CN121501342A - Task execution methods and devices, program products - Google Patents

Abstract

The application discloses a task execution method, a task execution device and a program product, wherein the method comprises the steps of generating target information based on an execution rule of a target task, wherein the execution rule is used for representing the purpose and rule of executing the target task, the target information is used for representing target conditions and target actions required by executing the target task, generating a target instruction set used for executing the target actions under the target conditions based on the target information, and sending the target instruction set to a target algorithm module to instruct the target algorithm module to execute the target task through executing instructions included in the target instruction set so as to obtain a target execution result. The application solves the problem that the task cannot be efficiently executed in the related technology, and further achieves the effect of efficiently executing the task.

Description

Task execution method and device and program product

Technical Field

The present application relates to the field of computer technologies, and in particular, to a method and apparatus for executing a task, and a program product.

Background

When complex multi-rule tasks are executed, related technologies mostly rely on manual execution, and particularly in the process of rule making and adjusting, the problem that the tasks cannot be executed efficiently exists. For example, when a worker of a financial institution performs a task of evaluating an asset of a user, the worker is familiar with business logic and evaluation requirements, but lacks an effective algorithm and a flexible rule processing mechanism, so that the worker cannot comprehensively consider and integrate various evaluation factors when evaluating the asset of each user, thereby resulting in low evaluation efficiency and inaccurate evaluation results.

Disclosure of Invention

The embodiment of the application provides a task execution method, a task execution device and a program product, which at least solve the problem that the task cannot be executed efficiently in the related technology.

According to one aspect of the embodiment of the application, a task execution method is provided, which comprises the steps of generating target information based on an execution rule of a target task, wherein the execution rule is used for representing the purpose and rule of executing the target task, the target information is used for representing target conditions and target actions required by executing the target task, generating a target instruction set used for executing the target actions under the target conditions based on the target information, and sending the target instruction set to a target algorithm module to instruct the target algorithm module to execute the target task by executing instructions included in the target instruction set, so that a target execution result is obtained.

In one exemplary embodiment, generating target information based on an execution rule of a target task includes generating first information based on the execution rule, wherein the first information is used for representing the target condition required for executing the target task, generating second information based on the execution rule, wherein the second information is used for representing the target action required for executing the target task, and determining the first information and the second information as the target information.

In one exemplary embodiment, generating the first information based on the execution rule includes parsing the execution rule, determining a target condition attribute and a target condition attribute value corresponding to the target condition attribute from the execution rule, and determining the target condition attribute and the target condition attribute value corresponding to the target condition attribute as the first information.

In an exemplary embodiment, the target condition attribute includes at least one of a first condition attribute for representing a conditional logical relationship in the target task, a second condition attribute for representing a conditional entity in the target task, and a third condition attribute for representing a conditional comparison relationship in the target task.

In an exemplary embodiment, generating the second information based on the execution rule includes parsing the execution rule, determining a target action attribute and a target action attribute value corresponding to the target action attribute from the execution rule, and determining the target action attribute and the target action attribute value corresponding to the target action attribute as the second information.

In an exemplary embodiment, the target action attribute includes at least one of a first action attribute for indicating an action type in the target task, a second action attribute for indicating an action entity in the target task, and a third action attribute for indicating an action comparison relationship in the target task.

In one exemplary embodiment, generating a target instruction set for executing the target action under the target condition based on the target information includes generating a first instruction set based on the first information, wherein the first instruction set is an instruction set for verifying whether the target task satisfies the target condition, generating a second instruction set based on the second information, wherein the second instruction set is an instruction set for indicating execution of the target action, and determining the first instruction set and the second instruction set as the target instruction set.

In one exemplary embodiment, the method includes sending the first instruction set to a first algorithm module to instruct the first algorithm module to verify whether a current condition for executing the target task satisfies the target condition through a first instruction included in the first instruction set to obtain a first execution result, where the target algorithm module includes the first algorithm module, and sending the second instruction set to a second algorithm module to instruct the second algorithm module to execute the target action through a second instruction included in the second instruction set to obtain the target execution result if the first execution result indicates that the current condition satisfies the target condition.

In another aspect of the embodiment of the application, the task execution device further provides a first generation module, which is used for generating target information based on an execution rule of a target task, wherein the execution rule is used for representing the purpose and rule of executing the target task, the target information is used for representing target conditions and target actions required by executing the target task, a second generation module is used for generating a target instruction set for executing the target actions under the target conditions based on the target information, and a first transmission module is used for transmitting the target instruction set to a target algorithm module to instruct the target algorithm module to execute the target task by executing instructions included in the target instruction set, so that a target execution result is obtained.

According to a further aspect of embodiments of the present application, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the method embodiments described above when being executed by a processor.

According to yet another aspect of embodiments of the present application, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium and executes the computer instructions to cause the computer device to perform the steps of any of the method embodiments described above.

According to a further aspect of embodiments of the present application there is also provided an electronic device comprising a memory having a computer program stored therein and a processor arranged to perform the steps of any of the method embodiments described above by means of the computer program.

Through the method and the device, firstly, the execution rule of the target task is converted into the target information, so that the business logic of the execution rule of the complex task can be converted into the structured configuration information, the preparation of the task in the early stage of execution is simplified, and the condition of high dependence on technicians in the related technology is avoided. And secondly, analyzing the target information and converting the target information into a target instruction set (namely a group of instructions executable by a computer), so that seamless butt joint of business logic from a human understanding level to a computer processing level is realized, and the accuracy and the speed of task execution are improved. Finally, the target instruction set is sent to the target algorithm module, so that the instructions in the instruction set can be rapidly analyzed and executed, and the target task is completed. Therefore, the problem that the task cannot be efficiently executed in the related technology can be solved, and the effect of efficiently executing the task is achieved.

Drawings

Fig. 1 is a schematic view of an application scenario of a task execution method according to an embodiment of the present application;

FIG. 2 is a flow chart of an alternative method of task execution according to an embodiment of the application;

FIG. 3 is a block diagram of an alternative method of performing tasks according to an embodiment of the application;

Fig. 4 is a block diagram of an alternative task execution device according to an embodiment of the present application.

Detailed Description

In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

According to one aspect of the embodiment of the application, a task execution method is provided. Alternatively, in the present embodiment, the above-described task execution method may be applied, but not limited to, in a hardware environment including the terminal device 102 and the server 104 as shown in fig. 1. The server 104 may be connected to the terminal device 102 via a network, may be used to provide services (e.g., application services, etc.) to the terminal device 102 or to clients installed on the terminal device 102, and may provide databases on the server 104 or independent of the server 104 for providing data storage services to the server 104.

The network may include, but is not limited to, at least one of a wired network, a wireless network. The wired network may include, but is not limited to, at least one of a wide area network, a metropolitan area network, and a local area network, and the wireless network may include, but is not limited to, at least one of wireless fidelity (WIRELESS FIDELITY, abbreviated as WIFI), bluetooth. The terminal device 102 may be, but is not limited to, a personal computer (Personal Computer, abbreviated as PC), a mobile phone, a tablet computer, etc. Server 104 may be, but is not limited to being, a cloud server, a server cluster, or other server type.

The method for executing the task according to the embodiment of the present application may be executed by the server 104, or executed by the terminal device 102, or executed by both the server 104 and the terminal device 102. The method for executing the task of the terminal device 102 according to the embodiment of the present application may be executed by a client installed thereon.

Taking the execution method of the task in the present embodiment performed by the terminal device 102 as an example, fig. 2 is a schematic flow chart of an alternative execution method of the task according to an embodiment of the present application, and as shown in fig. 2, the flow of the method may include the following steps:

step S202, generating target information based on an execution rule of the target task, wherein the execution rule is used for representing the purpose and rule of executing the target task, and the target information is used for representing target conditions and target actions required by executing the target task.

Optionally, the target task is a specific work or operation that is done. For example, in a business banking management scenario, one "target task" might be "identify and calculate the weighted assets of all cross-border loan transactions". For example, in the context of retail credit, one "target task" might be "automatically adjusting loan interest rate based on a customer's credit score and loan type". For example, in an educational scenario, one goal task might be "customize personalized learning path and resource recommendation according to the student's learning progress and interests.

Optionally, the execution rule is a task execution rule described in natural language. For example, in the case of risk weighted asset calculation where the target task is a commercial bank, the execution rules may include "apply a specific asset calculation formula when the customer type is a small micro-enterprise and the business type contains green credit". For example, where the target task is to adjust the interest rate of a loan, the execution rules may include "if the customer credit score is above a certain threshold and the loan type is a personal consumer loan, then the interest rate is downregulated by 0.5%". For example, in the case where the target task is to adjust the air conditioning state, the execution rule may include "automatically turning on the air conditioner when the indoor temperature exceeds 28 ℃, and setting to 24 ℃, and turning off the air conditioner when it is lower than 20 ℃.

Optionally, the target information is information generated according to execution rules, structured, in the form of algorithmic logic, and is a bridge between the task execution rules and the system-executable instructions described in natural language. For example, the execution rule is that "when the indoor temperature exceeds 28 ℃, the air conditioner is automatically turned on and set to 24 ℃, and when the indoor temperature is lower than 20 ℃, the air conditioner is turned off", the target information may include "the indoor temperature >28 ℃, the air conditioner is turned on, the air conditioner temperature=24 ℃, the indoor temperature <20 ℃, and the air conditioner is turned off".

Step S204, based on the target information, generating a target instruction set for executing the target action under the target condition.

Step S206, sending the target instruction set to a target algorithm module to instruct the target algorithm module to execute the target task by executing the instruction included in the target instruction set, so as to obtain a target execution result.

Optionally, the target instruction set is a set of specific instructions, which are operator-recognizable instructions in the target algorithm module, for directly guiding how the target algorithm module performs the predetermined actions under the given conditions. The target instruction set includes, but is not limited to, a condition matching instruction, a data processing instruction, a numerical calculation instruction, and a result checking instruction.

Through the embodiment, firstly, the execution rule of the target task is converted into the target information, so that the business logic of the execution rule of the complex task can be converted into the structured configuration information, the preparation of the task in the early stage of execution is simplified, and the condition of high dependence on technicians in the related technology is avoided. And secondly, analyzing the target information and converting the target information into a target instruction set (namely a group of instructions executable by a computer), so that seamless butt joint of business logic from a human understanding level to a computer processing level is realized, and the accuracy and the speed of task execution are improved. Finally, the target instruction set is sent to the target algorithm module, so that the instructions in the instruction set can be rapidly analyzed and executed, and the target task is completed. Therefore, the problem that the task cannot be efficiently executed in the related technology can be solved, and the effect of efficiently executing the task is achieved.

In one exemplary embodiment, generating target information based on an execution rule of a target task includes generating first information based on the execution rule, wherein the first information is used for representing the target condition required for executing the target task, generating second information based on the execution rule, wherein the second information is used for representing the target action required for executing the target task, and determining the first information and the second information as the target information.

Optionally, the target condition (first information) is a pre-condition defined in the execution rule to decide whether to perform a specific action, including a series of indexes or states to be satisfied, and the subsequent target action is triggered only when these conditions are determined to be true. The target action (second information) is a specific operation defined in the execution rule to be executed when the target condition is satisfied. For example, the objective is to optimize the efficiency of farm irrigation, ensuring that the crop is getting the right amount of water at the right time. The business personnel set the following rules through the rule configuration module of the decision measuring and calculating engine, namely, if the soil humidity is lower than a preset threshold value and weather forecast shows that no rain exists in the future 24 hours, an irrigation program is started, and the irrigation water quantity is adjusted to a medium level. The first information generated (target condition) may include condition 1 that the soil humidity is below a preset threshold value and condition 2 that no rain exists in the future 24 hours. The second information generated (target action) may include action 1: "initiate irrigation program"; "adjust irrigation water amount to medium level".

Alternatively, generating the first information based on the execution rules may be accomplished through a variety of techniques including, but not limited to, natural language processing and rule parsing, configuring an interface and template matching.

Optionally, natural language processing (Natural Language Processing, abbreviated as NLP) and rule parsing, which uses natural language processing techniques to analyze the grammar and semantics in executing rules, identify key elements (e.g., subjects, actions, objects, values, times, etc.) related to the conditions, and convert them into first information. For example, the execution rule is "when the customer loan balance exceeds 100 ten thousand yuan and the overdue day exceeds 90 days, the loan reorganization flow is automatically triggered". Through NLP techniques, this rule can be resolved into { condition 1 } "subject" { "customer", "action": "have", "object": "loan balance", "value": 100 ten thousand yuan "," comparator ":" exceed "}," condition 2 "{" subject ": customer", "action": have "," object ":" overdue days "," value ": 90 days", "comparator": exceed "}. This structured information is the first information representing the target conditions required to perform the target task.

Optionally, the configuration interface is matched with the template, so that the service personnel can directly select a preset condition template, such as 'numerical value is larger than/equal to/smaller than a certain value', 'date is in a certain range', 'object belongs to a certain category', and the like, by providing the configuration interface, and then the structured first information is generated by combining with a specific execution rule. For example, on the configured interface, the business person selects the "customer type" field and sets it "equal to" small micro-business, and selects the "business type" field and sets it "contain" green credit business. These conditions are converted to first information: "{ condition 1: {" object ":" customer type "," comparator ":" equals "," value ":" small micro-business "}, condition 2: {" object ":" business type "," comparator ":" contains "," value ":" green credit "} }.

Alternatively, generating the second information based on the execution rules may be accomplished through a variety of techniques including, but not limited to, natural language processing and rule parsing, configuring an interface and template matching.

Optionally, natural language processing and rule parsing, which uses natural language processing techniques to analyze the grammar and semantics in executing rules, identify key elements (e.g., subjects, actions, objects, values, times, etc.) associated with actions, and convert them into second information. For example, in the retail industry, replenishment requests are automatically sent when inventory falls below a certain threshold and price policies are adjusted. The execution rule is "if the stock quantity of commodity X is < threshold value Y, then a restocking request is sent to supplier Z, while the price of commodity X is adjusted up by 10%. This rule can be resolved to "{ action 1: {" type ":" send replenishment request "," target ":" vendor Z "}, action 2: {" type ":" price adjustment "," adjustment ratio ":"10% "," target commodity ":" commodity X "}".

Optionally, the configuration interface is matched with the template, so that the service personnel can directly select and execute the action template by providing the configuration interface, and then the structured second information is generated by combining with specific execution rules. For example, in a commercial bank credit risk assessment, when the condition of "residual loan occurrence >0" is satisfied, an action of calculating a risk weight needs to be performed. The business personnel selects the action of calculating the risk weight on the configuration interface, and sets a parameter of target field, namely the risk weight after slow release, and a calculation formula of residual loan occurrence amount x internal evaluation credit risk conversion coefficient x K value x 12.5. The second information is generated by "{ action 1: {" type ":" calculate "," target field ":" post-release risk weight "," formula ":" residual loan occurrence amount x internal evaluation credit risk conversion coefficient x K value x 12.5 "}).

According to the embodiment, the first information and the second information are automatically generated, so that business personnel can set the condition logic and the action of the complex execution target task through visual natural language description without deeply understanding the implementation of the bottom technology, delay and misoperation of manual operation are avoided, and timeliness and reliability of task execution are improved.

In one exemplary embodiment, generating the first information based on the execution rule includes parsing the execution rule, determining a target condition attribute and a target condition attribute value corresponding to the target condition attribute from the execution rule, and determining the target condition attribute and the target condition attribute value corresponding to the target condition attribute as the first information.

In an exemplary embodiment, the target condition attribute includes at least one of a first condition attribute for representing a conditional logical relationship in the target task, a second condition attribute for representing a conditional entity in the target task, and a third condition attribute for representing a conditional comparison relationship in the target task.

Optionally, the target condition attribute is used to define a characteristic or dimension of the target condition, including but not limited to a first condition attribute, a second condition attribute, and a third condition attribute, where the first condition attribute may be specifically a condition logic relationship, the second condition attribute is a specific object or parameter related to the condition in the execution rule, the second condition attribute may be specifically a condition comparison item type and a condition comparison item value, and the third condition attribute may be specifically a comparison symbol related to the condition. Specifically as shown in table 1:

Table 1:

the embodiment can accurately identify the condition logic relationship (such as ' and ' or '), the condition entity (such as ' client type ', ' service type ') and the condition comparison relationship (such as ' equal ', ' containing ') through the structural analysis execution rule, and the accurate analysis reduces the condition judgment error caused by the human understanding difference.

In an exemplary embodiment, generating the second information based on the execution rule includes parsing the execution rule, determining a target action attribute and a target action attribute value corresponding to the target action attribute from the execution rule, and determining the target action attribute and the target action attribute value corresponding to the target action attribute as the second information.

In an exemplary embodiment, the target action attribute includes at least one of a first action attribute for indicating an action type in the target task, a second action attribute for indicating an action entity in the target task, and a third action attribute for indicating an action comparison relationship in the target task.

Optionally, the target action attribute is used to define a characteristic or dimension of the target action, including but not limited to a first action attribute, a second action attribute, and a third action attribute, where the first action attribute may be specifically an action type, the second action attribute is a specific object or parameter related to the action in the execution rule, specifically an action object type and an action object value, and the third action attribute may be specifically a comparison symbol related to the action. As shown in table 2:

Table 2:

In one exemplary embodiment, generating a target instruction set for executing the target action under the target condition based on the target information includes generating a first instruction set based on the first information, wherein the first instruction set is an instruction set for verifying whether the target task satisfies the target condition, generating a second instruction set based on the second information, wherein the second instruction set is an instruction set for indicating execution of the target action, and determining the first instruction set and the second instruction set as the target instruction set.

Alternatively, the generating of the first instruction set and the second instruction set using the first information and the second information, respectively, may be implemented by a variety of technical means, including, but not limited to, matching the configurable interface with a template, scripting language, or Domain-specific language (Domain-Specific Language, abbreviated as DSL).

Optionally, the configuration interface is matched with a template, wherein the first instruction set is generated by analyzing a conditional logic relation, a conditional entity and a conditional comparison relation in the first information by using a preset template, mapping each condition into one or more instructions, and organizing the instructions according to the logic relation (such as 'and', 'or') among the conditions to form the first instruction set. And generating a second instruction set, namely converting action types, action entities and action comparison relations in the second information into corresponding instructions, such as assignment instructions, calculation formula instructions and the like, based on the templates, so as to ensure that each necessary step is covered, thereby forming the second instruction set.

Optionally, the scripting language or DSL first instruction set generates a small script interpreter or DSL parser capable of reading the structured format (e.g., JSON) of the first information and converting it into a series of conditional judgment instructions. The second instruction set is generated by converting the actions described by the second information into specific operational instructions via a similar DSL or scripting language.

According to the method, the first instruction set is generated, so that the target algorithm module can automatically verify whether the target condition is met or not under the condition that manual intervention is not needed, particularly complex condition judgment is achieved, and errors caused by manual operation are avoided. The second instruction set guides how to execute specific business actions, such as numerical calculation, data assignment, result verification and the like, so that the execution process of the actions is ensured to follow preset logic, and accurate results are output. Meanwhile, the generation and execution of the target instruction set eliminate the inefficiency caused by the traditional manual operation, so that the verification and execution of the target task can be completed in a short time, and particularly, the method is used for large-scale data processing and frequent rule updating scenes.

In one exemplary embodiment, the method includes sending the first instruction set to a first algorithm module to instruct the first algorithm module to verify whether a current condition for executing the target task satisfies the target condition through a first instruction included in the first instruction set to obtain a first execution result, where the target algorithm module includes the first algorithm module, and sending the second instruction set to a second algorithm module to instruct the second algorithm module to execute the target action through a second instruction included in the second instruction set to obtain the target execution result if the first execution result indicates that the current condition satisfies the target condition.

Optionally, the current condition is specific data or status of the target task that needs to be compared to the target condition to determine whether the condition for performing the target action is met. For example, in the target task of "small micro-business green credit," the current condition may be detailed information of a specific loan in a bank credit system, including but not limited to, customer type, which represents the business scale classification of borrowers, such as "small micro-business," "medium-business," "large-business," etc., business type, which describes the business attributes of the loan, such as whether it belongs to "green credit," "normal loan," "consumed loan," etc., and the remaining loan occurrence, which is the current unrepeated principal balance of the loan. Deposit value-if a mortgage is present, its evaluation value.

Optionally, the first algorithm module is an algorithm module that processes the first instruction set and performs condition verification, where the first algorithm module may include an operator such as a logical operator. The second algorithm module is an algorithm module for processing the second instruction set and executing specific business actions after the condition verification is passed, wherein the second algorithm module can comprise operators such as a numerical calculation operator, a result check operator and the like. The target algorithm module may specifically include operators, as shown in tables 3.1-3.4:

table 3.1:

Table 3.2:

Table 3.3:

Table 3.4:

the following explains the execution method of the task in the embodiment of the present application with reference to an alternative example.

Fig. 3 is a schematic diagram of an alternative task execution method according to an embodiment of the present application, as shown in fig. 3, in a scenario where the task execution method is applied to a decision engine system, the decision engine system includes an open layer, a rule engine, and a data layer, where the rule engine includes a rule configuration module, an algorithm processing module (i.e., a target algorithm module), a policy and authority management module, a data interaction module, and a deployment module.

Business personnel input the compound rule (namely the execution rule) of the target task through the visual interface of the rule configuration module, taking the processing rule of the task which is not slowly released by the internal evaluation method as an example, namely, the main table is calculated when the process is single. And when the residual loan occurrence amount is more than 0, the result is slowly released by a temporary internal evaluation method. Table internal and external identification = procedure-single measurement master table. The internal evaluation method is shown as an internal and external mark, and the result is delayed by the temporary internal evaluation method. Slow release amount = procedure-single measurement master. And (5) slowly releasing the result by a temporary internal evaluation method by the residual loan occurrence amount. Risk weighted asset after sustained release = sustained release amount x internal evaluation credit risk conversion coefficient x risk weight after sustained release x 12.5 ");

The rule configuration module analyzes the composite rule into first information (residual loan occurrence > 0) and second information (3 assignment logic+1 risk weighted property calculation logic), and converts the first information and the second information into a rule instruction set (namely a target instruction set) which can be identified by an operator in the algorithm processing module. Wherein the instructions in the first instruction set include, but are not limited to, [ logical operator-single matching operator: field = residual loan occurrence, comparator = >, value = 0; output = matching result (1/0) ]. The instructions in the second instruction set include, but are not limited to, instruction 1 of [ a numerical calculation operator-basic arithmetic operator: a target field=slow release amount, a source field=residual loan occurrence amount, an operation type=assignment (=) ], instruction 2 of [ a numerical calculation operator-compound formula operator: a target field=slow release post-risk weighting property, a formula=slow release amount×an internal evaluation credit risk conversion coefficient×a slow release post-risk weight×12.5], [ a result check operator-validity check operator: a check rule=slow release post-risk weighting property.

The algorithm processing module receives a rule instruction set, firstly, a data preprocessing operator is called, the data preprocessing operator is utilized to obtain the original data of a process-single measurement main table from the data interaction module, the residual loan occurrence amount (such as 1,000,000.00 yuan), the internal and external identifications of an internal evaluation method table (such as table internal=01), the credit risk conversion coefficient of the internal evaluation method (such as 1.00) and the internal evaluation method K value (such as the slow-release risk weight=0.08) are extracted, 4 core dimension fields, then, a data format normalization operator is called to unify the format of the residual loan occurrence amount into a numerical value (reserved 2 decimal), the internal and external identifications of the internal evaluation method table are unified into an encoding type (01=table internal and 02=table external), and the field format is ensured to be consistent with the data format normalization operator. Then, a logic operator is called, a single condition matching operator is utilized to receive an instruction of 'residual loan occurrence > 0', the pretreated '1,000,000.00 th element' is compared with '0', and 'matching success (1') is output.

Because the internal evaluation method does not release the compound rule unconditional combination of the task, the algorithm processing module directly executes the second instruction set in the rule instruction set after executing the first instruction set in the rule instruction set (if multiple conditions exist, the multi-condition combination operator needs to be called to execute "and/or" operation, for example, "client type=small micro-enterprise and service type contains green credit", 2 single condition matches need to be executed first, and then "and" operation "needs to be executed). Firstly, a numerical calculation operator is called, namely, a basic arithmetic operator is used for executing an assignment operation of slow release amount=residual loan occurrence amount to obtain slow release amount= 1,000,000.00 yuan, and a basic arithmetic operator is used for executing a temporary internal evaluation slow release result. The evaluation of the table internal and external identifier=internal evaluation method table internal and external identifier 'is carried out to obtain the table internal and external identifier=01', and the calculation is carried out according to a preset formula by utilizing a compound formula operator, wherein the risk weighting asset= 1,000,000.00 ×1.00×0.08×12.5= 1,000,000.00 elements after slow release is carried out, and meanwhile, intermediate results (1,000,000.00 ×1.00=1,000,000.00; 1,000,000.00×0.08=80,000.00; 80,000.00×12.5= 1,000,000.00) are recorded. And then a result check operator is called, wherein the legitimacy check operator is utilized to check that the calculated result ' 1,000,000.00 yuan ' meets the requirement according to the rule that the risk weighted asset after slow release is more than or equal to 0 ', and the legal result is output, if a plurality of businesses exist, the risk weighted asset results (such as 950,000.00 yuan in average value) of the businesses which are not slow released by the evaluation method in the same batch are compared by the consistency check operator, and the current result (1,000,000.00 yuan) is within a fluctuation range of +/-20%, and the consistency is output.

After all operators are executed, feeding back a temporary internal evaluation slow release result (namely a target execution result) that the internal and external identifiers of the table are=01, the slow release amount is= 1,000,000.00 yuan, the risk weighted asset after slow release is= 1,000,000.00 yuan, and an operator execution log (such as 'single condition matching operator is successfully executed, and compound formula operator is successfully executed') to a rule configuration module for service personnel to check.

In this embodiment, if an abnormality occurs in the above process (e.g., the residual loan occurrence= -500,000.00 yuan), the abnormal value filtering function of the data preprocessing operator may mark "the residual loan occurrence as negative" and output a "data abnormality" log, after receiving the abnormal data, the single condition matching operator may output a "matching failure (0)", and trigger a "rule not execute" instruction at the same time, and the result checking operator generates a "data abnormality report" including an abnormal field (residual loan occurrence), an abnormal value (-500,000.00 yuan), and an abnormal cause (the numerical value is less than 0, and does not conform to the service data specification), and may feed back to the data interaction module to request retransmission of the correct data.

It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.

From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. Read-Only Memory (ROM)/random access Memory (Random Access Memory, RAM), magnetic disk, optical disk), comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present application.

According to another aspect of the embodiments of the present application, a task execution device is provided, and the task execution device may be used to implement the task execution method provided in the foregoing embodiments, which is not described herein. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

Fig. 4 is a block diagram of an alternative task performing device according to an embodiment of the present application, and as shown in fig. 4, the task performing device includes:

A first generation module 402, configured to generate target information based on an execution rule of a target task, where the execution rule is used to indicate a purpose and a rule of executing the target task, and the target information is used to indicate a target condition and a target action required for executing the target task;

a second generating module 404, configured to generate a target instruction set for executing the target action under the target condition based on the target information;

The first sending module 406 is configured to send the target instruction set to a target algorithm module, so as to instruct the target algorithm module to execute the target task by executing an instruction included in the target instruction set, and obtain a target execution result.

It should be noted that, the first generating module 402 in this embodiment may be used to perform the step S202, the second generating module 404 in this embodiment may be used to perform the step S204, and the first transmitting module 406 in this embodiment may be used to perform the step S206.

In an exemplary embodiment, the first generating module 402 includes a first generating sub-module configured to generate first information based on the execution rule, where the first information is used to indicate the target condition required to execute the target task, a second generating sub-module configured to generate second information based on the execution rule, where the second information is used to indicate the target action required to execute the target task, and a first determining sub-module configured to determine the first information and the second information as the target information.

In an exemplary embodiment, the first generation sub-module includes a first parsing unit configured to parse the execution rule, determine a target condition attribute and a target condition attribute value corresponding to the target condition attribute from the execution rule, and a first determining unit configured to determine the target condition attribute and the target condition attribute value corresponding to the target condition attribute as the first information.

In an exemplary embodiment, the target condition attribute includes at least one of a first condition attribute for representing a conditional logical relationship in the target task, a second condition attribute for representing a conditional entity in the target task, and a third condition attribute for representing a conditional comparison relationship in the target task.

In an exemplary embodiment, the second generation submodule comprises a second analysis unit and a second determination unit, wherein the second analysis unit is used for analyzing the execution rule and determining a target action attribute value corresponding to the target action attribute and a target action attribute value corresponding to the target action attribute from the execution rule, and the second determination unit is used for determining the target action attribute and the target action attribute value corresponding to the target action attribute as the second information.

In an exemplary embodiment, the target action attribute includes at least one of a first action attribute for indicating an action type in the target task, a second action attribute for indicating an action entity in the target task, and a third action attribute for indicating an action comparison relationship in the target task.

In an exemplary embodiment, the second generating module 404 includes a third generating sub-module configured to generate a first instruction set based on the first information, where the first instruction set is an instruction set for indicating whether the target task meets the target condition, a fourth generating sub-module configured to generate a second instruction set based on the second information, where the second instruction set is an instruction set for indicating that the target action is performed, and a second determining sub-module configured to determine the first instruction set and the second instruction set as the target instruction set.

In an exemplary embodiment, the first sending module 406 includes a first sending sub-module configured to send the first instruction set to a first algorithm module, to instruct the first algorithm module to verify, through a first instruction included in the first instruction set, whether a current condition for executing the target task meets the target condition, to obtain a first execution result, where the target algorithm module includes the first algorithm module, and a second sending sub-module configured to send the second instruction set to a second algorithm module, to instruct the second algorithm module to execute, through a second instruction included in the second instruction set, the target action to obtain the target execution result, where the first execution result indicates that the current condition meets the target condition.

It should be noted that each of the above modules may be implemented by software or hardware, and the latter may be implemented by, but not limited to, the above modules all being located in the same processor, or each of the above modules being located in different processors in any combination.

According to a further aspect of the embodiments of the present application, there is provided a computer readable storage medium comprising a stored program, wherein the program when run performs the steps of any of the method embodiments described above.

In an exemplary embodiment, the computer readable storage medium may include, but is not limited to, a USB flash disk, a ROM, a RAM, a removable hard disk, a magnetic or optical disk, and other various media in which computer programs may be stored.

According to a further aspect of an embodiment of the application there is provided an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor being arranged to perform the steps of any of the method embodiments described above by the computer program. In an exemplary embodiment, the electronic device may further include a transmission device connected to the processor, and an input/output device connected to the processor.

Specific examples in this embodiment may refer to the examples described in the foregoing embodiments and the exemplary implementation, and this embodiment is not described herein.

According to yet another aspect of an embodiment of the present application, there is also provided a computer program product comprising a computer program/instruction containing program code for executing the method shown in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via a communication portion, and/or installed from a removable medium. When executed by a central processing unit, performs various functions provided by embodiments of the present application. The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.

It will be appreciated by those skilled in the art that the modules or steps of the application described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may be implemented in program code executable by computing devices, so that they may be stored in a memory device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than herein, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module. Thus, the present application is not limited to any specific combination of hardware and software.

In the technical scheme of the application, the related processes of collecting, storing, using, processing, transmitting, providing, disclosing and the like of the information such as financial data or user data are in accordance with the regulations of related laws and regulations, and the public welfare is not violated.

It should be noted that, in the embodiments of the present application, some existing solutions in the industry such as software, components, models, etc. may be mentioned, and they should be regarded as exemplary, only for illustrating the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or must not use the solution.

The above is only a preferred embodiment of the present application, and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the principle of the present application should be included in the protection scope of the present application.

Claims (10)

1. A method of performing a task, comprising:

generating target information based on an execution rule of a target task, wherein the execution rule is used for representing the purpose and rule of executing the target task, and the target information is used for representing target conditions and target actions required by executing the target task;

generating a target instruction set for executing the target action under the target condition based on the target information;

and sending the target instruction set to a target algorithm module to instruct the target algorithm module to execute the target task by executing the instructions included in the target instruction set, so as to obtain a target execution result.

2. The method of claim 1, wherein generating the target information based on the execution rules of the target task comprises:

generating first information based on the execution rule, wherein the first information is used for representing the target condition required for executing the target task;

generating second information based on the execution rule, wherein the second information is used for representing the target action required by executing the target task;

and determining the first information and the second information as the target information.

3. The method of claim 2, wherein generating the first information based on the execution rule comprises:

Analyzing the execution rule, and determining a target condition attribute and a target condition attribute value corresponding to the target condition attribute from the execution rule;

and determining the target condition attribute value corresponding to the target condition attribute and the target condition attribute as the first information.

4. The method of claim 3, wherein the target condition attributes comprise at least one of a first condition attribute for representing a conditional logical relationship in the target task, a second condition attribute for representing a conditional entity in the target task, and a third condition attribute for representing a conditional comparison relationship in the target task.

5. The method of claim 2, wherein generating second information based on the execution rule comprises:

analyzing the execution rule, and determining a target action attribute and a target action attribute value corresponding to the target action attribute from the execution rule;

and determining the target action attribute and the target action attribute value corresponding to the target action attribute as the second information.

6. The method of claim 5, wherein the target action attribute comprises at least one of a first action attribute for representing an action type in the target task, a second action attribute for representing an action entity in the target task, and a third action attribute for representing an action comparison relationship in the target task.

7. The method of claim 2, wherein generating a target instruction set for performing the target action under the target condition based on the target information comprises:

Generating a first instruction set based on the first information, wherein the first instruction set is an instruction set for representing verifying whether the target task meets the target condition;

Generating a second instruction set based on the second information, wherein the second instruction set is an instruction set for representing performing the target action;

The first instruction set and the second instruction set are determined to be the target instruction set.

8. The method of claim 7, wherein sending the target instruction set to a target algorithm module to instruct the target algorithm module to execute the target task by executing instructions included in the target instruction set to obtain a target execution result, comprising:

the first instruction set is sent to a first algorithm module to instruct the first algorithm module to verify whether the current condition for executing the target task meets the target condition or not through a first instruction included in the first instruction set to obtain a first execution result, wherein the target algorithm module comprises the first algorithm module;

And under the condition that the first execution result indicates that the current condition meets the target condition, sending the second instruction set to a second algorithm module to instruct the second algorithm module to execute the target action through a second instruction included in the second instruction set, so as to obtain the target execution result.

9. A task execution device, comprising:

the first generation module is used for generating target information based on an execution rule of a target task, wherein the execution rule is used for representing the purpose and rule of executing the target task, and the target information is used for representing target conditions and target actions required by executing the target task;

A second generation module for generating a target instruction set for executing the target action under the target condition based on the target information;

and the first sending module is used for sending the target instruction set to a target algorithm module so as to instruct the target algorithm module to execute the target task by executing the instruction included in the target instruction set, and obtain a target execution result.

10. A computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the method of any of claims 1 to 8.