Clue work order dispatching method and device

Abstract

The invention discloses a clue work order assignment method and device. The method comprises the following steps: acquiring a behavior of a target entity; determining an abnormal clue corresponding to the behavior of the target entity by using a rule engine based on rules in a rule base, and determining a risk level corresponding to the abnormal clue; and assigning the abnormal clues of different risk levels to different accounts in the form of work orders. The abnormal clues in the entity behaviors are determined through the rule engine, and then different work orders are automatically dispatched, so that the work order dispatching efficiency is improved. And the defect of poor efficiency in related technologies is overcome.

Description

Technical Field

[0001] The present invention relates to the technical field, and in particular to a method and device for allocating clue work orders. Background Art

[0002] In order to improve the industry's regulatory capabilities, it is necessary to determine abnormal behavior of entities within the industry and generate abnormal clues and assign work orders based on abnormal behavior, which can provide a reference for law enforcement.

[0003] In related technologies, the assignment of abnormal clue work orders usually relies on human judgment, and the efficiency needs to be improved. Summary of the invention

[0004] The main purpose of the present invention is to provide a clue work order dispatching method and device, which has solved the technical problems existing in the related technology.

[0005] In order to achieve the above-mentioned purpose, according to the first aspect of the present invention, a clue work order dispatching method is provided, including obtaining the behavior of the target entity; based on the rules in the rule base, using a rule engine to determine the abnormal clues corresponding to the behavior of the target entity, and determining the risk level corresponding to the abnormal clues; and dispatching the abnormal clues of different risk levels to different accounts in the form of work orders.

[0006] Optionally, allocating abnormal clues of different risk levels to different accounts in the form of work orders includes allocating abnormal clues of different risk levels to different accounts in the form of work orders based on different locations of the target entities.

[0007] Optionally, determining the abnormal clues corresponding to the behavior of the target entity based on a preset rule engine includes: determining the rules corresponding to the target entity from a rule library based on the type of the target entity; extracting specified information from the behavior of the target entity based on the corresponding rules; and determining the abnormal clues based on the specified information and the corresponding rules.

[0008] Optionally, the method also includes: providing visual configuration interface data to the terminal so that the terminal can present a visual configuration page; in response to receiving a request for rule changes in a rule base sent by the terminal, changing the rules in the rule base based on the content indicated by the request, wherein the request is generated by the terminal after a rule change operation is triggered on the visual configuration interface; the change includes modifying the content of the rule, the entity type corresponding to the rule, the risk level corresponding to the abnormal clue determined based on the rule, and / or the type of work order corresponding to the rule under different jurisdictions.

[0009] Optionally, it also includes providing visual configuration interface data to the terminal to present the visual configuration interface on the terminal; in response to receiving a rule extension request sent by the terminal, extending the rules in the rule library based on the content indicated by the rule extension request, wherein the rule extension request is generated after the rule extension configuration operation is triggered on the visual configuration interface of the terminal; the extended rules include: the name of the newly added rule, the content of the rule, the entity type corresponding to the rule, the risk level corresponding to the abnormal clue determined based on the rule, and the type of work order corresponding to the rule under different jurisdictions.

[0010] Optionally, reassign the work order based on the changed rules.

[0011] According to a second aspect of the present invention, there is provided a clue and work order dispatching device, comprising: a behavior acquisition unit, configured to acquire the behavior of a target entity; a risk level determination unit, configured to determine the abnormal clues corresponding to the behavior of the target entity from a rule base based on a rule engine, and determine the risk level corresponding to the abnormal clues; and a work order dispatching unit, configured to dispatch abnormal clues of different risk levels to different accounts in the form of work orders.

[0012] According to a third aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the method described in any one of the implementations of the first aspect.

[0013] According to a fourth aspect of the present invention, there is provided an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor executes the method described in any one implementation of the first aspect.

[0014] According to a fifth aspect of the present invention, there is provided a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method described in any one of the implementation modes of the first aspect is implemented.

[0015] The present embodiment provides a method and device for assigning clues and work orders, wherein the method includes obtaining the behavior of a target entity; based on the rules in a rule base, using a rule engine to determine the abnormal clues corresponding to the behavior of the target entity, and determining the risk level corresponding to the abnormal clues; and assigning abnormal clues of different risk levels to different accounts in the form of work orders. By using a rule engine to determine abnormal clues in entity behavior and then automatically assigning different work orders, the efficiency of assigning work orders is improved. The defect of poor efficiency of related technologies is overcome.

[0016] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 is a flow chart of a method for assigning clue work orders according to an embodiment of the present invention;

[0018] Figure 2 This is an application scenario diagram of the clue work order dispatching method according to an embodiment of the present invention;

[0019] Figure 3 is another application scenario diagram of the clue work order dispatching method according to an embodiment of the present invention;

[0020] Figure 4 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so as to describe the embodiments of the present invention described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0024] According to an embodiment of the present invention, a method for assigning a clue work order is provided, such as Figure 1As shown, it includes the following steps 101 to 103:

[0025] Step 101: Get the behavior of the target entity.

[0026] In this embodiment, the behavior data of the monitored target entity can be obtained. Exemplarily, the behavior data of the monitored target entity can be obtained from the terminal. The entity refers to the monitored object, including but not limited to vehicles, personnel, and businesses, and the behavior can be a specific behavior in a traffic scene. Information of multiple dimensions can be extracted from the behavior, and abnormal clues can be determined based on this information.

[0027] Step 102: Based on the rule engine, determine the abnormal clues corresponding to the behavior of the target entity from the rule base, and determine the risk level corresponding to the abnormal clues.

[0028] In this embodiment, when determining the abnormal clues corresponding to the target entity behavior through the rule engine, the rules in the rule library can be called to determine the abnormal clues corresponding to the target entity behavior based on the content of each rule.

[0029] The rules in the rule base are obtained based on user configuration. The rule configuration page is presented in the terminal interface. Users can trigger the configuration operation on the page to complete the rule configuration, including the name of the configuration rule, the entity type targeted by the rule, and the content corresponding to the rule. According to actual needs, a rule can be configured with one or more contents as needed, if the entity behavior meets any rule content and is determined to be an abnormal clue, the risk level corresponding to the abnormal clue, the work order type corresponding to the local entity under different rule content and different risk levels, and the work order type corresponding to the foreign entity under different rule content. After the configuration is completed, the configured rules can be stored in the rule base.

[0030] Exemplarily, the rule name is "The vehicle is still in operation despite the expiration of its certificate"; the rule content may be the validity determination of the vehicle status, the operation status determination, and the validity period determination in the entity behavior; the corresponding entity type may be a vehicle; the entity behavior that meets the rule content is determined to have abnormal clues, i.e., the vehicle is still in operation despite the expiration of its certificate, and the abnormal clues correspond to a high-risk level; local entities correspond to pre-work orders at high-risk levels; and foreign entities directly correspond to copy notices.

[0031] For example, the rule name is "The main responsibility of the enterprise's East Tower monitoring has not been fulfilled (speeding)", the corresponding rule content (which can be configured as needed and is not limited here), the targeted entity type is "business owner", the corresponding risk level, the corresponding work order type of the local entity, and the work order type of the foreign entity.

[0032] Exemplarily, the rule name may be "Red code driver violates the regulations on duty", the rule content (can be configured as needed and is not limited here), the targeted entity type is "personnel", the corresponding risk level, the corresponding work order type of the local entity, and the work order type of the foreign entity.

[0033] The above are just individual examples to further explain the composition of rules in the rule base.

[0034] Step 103: Assign abnormal clues of different risk levels to different accounts in the form of work orders.

[0035] In this embodiment, after determining the abnormal clue, the risk level corresponding to the abnormal clue can be determined based on the pre-associated risk level, and the type of clue work order can be determined based on the different risk levels, and then the clue work order of the corresponding type can be assigned.

[0036] refer to Figure 2 When the engine judges the entity behavior, it takes the rule name "the vehicle is still engaged in operation despite the invalid certificate" as an example and makes judgments based on the content of the rule, such as validity judgment, operation status judgment, validity period judgment, etc. If the rules are met, different types of clue work orders are generated, otherwise no clue work orders are generated.

[0037] As an optional implementation method of this embodiment, assigning abnormal clues of different risk levels to different accounts in the form of work orders includes: based on the different locations of the target entities, assigning abnormal clues of different risk levels to different accounts in the form of work orders.

[0038] In this optional implementation, reference Figure 3 When determining the clue work order and assigning it, you can first determine the location of the target entity, whether it is local or out-of-town. If it is local, determine the risk level corresponding to the abnormal clue. If it is high risk, assign it in the form of a pre-work order; if it is medium risk, assign it in the form of a rectification order; if it is low risk, assign it in the form of a reminder order. If it is out-of-town, assign it directly in the form of a copy notice.

[0039] As an optional implementation method of this embodiment, determining the abnormal clues corresponding to the behavior of the target entity based on a preset rule engine includes: determining the rules corresponding to the target entity from a rule library based on the type of the target entity; extracting specified information in the behavior of the target entity based on the corresponding rules; and determining the abnormal clues based on the specified information and the corresponding rules.

[0040] In this optional implementation, a rule base is pre-built, and the rule base includes multiple rules. Specifically, the same type of entity can be associated with multiple rules, and the associated rules are determined based on the type of the entity. For example, if the entity type is a vehicle, the associated rules may include but are not limited to "the vehicle is still engaged in operation after the expiration of the vehicle certificate", "the vehicle is still engaged in operation after the annual inspection is overdue", "the vehicle is engaged in transportation operations beyond the scope", etc. Further, based on the content of each rule, the preset information is extracted from the behavior of the target entity, and the preset information is further judged based on the rule content to determine the abnormal clues.

[0041] For example, when judging the rule of "the vehicle is still operating with expired certificates", the validity period, operating date, etc. of the entity's vehicle certificate can be extracted to ultimately determine whether the rule is met. If the rule is met, it is considered that the entity has abnormal clues, and the abnormal clue is "the vehicle is still operating with expired certificates".

[0042] For example, taking the rule named "Vehicles engage in transport operations beyond the scope" as an example, its content is to determine whether the vehicle road transport license has specific transport qualifications. Based on this, the transport qualification information in the vehicle road transport license of the target entity can be extracted, and the actual transport information in the target entity behavior can be extracted. For example, if dangerous goods are transported, it is determined whether the actual transport information and the vehicle transport qualification information are consistent. For example, if the vehicle road transport license does not have the dangerous goods transport qualification, then the two transport information do not match. If they do not match, the abnormal clues that exist may be "the vehicle road transport license does not have the corresponding dangerous goods transport qualification or does not have the dangerous goods transport qualification" and so on.

[0043] Furthermore, abnormal clues that meet the rules are associated with risk levels. For example, if the target entity in the above example meets the rule of "the vehicle is engaged in transportation operations beyond the scope", it is judged to be high risk.

[0044] As an optional implementation of this embodiment, the method also includes: providing visual configuration interface data to the terminal so that the terminal can present a visual configuration page; in response to receiving a request for rule changes in the rule base sent by the terminal, changing the rules in the rule base based on the content indicated by the request, wherein the request is generated by the terminal after the rule change operation is triggered on the visual configuration interface; the change includes modifying the content of the rule, the entity type corresponding to the rule, the risk level corresponding to the abnormal clue determined based on the rule, and / or the type of work order corresponding to the rule under different jurisdictions.

[0045] In this optional implementation, the rules in the rule library can enable users to modify the rules through visual configuration. Specifically, a visual configuration page is presented on the terminal, and the page presents the name of the rule stored in the rule library, the content corresponding to the rule, the entity type targeted by the rule (including but not limited to vehicles, businesses, and personnel), and if the entity behavior meets any rule content and is determined to be an abnormal clue, the risk level corresponding to the abnormal clue (including high, medium, and low), the work order type corresponding to the local entity under different rule contents and different risk levels (including but not limited to pre-work orders and rectification orders), and the work order type corresponding to the foreign entity under different rule contents (reporting copy orders).

[0046] Furthermore, when changing the rules, any one of the rule name, rule content, entity object type targeted by each rule, risk level, and work order type may be modified.

[0047] The modification of the rule content determines the abnormal clues corresponding to the entity behavior. For example, if the judgment conditions and the required judgment thresholds in the rule content change, the abnormal clues will change and may become no abnormal clues. For example, in the rule of "the mass of goods transported by the vehicle exceeds the rated load of the vehicle", if the rated load in the rule content sets an exceeding threshold, then the vehicle that originally met the rule and was judged as an abnormal clue may not exceed the sum of the rated load and the set threshold after the modification. In this case, there are no abnormal clues for the entity behavior under this rule.

[0048] For example, if the initial rule of "the vehicle is still operating despite the expiration of its certificate" is deleted from the vehicle entity, then there will be no abnormal clues under this rule for the vehicle entity.

[0049] It should be understood that the same entity may correspond to multiple exception clues, and thus multiple types of work orders may be assigned.

[0050] As an optional implementation method of this embodiment, the method also includes: providing visualization configuration interface data to the terminal to present the visualization configuration interface on the terminal; in response to receiving a rule extension request sent by the terminal, extending the rules in the rule library based on the content indicated by the rule extension request, wherein the rule extension request is generated by the terminal after the rule extension configuration operation is triggered on the visualization configuration interface; the extended rules include: the name of the newly added rule, the content of the rule, the entity type corresponding to the rule, the risk level corresponding to the abnormal clue determined based on the rule, and the type of work order corresponding to the rule under different jurisdictions.

[0051] In this optional implementation, users can expand rules through visual configuration. Taking adding new rules as an example, users can add rule names, configure rule contents, corresponding risk levels when entity behaviors meet the rules, work order types of local entities at different risk levels, and work order types of foreign entities in the visual configuration page.

[0052] The flexible expansion of rules is achieved through visual configuration, which overcomes the problem that as the demand for abnormal behavior monitoring continues to increase in related technologies, more judgment rules need to be developed, consuming more manpower and material costs.

[0053] As an optional implementation of this embodiment, the work order is reassigned based on the modified rules.

[0054] In this optional implementation, when the risk level corresponding to the abnormal clue determined after the rule content or the entity behavior satisfies the rule changes, the work order type corresponding to the entity will also change.

[0055] This optional implementation overcomes the defects in related technologies that the processing requirements for different abnormal clues cannot be changed and the dispatching process cannot be adaptively changed.

[0056] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0057] According to an embodiment of the present invention, a clue and work order dispatching device is also provided, including a behavior acquisition unit, configured to acquire the behavior of a target entity; a risk level determination unit, configured to determine the abnormal clues corresponding to the behavior of the target entity from a rule base based on a rule engine, and determine the risk level corresponding to the abnormal clues; and a work order dispatching unit, configured to dispatch abnormal clues of different risk levels to different accounts in the form of work orders.

[0058] As an optional implementation method of this embodiment, assigning abnormal clues of different risk levels to different accounts in the form of work orders includes: based on the different locations of the target entities, assigning abnormal clues of different risk levels to different accounts in the form of work orders.

[0059] As an optional implementation method of this embodiment, determining the abnormal clues corresponding to the behavior of the target entity based on a preset rule engine includes: determining the rules corresponding to the target entity from a rule library based on the type of the target entity; extracting specified information in the behavior of the target entity based on the corresponding rules; and determining the abnormal clues based on the specified information and the corresponding rules.

[0060] The device also includes a change unit, which is configured to provide visual configuration interface data to the terminal so that the terminal can present a visual configuration page; in response to receiving a request for changing the rules in the rule base sent by the terminal, the rules in the rule base are changed based on the content indicated by the request, wherein the request is generated by the terminal after the rule change operation is triggered on the visual configuration interface; the change includes modifying the content of the rule, the entity type corresponding to the rule, the risk level corresponding to the abnormal clue determined based on the rule, and / or the type of work order corresponding to the rule under different jurisdictions.

[0061] As an optional implementation method of this embodiment, the device includes an expansion unit, which is configured to provide visual configuration interface data to the terminal to present the visual configuration interface on the terminal; in response to receiving a rule extension request sent by the terminal, the rule is extended in the rule library based on the content indicated by the rule extension request, wherein the rule extension request is generated by the terminal after the rule extension configuration operation is triggered on the visual configuration interface; the extended rule includes: the name of the newly added rule, the content of the rule, the entity type corresponding to the rule, the risk level corresponding to the abnormal clue determined based on the rule, and the type of work order corresponding to the rule under different jurisdictions.

[0062] As an optional implementation of this embodiment, the device reassigns the work order based on the modified rules.

[0063] According to an embodiment of the present invention, the present invention also provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can implement the object method described in any of the above embodiments when executing.

[0064] According to an embodiment of the present invention, the present invention further provides a readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to implement the object matching method described in any of the above embodiments when executed.

[0065] According to an embodiment of the present invention, the present invention further provides a computer program product, which can implement the method described in any of the above embodiments when executed by a processor.

[0066] Figure 4A schematic block diagram of an example electronic device 300 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices.

[0067] As shown in FIG. 4 , the device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 302 or a computer program loaded from a storage unit 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0068] A number of components in the device 300 are connected to the I / O interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0069] The computing unit 301 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 301 performs the various methods and processes described above, such as the object matching method. For example, in some embodiments, the object matching method may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 300 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the computing unit 301, one or more steps of the method described above may be performed.

[0070] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs, which may be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general programmable processor, which may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0071] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0072] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

Claims

1. A method for assigning clue work orders, characterized in that: include: Get the behavior of the target entity; Based on the rules in the rule base, a rule engine is used to determine the abnormal clues corresponding to the behavior of the target entity, and to determine the risk level corresponding to the abnormal clues; Assign abnormal clues of different risk levels to different accounts in the form of work orders.

2. The clue work order dispatching method according to claim 1, characterized in that: Assigning abnormal clues of different risk levels to different accounts in the form of work orders includes: Based on the location of the target entity, abnormal clues of different risk levels are assigned to different accounts in the form of work orders.

3. The clue work order dispatching method according to claim 1, characterized in that: The abnormal clues corresponding to the behavior of the target entity determined based on the preset rule engine include: Determining a rule corresponding to the target entity from a rule base based on the type of the target entity; Extracting specified information from the behavior of the target entity based on the corresponding rules; Abnormal clues are determined based on the specified information and the corresponding rules.

4. The clue work order dispatching method according to claim 1, characterized in that: The method further comprises: Providing visual configuration interface data to the terminal so that the terminal can present a visual configuration page; In response to receiving a request for changing rules in a rule base sent by a terminal, the rules in the rule base are changed based on the content indicated by the request, wherein the request is generated by the terminal after a rule change operation is triggered on a visual configuration interface; the change includes modifying the content of the rule, the entity type corresponding to the rule, the risk level corresponding to the abnormal clue determined based on the rule, and / or the type of work order corresponding to the rule under different jurisdictions.

5. The clue work order dispatching method according to claim 1, characterized in that: The method further comprises: Providing visual configuration interface data to the terminal to present the visual configuration interface on the terminal; In response to receiving a rule extension request sent by a terminal, the rules are extended in a rule library based on the content indicated by the rule extension request, wherein the rule extension request is generated by the terminal after a rule extension configuration operation is triggered in a visual configuration interface; the extended rules include: the name of the newly added rule, the content of the rule, the entity type corresponding to the rule, the risk level corresponding to the abnormal clue determined based on the rule, and the type of work order corresponding to the rule under different jurisdictions.

6. The clue work order dispatching method according to claim 4, characterized in that: Reassign work orders based on the changed rules.

7. A clue work order dispatching device, characterized in that: include: a behavior acquisition unit, configured to acquire the behavior of a target entity; a risk level determination unit configured to determine, based on a rule engine, from a rule base, abnormal clues corresponding to the behavior of the target entity, and determine a risk level corresponding to the abnormal clues; The work order dispatching unit is configured to dispatch abnormal clues of different risk levels to different accounts in the form of work orders.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method according to any one of claims 1 to 6.

9. An electronic device, characterized in that: include: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor executes the method described in any one of claims 1-6.

10. A computer program product, comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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