730 connecting different system components (including the storage unit 720 and the processing unit 710).

[0165] The storage unit stores program codes, which can be executed by the processing unit 710, so that the processing unit 710 performs the steps according to various exemplary embodiments of the present disclosure described in the above “Exemplary Method” section of this specification. For example, the processing unit 710 can perform the following steps: Figure 2 Steps S202 and S204 shown in , and other steps defined in the order processing method of the present disclosure.

[0166] The storage unit 720 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 7201 and / or a cache storage unit 7202 , and may further include a read-only storage unit (ROM) 7203 .

[0167] The storage unit 720 may also include a program / utility 7204 having a set (at least one) of program modules 7205, such program modules 7205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0168] Bus 730 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0169] The electronic device 700 may also communicate with one or more external devices 760 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device, and / or may communicate with any device that enables the electronic device 700 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 750. Furthermore, the electronic device 700 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 750. As shown, the network adapter 750 communicates with other modules of the electronic device 700 via a bus 730. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0170] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0171] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present disclosure may also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary implementations of the present disclosure described in the above "Exemplary Method" section of the present specification.

[0172] According to the program product for implementing the above method in the embodiment of the present disclosure, it can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto. In this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0173] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a 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.

[0174] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0175] Program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may 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 may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0176] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0177] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0178] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0179] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.

Claims

1. An order processing method, characterized in that: include: Monitor the acquisition operation of processing equipment for pending orders; Determine multiple attribute values ​​of the acquisition operation based on the monitoring result, so as to generate pre-operation attribute values ​​for the to-be-processed order based on the multiple attribute values; Performing risk control verification on a user account that logs into the processing device based on the pre-operation attribute value; Detecting that the user account has passed the risk control verification, confirming that the processing device continues to process the pending order; It is detected that the user account has not passed the risk control verification, and the pending order is released to the corresponding order grabbing area.

2. The order processing method according to claim 1, characterized in that: Determining a plurality of attribute values ​​of the acquisition operation based on the monitoring result, so as to generate a pre-operation attribute value for the to-be-processed order based on the plurality of attribute values, comprises: Determine, based on the monitoring result, a consistency attribute value of the acquisition operation as a first attribute value; Determine, based on the monitoring result, a frequency attribute value of the processing device refreshing the order grabbing area as a second attribute value; Determine, based on the monitoring result, a parallel operation attribute value of the acquisition operation as a third attribute value; The pre-operational attribute value is obtained based on the first attribute value, the second attribute value, and the third attribute value.

3. The order processing method according to claim 2, characterized in that: Determining a consistency attribute value of the acquisition operation based on the monitoring result as a first attribute value includes: Determining the processing area to which the pending order belongs; Determine, based on the monitoring result, whether the pending order is obtained by the processing device in the order grabbing area corresponding to the processing field; If the order is obtained in the order grabbing area corresponding to the processing field, the first attribute value is configured as 1; If the order is not obtained in the order grabbing area corresponding to the processing field, the first attribute value is configured as 0.

4. The order processing method according to claim 3, characterized in that: Determining whether the pending order is obtained by the processing device in the order grabbing area corresponding to the processing field based on the monitoring result includes: Based on the monitoring result, it is detected whether the background records the order grabbing mark of the processing device for the pending order; If the order grabbing identifier is present, detecting whether the order grabbing identifier is consistent with the field identifier of the order grabbing area and the field identifier of the processing device; Based on the detection result, it is determined whether the pending order is obtained by the processing device in the order grabbing area.

5. The order processing method according to claim 2, characterized in that: Determining a frequency attribute value of the processing device refreshing the order grabbing area based on the monitoring result as a second attribute value includes: The monitoring result includes a first monitoring result, and a second attribute value of the order grabbing area refresh operation is calculated based on the first monitoring result. The first monitoring result is generated based on an operation of refreshing the order grabbing area of ​​the processing device within the sliding time window.

6. The order processing method according to claim 5, characterized in that: Calculating a second attribute value of the order grabbing area refresh operation based on the first monitoring result includes: Based on the sliding time windows of different lengths, the operations of the processing device refreshing the order grabbing area are monitored respectively, and the refresh frequency of the order grabbing area in the corresponding sliding time window and the average frequency of the order grabbing area in the sliding time windows of different lengths are obtained; The second attribute value is obtained based on the refresh frequency and the average frequency.

7. The order processing method according to claim 6, characterized in that: Obtaining the second attribute value based on the refresh frequency and the average frequency includes: Calculate the second attribute value based on the first calculation formula, Among them, the first calculation formula is F1 is the second attribute value, μ i is the refresh frequency of the order grabbing area in the i-th sliding time window, μ avg is the average frequency, and N1 is the number of the sliding time windows.

8. The order processing method according to claim 2, characterized in that: Also includes: It is detected that the second attribute value is greater than a first risk threshold, and the login account of the processing device is marked as a risky script doctor.

9. The order processing method according to claim 2, characterized in that: Determining a parallel operation attribute value of the acquisition operation based on the monitoring result as a third attribute value includes: The monitoring result includes a second monitoring result, which monitors the processing actions of the processing device on the to-be-processed order at multiple times as the second monitoring result; detecting the number of the processing actions at the same time based on the second monitoring result; The third attribute value is determined based on the number of the processing actions.

10. The order processing method according to claim 9, characterized in that: The pending order is a consultation order of an Internet hospital, and the action sequence of the processing device for processing the consultation order includes grabbing the order, consultation, user reply and prescribing.

11. The order processing method according to claim 9, characterized in that: Determining the third attribute value based on the number of the processing actions includes: Calculate the third attribute value based on the second calculation formula, Among them, the second calculation formula is F2 is the third attribute value, N2 is the number of the multiple moments, T i The number of processing actions described below.

12. The order processing method according to claim 2, characterized in that: Performing risk control verification on a user account that logs into the processing device based on the pre-operation attribute value includes: configuring a first weight for the second attribute value, and configuring a second weight for the third attribute value; If the first attribute value is configured as 1, the pre-operation attribute value is obtained based on the second attribute value, the first weight, the third attribute value and the second weight; A risk control check is performed based on the relationship between the pre-operation attribute value and the second risk threshold.

13. The order processing method according to claim 11, characterized in that: Also includes: If the first attribute value is configured as 0, it is determined that the processing device has not passed the risk control verification.

14. The order processing method according to any one of claims 1 to 13, characterized in that: Also includes: It is detected that the processing device has not passed the risk control check, and an error code indicating the failure of the consultation is fed back to the processing device.

15. The order processing method according to any one of claims 1 to 13, characterized in that: Also includes: Detecting that the processing device fails the risk control verification, and generating a risk record for the user account; It is detected that the number of risk records reaches a number threshold, and the user account is determined as a risk account.

16. An order processing device, characterized in that: include: A detection module, used for monitoring the acquisition operation of the processing device on the order to be processed; A determination module, configured to determine a plurality of attribute values ​​of the acquisition operation based on the monitoring result, so as to generate a pre-operation attribute value for the to-be-processed order based on the plurality of attribute values; A verification module, configured to perform risk control verification on a user account that logs into the processing device based on the pre-operation attribute value; A confirmation module, configured to detect that the user account has passed the risk control verification and confirm that the processing device continues to process the pending order; The release module is used to detect that the user account has not passed the risk control verification and release the pending order to the corresponding order grabbing area.

17. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; Wherein, the processor is configured to execute the order processing method described in any one of claims 1 to 15 by executing the executable instructions.

18. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the order processing method according to any one of claims 1 to 15 is implemented.

19. A computer program product having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the order processing method according to any one of claims 1 to 15 is implemented.

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