CN115795185B - Risk trip screening method, risk trip screening device, computer equipment and storage medium - Google Patents
Risk trip screening method, risk trip screening device, computer equipment and storage medium Download PDFInfo
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Abstract
The application relates to a risk trip screening method, a risk trip screening device, computer equipment and a storage medium. The method comprises the following steps: receiving a risk screening request of a target journey sent by a service calling party; the risk screening request comprises journey identification information, rule selection information and supplementary parameters; acquiring a target rule from a rule base according to rule selection information; analyzing each rule factor in the target rule, determining an index corresponding to each rule factor, and obtaining storage information preconfigured for each index; acquiring execution parameters corresponding to each rule factor according to the travel identification information and the storage information of each index; and carrying out risk screening on the target journey according to the target rule, each execution parameter and the supplementary parameter. By adopting the method, the efficiency and timeliness of risk journey screening can be improved.
Description
Technical Field
The present disclosure relates to the field of data processing technologies, and in particular, to a risk trip screening method, a risk trip screening device, a computer device, and a storage medium.
Background
With the development of data processing technology, a risk control engine appears, for example, in an application scene of on-line ordering, whether a target journey is at risk can be judged according to a certain business rule from vehicle driving big data.
In the traditional technology, the risk control engine is a business personnel to formulate a risk control rule, a technician realizes a flow rule through code design, then compiles, packages and deploys a program to a server, the technician is required to modify, package and online the code according to scene and business changes, the whole process consumes a long time, quick adjustment cannot be realized, and the risk journey screening efficiency is low and timeliness is poor.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a risk trip screening method, apparatus, computer device, and storage medium that can improve the efficiency and timeliness of risk trip screening.
A risk trip screening method, the method comprising:
receiving a risk screening request of a target journey sent by a service calling party; the risk screening request comprises journey identification information, rule selection information and supplementary parameters;
acquiring a target rule from a rule base according to rule selection information;
analyzing each rule factor in the target rule, determining an index corresponding to each rule factor, and obtaining storage information preconfigured for each index;
acquiring execution parameters corresponding to each rule factor according to the travel identification information and the storage information of each index;
and carrying out risk screening on the target journey according to the target rule, each execution parameter and the supplementary parameter.
In one embodiment, the rule selection information includes service scene identification information, and obtaining the target rule from the rule base according to the rule selection information includes:
and screening all or part of configured rules in the business scene corresponding to the business scene identification information from the rule library as target rules.
In one embodiment, the rule selection information is rule identification information, and the obtaining the target rule from the rule base according to the rule selection information includes:
and screening the configured rule corresponding to the rule identification information from the rule base as a target rule.
In one embodiment, the supplemental parameters include at least one of a current average travel speed of the target trip, a difference between the order pickup time and a last online time before the order pickup by the driver, a current distance travelled, and a matching distance between the trip start point of the order and the driver.
In one embodiment, the metrics include average travel speed for the total trip, number of reports, type of order, distance between the driver and passenger when they match, and time difference between completion of two similar trip orders in the driver dimension.
In one embodiment, the method further comprises:
receiving a plurality of rule factors configured based on a configuration interface;
receiving storage information of indexes corresponding to rule factors configured based on a configuration interface; wherein the storage information comprises type information and storage position information of a storage database;
responding to a rule issuing instruction, and generating configured rules according to the received data;
and analyzing and pre-compiling the configured rules and storing the configured rules.
In one embodiment, the method further comprises:
monitoring the update of each rule factor of the configured rule in real time, analyzing and precompiling the updated rule, and storing the rule into a rule base;
monitoring the updating of the storage information of the index corresponding to each rule factor of the configured rule in real time, and storing the updated storage information of the index corresponding to each rule factor into a factor information database or a factor information cache.
A risk trip screening device, the device comprising:
the request receiving module is used for receiving a risk screening request of a target journey sent by a service calling party; the risk screening request comprises journey identification information, rule selection information and supplementary parameters;
the rule selection module is used for acquiring target rules from the rule base according to the rule selection information;
the factor analysis module is used for analyzing each rule factor in the target rule, determining the index corresponding to each rule factor and acquiring the storage information preconfigured for each index;
the parameter acquisition module is used for acquiring execution parameters corresponding to each rule factor according to the travel identification information and the storage information of each index;
and the risk screening module is used for carrying out risk screening on the target journey according to the target rule, each execution parameter and the supplementary parameter.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any one of the risk trip screening methods described above when the computer program is executed.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the risk trip screening method of any one of the above.
According to the risk journey screening method, the risk journey screening device, the computer equipment and the storage medium, after a risk screening request is received, the target rule is determined according to the rule selection information, indexes corresponding to the rule factors are determined by analyzing the rule factors configured in the target rule, and execution parameters of the target journey are obtained according to the storage information corresponding to the pre-configured indexes, so that risk screening for the target journey is achieved. By adopting the method, the service calling party can automatically screen rules and accurately call the execution parameters and execute the rules only by sending out the request and according to the related request information, thereby improving the efficiency and timeliness of risk trip screening.
Drawings
FIG. 1 is an application environment diagram of a method of screening a risk trip in one embodiment;
FIG. 2 is a flow chart of a method of screening a risk trip in one embodiment;
FIG. 3 is a flow chart of a risk trip screening method in one example application;
FIG. 4 is a block diagram of an embodiment of a risk trip screening device;
fig. 5 is an internal structural diagram of a computer device in one embodiment.
Description of the embodiments
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The risk journey screening method provided by the application can be applied to an application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. Specifically, the server 104 receives a risk screening request of a target trip sent by a service caller (terminal 102); the risk screening request comprises journey identification information, rule selection information and supplementary parameters; acquiring a target rule from a rule base according to rule selection information; analyzing each rule factor in the target rule, determining an index corresponding to each rule factor, and obtaining storage information of each index; acquiring execution parameters corresponding to each rule factor according to the travel identification information and the storage information of each index; and carrying out risk screening on the target journey according to the target rule, each execution parameter and the supplementary parameter. Still further, the results of the risk screening may be returned to the service caller (terminal 102). The terminal 102 may be, but not limited to, various vehicle terminals, personal computers, notebook computers, smartphones, tablet computers, and portable wearable devices, and the server 104 may be implemented by a stand-alone server or a server cluster composed of a plurality of servers.
In one embodiment, as shown in fig. 2, a risk trip screening method is provided, and the method is applied to the terminal in fig. 1 for illustration, and includes the following steps:
step S202: receiving a risk screening request of a target journey sent by a service calling party; the risk screening request comprises journey identification information, rule selection information and supplementary parameters.
The service calling party refers to a client or a terminal for calling the service interface to initiate the risk screening request. The target itinerary refers to an itinerary designated by the service caller to be risk screened. The risk screening request may include information about the target trip for which screening is requested, for example, trip identification information, rule selection information, and supplementary parameters of the target trip.
By way of example, the trip identification information refers to an identification capable of identifying the trip to be screened, e.g., from the dimension of the order service may be an order number, from the dimension of the customer service may also be a driver identification, passenger identification, or vehicle identification, etc. The rule selection information refers to indication information for representing how to select the screening rule, for example, may be service scene identification information, and represents determining a risk screening rule according to a service scene; or may be a rule ID, and the token may individually execute a single specified rule.
The supplementary parameter may be data that is more real-time, and may be data that is generated by the target trip during the course of the trip, for example, may include at least one of a current average travel speed of the target trip (average speed of the traveled trip), a difference between the order taking time and a latest on-line time before the order taking by the driver, a current traveled mileage, and a matching distance between a trip start point of the order and the driver. The service calling party is supported to transmit the supplementary parameters at the interface of the calling service, and the data with higher real-time performance can be transmitted to the rule engine for execution in a mode of transmitting the supplementary parameters through the interface, so that the data support of two dimensions of historical data and real-time data can be provided for risk screening, and the accuracy and timeliness of the risk screening executed by the rule engine can be improved.
Step S204: and acquiring the target rule from the rule base according to the rule selection information.
Wherein, the rule base can be pre-stored with a plurality of configured screening rules.
Specifically, the server may select, according to rule selection information included in the risk screening request, one or more rules from the rule base according to an instruction of the rule selection information, and use the one or more rules as the target rule executed at this time.
In one embodiment, the rule selection information includes service scene identification information, and obtaining the target rule from the rule base according to the rule selection information includes: and screening all or part of configured rules in the business scene corresponding to the business scene identification information from the rule library as target rules.
In this embodiment, the execution rule according to the service scenario may be supported, and if the rule selection information in the risk screening request of the target trip sent by the service caller is the service scenario identification information, all or part of the rules under the corresponding service scenario may be executed as the target rule according to the service scenario identification.
In one embodiment, the rule selection information is rule identification information, and the obtaining the target rule from the rule base according to the rule selection information includes: and screening the configured rule corresponding to the rule identification information from the rule base as a target rule.
In this embodiment, it may be supported to execute a single rule according to a rule ID (Identity), and if rule selection information in a risk screening request of a target trip sent by a service caller is rule identification information, it may be executed according to a rule that the rule identification information determines a corresponding ID.
According to the two embodiments, the flexibility of rule selection can be improved according to the difference of the received rule selection information, so that the flexibility of risk screening is improved, the adaptive rule can be flexibly screened according to the user requirement without modifying a hard code, and accurate and various screening services are provided for a service caller.
Step S206: and analyzing each rule factor in the target rule, determining the index corresponding to each rule factor, and obtaining the storage information preconfigured for each index.
Wherein the target rule includes at least one rule factor, and the rule factor is configurable, for example, the rule factor can be configured in a JOSN mode. Different rule factors may be combined differently in units of rule factors, thereby generating different rules.
Specifically, the server analyzes each rule factor in the target rule, determines what the index pointed to by each rule factor corresponds to, and obtains storage information configured corresponding to each index, wherein the storage information comprises the type of a database corresponding to each index and the position information of each index in the database.
Illustratively, the rule factor may be:
A. average running speed of total journey is greater than XX km/h
B. The number of times of danger report is greater than XX times
C. The order type is XX model.
……
The user can perform rule configuration based on the cloud configuration center, after a plurality of rule factors are combined and configured, the server can generate and issue configured rules according to the received configuration data in response to a rule issuing instruction triggered by the user. For the rule factors a to C, the index corresponding to the rule factor a may be the average running speed of the total journey, the index corresponding to the rule factor B is the number of risk reporting, and the index corresponding to the rule factor C is the order type. Different indexes can be correspondingly configured with different storage information, and execution data corresponding to the indexes are respectively stored in corresponding databases or data tables according to the different storage information.
By way of example, the metrics may include average travel speed for the total trip, number of hazards, type of order, distance between the driver and passenger when they match, and time difference between completion of two similar trip orders in the driver dimension.
Illustratively, the method for acquiring the index may include: and extracting index data corresponding to each index from the running data by the running data of each vehicle associated with the real-time task or the off-line task processing platform, and respectively storing the extracted index data into a corresponding database according to the storage information of each index.
Step S208: and acquiring the execution parameters corresponding to the rule factors according to the journey identification information and the storage information of the indexes.
Specifically, the server determines a database and a storage position where each index is located according to each storage information, inquires index data of a target journey from the determined storage position according to journey identification information, and uses the index data of the target journey as an execution parameter corresponding to each rule factor, so that whether the data formed by the target meets the requirement of the rule factors is judged.
Step S210: and carrying out risk screening on the target journey according to the target rule, each execution parameter and the supplementary parameter.
Specifically, after the server obtains the execution parameters of each rule factor from different storage positions according to different storage information, a rule executor can be called, and the rule executor analyzes the target rule, utilizes the execution parameters and combines the supplementary parameters to perform risk judgment, so as to judge whether the target journey has risk.
According to the risk journey screening method, after a risk screening request is received, the target rule is determined according to the rule selection information, indexes corresponding to the rule factors are determined by analyzing the rule factors configured in the target rule, and execution parameters of the target journey are obtained according to the storage information corresponding to the pre-configured indexes, so that risk screening for the target journey is achieved. By adopting the method, the service calling party can automatically screen rules and accurately call the execution parameters and execute the rules only by sending out the request and according to the related request information, thereby improving the efficiency and timeliness of risk screening.
In one embodiment, the method further comprises: receiving a plurality of rule factors configured based on a configuration interface; receiving storage information of indexes corresponding to rule factors configured based on a configuration interface; wherein the storage information comprises type information and storage position information of a storage database; responding to a rule issuing instruction, and generating configured rules according to the received data; and analyzing and pre-compiling the configured rules and storing the configured rules.
In this embodiment, the user may customize the rule factors based on the configuration center, and may customize the stored information of the indicators corresponding to each rule factor. On one hand, the expression formed by the rule factors is easy to understand, the learning cost is low, the service personnel can directly configure, the change of the rule does not need the participation of a back-end code developer, the whole period time from the requirement stage to the online of the rule is shortened, on the other hand, the mode of acquiring the execution parameters of the rule is unified because the storage information of the index corresponding to each rule factor is configurable, different indexes can configure different databases without unified data sources, and the type of the database for storing the execution parameters is not limited and expandable, for example, h-base, ES and the like.
In one embodiment, the method further comprises: monitoring the update of each rule factor of the configured rule in real time, analyzing and precompiling the updated rule, and storing the rule into a rule base; monitoring the updating of the storage information of the index corresponding to each rule factor of the configured rule in real time, and storing the updated storage information of the index corresponding to each rule factor into a factor information database or a factor information cache.
According to the embodiment, the change of the rule can be found in time by monitoring the update of the rule factors and the update of the stored information in real time, so that the quasi-real-time online of the rule is realized, and the accuracy and the efficiency of risk screening are improved.
In the following, a further detailed description of the risk trip screening method related to the present application is described with reference to fig. 3, and fig. 3 shows a schematic flow chart of the risk trip screening method in an application example. Specifically, the following may be included:
1. the user may perform rule configuration in the cloud configuration center, for example, may configure rule factors included in the rules and stored information of indexes (source data) corresponding to the rule factors.
2. And the server of the cloud configuration center monitors the rule factors and the change of the stored information in real time or periodically, and timely updates the rules and the cache of the stored information.
3. And processing the history or real-time travel data of each associated vehicle through the real-time task and the off-line task, extracting index data and storing the index data into a database corresponding to each index.
4. When a service caller invokes a risk screening service through an RPC (Remote Procedure Call ) interface, the service caller sends a risk screening request of a target trip to a server based on a terminal, wherein the risk screening request may include the following information: the risk screening request includes trip identification information, rule selection information, and supplemental parameters. The server acquires target rules from the rule base according to the rule selection information; analyzing each rule factor in the target rule, determining an index corresponding to each rule factor, and obtaining storage information preconfigured for each index; acquiring execution parameters corresponding to each rule factor according to the travel identification information and the storage information of each index; and carrying out risk screening on the target journey according to the target rule, each execution parameter and the supplementary parameter.
5. Further, after the risk screening result is obtained, the server may feed back the result to the terminal where the service caller is located.
It should be understood that, although the steps in the flowcharts of fig. 1 and 3 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1 and 3 may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed sequentially, but may be performed alternately or alternately with at least a portion of the other steps or sub-steps of other steps.
In one embodiment, as shown in fig. 4, there is provided a risk trip screening apparatus comprising: a request receiving module 410, a rule selecting module 420, a factor analyzing module 430, a parameter obtaining module 440, and a risk screening module 450, wherein:
a request receiving module 410, configured to receive a risk screening request of a target trip sent by a service caller; the risk screening request comprises journey identification information, rule selection information and supplementary parameters;
the rule selection module 420 is configured to obtain a target rule from the rule base according to the rule selection information;
the factor analysis module 430 is configured to analyze each rule factor in the target rule, determine an index corresponding to each rule factor, and obtain storage information preconfigured for each index;
a parameter obtaining module 440, configured to obtain execution parameters corresponding to each rule factor according to the trip identification information and the stored information of each index;
the risk screening module 450 is configured to perform risk screening on the target trip according to the target rule, each execution parameter, and the supplementary parameter.
In one embodiment, the rule selection information includes service scenario identification information, and the rule selection module 420 screens all or part of the configured rules in the service scenario corresponding to the service scenario identification information from the rule base as target rules.
In one embodiment, the rule selection information is rule identification information, and the rule selection module 420 screens the configured rule corresponding to the rule identification information from the rule base as a target rule.
In one embodiment, risk screening module 450 is further configured to receive a plurality of rule factors configured based on the configuration interface; receiving storage information of indexes corresponding to rule factors configured based on a configuration interface; wherein the storage information comprises type information and storage position information of a storage database; responding to a rule issuing instruction, and generating configured rules according to the received data; and analyzing and pre-compiling the configured rules and storing the configured rules.
In one embodiment, the risk screening module 450 is further configured to monitor, in real time, the update of each rule factor of the configured rule, parse and precompiled the updated rule, and store the rule in the rule base; monitoring the updating of the storage information of the index corresponding to each rule factor of the configured rule in real time, and storing the updated storage information of the index corresponding to each rule factor into a factor information database or a factor information cache.
For specific limitations of the risk trip screening device, reference may be made to the limitations of the risk trip screening method hereinabove, and no further description is given here. The various modules in the risk trip screening apparatus described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing source data corresponding to each index. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor implements a risk trip screening method.
It will be appreciated by those skilled in the art that the structure shown in fig. 5 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program: receiving a risk screening request of a target journey sent by a service calling party; the risk screening request comprises journey identification information, rule selection information and supplementary parameters; acquiring a target rule from a rule base according to rule selection information; analyzing each rule factor in the target rule, determining an index corresponding to each rule factor, and obtaining storage information preconfigured for each index; acquiring execution parameters corresponding to each rule factor according to the travel identification information and the storage information of each index; and carrying out risk screening on the target journey according to the target rule, each execution parameter and the supplementary parameter.
In one embodiment, when the processor executes the computer program to obtain the target rule from the rule base according to the rule selection information, the following steps are specifically implemented: and screening all or part of configured rules in the business scene corresponding to the business scene identification information from the rule library as target rules.
In one embodiment, when the processor executes the computer program to obtain the target rule from the rule base according to the rule selection information, the following steps are specifically implemented: and screening the configured rule corresponding to the rule identification information from the rule base as a target rule.
In one embodiment, execution of the computer program by the processor further implements the steps of: receiving a plurality of rule factors configured based on a configuration interface; receiving storage information of indexes corresponding to rule factors configured based on a configuration interface; wherein the storage information comprises type information and storage position information of a storage database; responding to a rule issuing instruction, and generating configured rules according to the received data; and analyzing and pre-compiling the configured rules and storing the configured rules.
In one embodiment, execution of the computer program by the processor further implements the steps of: monitoring the update of each rule factor of the configured rule in real time, analyzing and precompiling the updated rule, and storing the rule into a rule base; monitoring the updating of the storage information of the index corresponding to each rule factor of the configured rule in real time, and storing the updated storage information of the index corresponding to each rule factor into a factor information database or a factor information cache.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of: receiving a risk screening request of a target journey sent by a service calling party; the risk screening request comprises journey identification information, rule selection information and supplementary parameters; acquiring a target rule from a rule base according to rule selection information; analyzing each rule factor in the target rule, determining an index corresponding to each rule factor, and obtaining storage information preconfigured for each index; acquiring execution parameters corresponding to each rule factor according to the travel identification information and the storage information of each index; and carrying out risk screening on the target journey according to the target rule, each execution parameter and the supplementary parameter.
In one embodiment, when the computer program is executed by the processor to obtain the target rule from the rule base according to the rule selection information, the following steps are specifically implemented: and screening all or part of configured rules in the business scene corresponding to the business scene identification information from the rule library as target rules.
In one embodiment, when the computer program is executed by the processor to obtain the target rule from the rule base according to the rule selection information, the following steps are specifically implemented: and screening the configured rule corresponding to the rule identification information from the rule base as a target rule.
In one embodiment, execution of the computer program by the processor further implements the steps of: receiving a plurality of rule factors configured based on a configuration interface; receiving storage information of indexes corresponding to rule factors configured based on a configuration interface; wherein the storage information comprises type information and storage position information of a storage database; responding to a rule issuing instruction, and generating configured rules according to the received data; and analyzing and pre-compiling the configured rules and storing the configured rules.
In one embodiment, execution of the computer program by the processor further implements the steps of: monitoring the update of each rule factor of the configured rule in real time, analyzing and precompiling the updated rule, and storing the rule into a rule base; monitoring the updating of the storage information of the index corresponding to each rule factor of the configured rule in real time, and storing the updated storage information of the index corresponding to each rule factor into a factor information database or a factor information cache.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. A risk trip screening method, the method comprising:
receiving a plurality of rule factors configured based on a configuration interface; receiving storage information of indexes corresponding to the rule factors configured based on a configuration interface; wherein the storage information comprises type information and storage position information of a storage database;
extracting index data corresponding to each index from the running data through the running data of each vehicle associated with the real-time task or the off-line task processing platform, and respectively storing the extracted index data into a corresponding database according to the pre-configured storage information of each index;
receiving a risk screening request of a target journey sent by a service calling party; the risk screening request comprises journey identification information, rule selection information and supplementary parameters, wherein the supplementary parameters are data generated in real time in the process of carrying out the target journey;
acquiring a target rule from a rule base according to the rule selection information;
analyzing each rule factor in the target rule, determining an index corresponding to each rule factor, and obtaining storage information preconfigured for each index;
acquiring execution parameters corresponding to the rule factors according to the travel identification information and the storage information of the indexes;
and calling a rule executor, wherein the rule executor performs risk screening on the target journey by analyzing the target rule and utilizing the execution parameters and combining the supplementary parameters.
2. The method of claim 1, wherein the rule selection information includes service scenario identification information, and wherein the obtaining the target rule from the rule base according to the rule selection information includes:
and screening all or part of configured rules under the service scene corresponding to the service scene identification information from a rule base to serve as the target rules.
3. The method according to claim 1, wherein the rule selection information is rule identification information, and the obtaining the target rule from the rule base according to the rule selection information includes:
and screening the configured rule corresponding to the rule identification information from a rule base to serve as the target rule.
4. The method of claim 1, wherein the supplemental parameters include at least one of a current average travel speed of the target trip, a difference between a pick-up time and a last on-line time prior to pick-up by the driver, a current travelled distance, and a trip start point of the order and a matching distance of the driver.
5. The method of claim 1, wherein the indicators include average speed of travel for total trips, number of hazards, type of order, distance between positions when driver and passenger are matched, time difference between completion of two similar trips in driver dimension.
6. The method according to claim 1, wherein the method further comprises:
responding to a rule issuing instruction, and generating configured rules according to the received configured data;
and analyzing and pre-compiling the configured rules and storing the configured rules.
7. The method of claim 6, wherein the method further comprises:
monitoring the updating of each rule factor of the configured rule in real time, analyzing and precompiling the updated rule, and storing the rule into the rule base;
monitoring the updating of the storage information of the index corresponding to each rule factor of the configured rule in real time, and storing the updated storage information of the index corresponding to each rule factor into a factor information database or a factor information cache.
8. A risk trip screening device, the device comprising:
a risk screening module for receiving a plurality of rule factors configured based on a configuration interface; receiving storage information of indexes corresponding to the rule factors configured based on a configuration interface; wherein the storage information comprises type information and storage position information of a storage database; extracting index data corresponding to each index from the running data through the running data of each vehicle associated with the real-time task or the off-line task processing platform, and respectively storing the extracted index data into a corresponding database according to the pre-configured storage information of each index;
the request receiving module is used for receiving a risk screening request of a target journey sent by a service calling party; the risk screening request comprises journey identification information, rule selection information and supplementary parameters, wherein the supplementary parameters are data generated in real time in the process of carrying out the target journey;
the rule selection module is used for acquiring a target rule from a rule base according to the rule selection information;
the factor analysis module is used for analyzing each rule factor in the target rule, determining an index corresponding to each rule factor and acquiring storage information preconfigured for each index;
the parameter acquisition module is used for acquiring execution parameters corresponding to the rule factors according to the travel identification information and the storage information of the indexes;
the risk screening module is further used for calling a rule executor, and the rule executor performs risk screening on the target journey by analyzing the target rule and utilizing the execution parameters and combining the supplementary parameters.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310085024.0A CN115795185B (en) | 2023-01-28 | 2023-01-28 | Risk trip screening method, risk trip screening device, computer equipment and storage medium |
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| WO2020037942A1 (en) * | 2018-08-20 | 2020-02-27 | 平安科技（深圳）有限公司 | Risk prediction processing method and apparatus, computer device and medium |
| CN114693192A (en) * | 2022-06-01 | 2022-07-01 | 四川高灯企服科技有限公司 | Wind control decision method and device, computer equipment and storage medium |
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| CN113361838A (en) * | 2020-03-04 | 2021-09-07 | 北京沃东天骏信息技术有限公司 | Business wind control method and device, electronic equipment and storage medium |
| CN115222176A (en) * | 2021-04-20 | 2022-10-21 | 京东科技控股股份有限公司 | Risk control method, apparatus, device and medium |
| CN114115967A (en) * | 2021-11-17 | 2022-03-01 | 南京苏宁电子信息技术有限公司 | Service data processing method and device, computer equipment and storage medium |
| CN114913005A (en) * | 2022-06-21 | 2022-08-16 | 中银金融科技有限公司 | Mobile risk data detection method, mobile risk data detection system, electronic device and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2020037942A1 (en) * | 2018-08-20 | 2020-02-27 | 平安科技（深圳）有限公司 | Risk prediction processing method and apparatus, computer device and medium |
| CN114693192A (en) * | 2022-06-01 | 2022-07-01 | 四川高灯企服科技有限公司 | Wind control decision method and device, computer equipment and storage medium |
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