CN116645136A - User attribute data trial calculation verification method and device of online platform and terminal - Google Patents

User attribute data trial calculation verification method and device of online platform and terminal Download PDF

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CN116645136A
CN116645136A CN202310299833.1A CN202310299833A CN116645136A CN 116645136 A CN116645136 A CN 116645136A CN 202310299833 A CN202310299833 A CN 202310299833A CN 116645136 A CN116645136 A CN 116645136A
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description information
trial calculation
order data
rule
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陈明日
梁金惠
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Hangzhou Shuyun Information Technology Co ltd
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Hangzhou Shuyun Information Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06F16/23—Updating
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    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution
    • G06F16/24564—Applying rules; Deductive queries
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    • G06F—ELECTRIC DIGITAL DATA PROCESSING
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    • G—PHYSICS
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
    • G06Q30/0635—Processing of requisition or of purchase orders
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

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Abstract

A user attribute data trial calculation verification method, a device and a terminal of an online platform, wherein the method comprises the following steps: receiving newly added rule description information, wherein the rule description information is used for describing a rule operator and order conditions corresponding to the rule operator; according to the newly added rule description information, trial calculation is carried out based on order data in a shadow database to obtain a trial calculation result, wherein the trial calculation result refers to attribute data to be obtained by a user applying the newly added rule description information, and the shadow database is updated along with a service database in real time; and responding to a confirmation instruction aiming at the trial calculation result, adding the newly added rule description information into a standard rule base, wherein the rule description information in the standard rule base is used for calculating user attribute data based on order data in the service database. By the scheme provided by the application, the rule verification can be realized on the premise of not influencing the normal operation of the on-line platform service.

Description

User attribute data trial calculation verification method and device of online platform and terminal
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a method and an apparatus for verifying user attribute data of an online platform.
Background
With the development of internet technology, consumption modes are continuously innovated. More and more merchants generally issue points or set grades for users in order to increase the viscosity of the users, and the more the points and the higher the grades, the more the user can enjoy the preferential usually, and the user can be stimulated to consume for the second time through the points or the grades.
For this reason, merchants often set a variety of points issuing rules, user upgrading rules, etc. to effectively increase the viscosity of users. However, the unverified rule is directly online, the accuracy of the rule cannot be guaranteed, and the error distribution of the points may be caused, so that not only the economic loss of the merchant is caused, but also the consumption experience of the user is affected.
Disclosure of Invention
The technical aim of the embodiment of the application is to provide a user attribute data trial calculation verification method, device and terminal of an online platform, which can realize the verification of rules on the premise of not influencing the normal operation of online platform business.
In order to achieve the above technical purpose, an embodiment of the present application provides a method for performing trial-and-error verification on user attribute data of an online platform, where the method includes: receiving newly added rule description information, wherein the rule description information is used for describing a rule operator and order conditions corresponding to the rule operator; according to the newly added rule description information, trial calculation is carried out based on order data in a shadow database to obtain a trial calculation result, wherein the trial calculation result refers to attribute data to be obtained by a user applying the newly added rule description information, and the shadow database is updated along with a service database in real time; and responding to a confirmation instruction aiming at the trial calculation result, adding the newly added rule description information into a standard rule base, wherein the rule description information in the standard rule base is used for calculating user attribute data based on order data in the service database.
Optionally, the performing trial calculation based on the order data in the shadow library includes: according to the newly added rule description information, trial calculation is carried out based on the historical order data in the shadow library, and a first trial calculation result is obtained; responding to a confirmation instruction aiming at the first trial calculation result, and adding the newly added rule description information into an intermediate rule base; and responding to target order data entering the shadow library, and performing trial calculation based on the target order data to obtain a second trial calculation result, wherein the target order data is order data meeting the order condition.
Optionally, before adding the new rule description information to the standard rule base, the method further includes: outputting the second trial calculation result; the adding the newly added rule description information into a standard rule base comprises the following steps: and responding to a confirmation instruction aiming at the second trial calculation result, and adding the newly added rule description information into the standard rule base.
Optionally, performing trial calculation based on order data in the shadow library, and obtaining the trial calculation result includes: searching target order data in the historical order data in the shadow library according to the order condition; and if the target order data is not found in the shadow library, acquiring the custom order data, wherein the custom order data is generated according to the order condition construction.
Optionally, the method further comprises: and saving the trial calculation result in the shadow library.
Optionally, before the receiving the new rule description information, the method further includes: responding to an input checking instruction, and checking the rule operator and/or the attribute expression of the order condition based on test order data to obtain a checking result; the receiving the newly added rule description information comprises the following steps: and receiving the newly added rule description information in response to a confirmation instruction for the checking result.
Optionally, the performing trial calculation based on the order data in the shadow library includes: trial calculation is carried out based on target order data in the shadow library, and trial calculation is carried out based on non-target order data in the shadow library; the target order data is order data meeting the order condition, and the target order data is order data not meeting the order condition.
The embodiment of the application also provides a trial calculation device of the user attribute data of the online platform, which comprises: the receiving module is used for receiving the newly added rule description information, and the rule description information is used for describing rule operators and order conditions corresponding to the rule operators; the trial calculation module is used for carrying out trial calculation based on order data in a shadow database according to the newly-added rule description information to obtain a trial calculation result, wherein the trial calculation result is attribute data to be obtained by a user applying the newly-added rule description information, and the shadow database is updated along with a service database in real time; and the updating module is used for responding to a confirmation instruction aiming at the trial calculation result, adding the newly added rule description information into a standard rule base, wherein the rule description information in the standard rule base is used for calculating the user attribute data based on the order data in the service database.
The embodiment of the application also provides a computer readable storage medium, on which a computer program is stored, which when being run by a processor, performs the steps of the trial-and-error verification method of user attribute data of the online platform.
The embodiment of the application also provides a terminal, which comprises a memory and a processor, wherein the memory stores a computer program which can be run on the processor, and the processor executes the step of trial-and-error verification of the user attribute data of the online platform when the computer program is run.
Compared with the prior art, the technical scheme of the embodiment of the application has the following beneficial effects:
in the scheme of the embodiment of the application, newly added rule description information is received, the rule description information is used for describing rule operators and order conditions corresponding to the rule operators, then trial calculation is carried out based on order data in a shadow library according to the newly added rule description information to obtain a trial calculation result, and the newly added rule description information is added into a standard rule library in response to a confirmation instruction aiming at the trial calculation result. According to the scheme, aiming at the newly added rule description information, trial calculation is carried out by adopting order data in a shadow library updated along with the service database to obtain a trial calculation result, so that the trial calculation and verification process of the rule in the scheme does not depend on the service database, and the influence on the service database can be avoided while the trial calculation and verification of the rule are realized.
Further, in the scheme of the embodiment of the application, the trial calculation verification process comprises two stages, wherein the trial calculation is firstly performed based on the historical order data in the shadow library to obtain a first trial calculation result, and if the first trial calculation result is confirmed, the newly added rule description information is added into the intermediate rule library; and then when target order data is entered in the shadow library, adopting the target order data to perform trial calculation to obtain a second trial calculation result. By adopting the scheme, the history order data can be adopted to carry out trial calculation and verification on the newly added rule description information, and the real-time order data can be also adopted to carry out trial calculation and verification, so that the effect of real-time operation after the newly added rule is online can be simulated, and the accuracy of the trial calculation verification result is more beneficial to ensuring.
Further, in the solution of the embodiment of the present application, if the target order data is not found in the shadow library, custom order data is obtained, where the custom order data is generated according to the order condition construction. By adopting the scheme, the situation that trial calculation and verification cannot be performed due to the fact that order data meeting the order conditions are not found in the shadow library can be avoided, so that the feasibility of the scheme is ensured.
Further, in the scheme of the embodiment of the application, the rule operator and/or the attribute expression of the order condition are checked based on the test order data to obtain a check result, and under the condition that the check result is confirmed, the newly added rule description information is checked. By adopting the scheme, the condition that the attribute expression is wrongly written and cannot be checked and verified by trial calculation can be avoided, and the accuracy of the checking and verification is improved.
Drawings
Fig. 1 is a schematic view of an application scenario of a trial-computing verification method for user attribute data of an online platform in an embodiment of the present application;
FIG. 2 is a flowchart of a method for trial-computing and verifying user attribute data of an online platform according to an embodiment of the present application;
FIG. 3 is a flowchart of another method for trial-and-error verification of user attribute data of an online platform according to an embodiment of the present application;
FIG. 4 is a flowchart of a method for trial-and-error verification of user attribute data of an online platform according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a trial-computing verification device for user attribute data of an online platform according to an embodiment of the present application.
Detailed Description
As described in the background, validating rules can be advantageous in avoiding false releases of points.
If the rule verification module is generally and directly deployed in an online environment, checking calculation is performed according to an order generated by an online platform in real time, in this case, if a checking result indicates that a rule is wrong, the rule needs to be stopped and then modified, so that the normal operation of the online platform is easily affected.
In view of this, an embodiment of the present application provides a trial calculation method for user attribute data of an online platform, in the solution of the embodiment of the present application, newly added rule description information is received, the rule description information is used to describe a rule operator and an order condition corresponding to the rule operator, then trial calculation is performed based on order data in a shadow library according to the newly added rule description information, so as to obtain a trial calculation result, and the newly added rule description information is added into a standard rule library in response to a confirmation instruction for the trial calculation result. According to the scheme, aiming at the newly added rule description information, trial calculation is carried out by adopting order data in a shadow library updated along with the service database to obtain a trial calculation result, so that the trial calculation and verification process of the rule in the scheme does not depend on the service database, and the influence on the service database can be avoided while the trial calculation and verification of the rule are realized.
In order to make the above objects, features and advantages of the present application more comprehensible, embodiments accompanied with figures are described in detail below.
Referring to fig. 1, fig. 1 is an application scenario schematic diagram of a user attribute data trial-computing verification method of an online platform in an embodiment of the application.
In particular, the online platform 10 may be a server that generates order data. The order data may be generated based on the act of purchasing the merchandise by the user, which may be referred to as the consumer. More specifically, the order data may include: purchase time, purchase item identification, amount, purchase channel, etc. In addition, the order data may also include user information, such as a user's birthday, etc.
In an embodiment, the online platform 10 may refer to a third party platform that a user and a merchant conduct transactions, the user may purchase goods issued by the merchant on the online platform 10, and the online platform 10 may generate order data in response to a payment success message of the user. The online platform 10 supports multiple merchants, each of which can maintain respective user attribute data, i.e., the user attribute data of different merchants are independent and can be calculated according to the own order data of the merchants.
Optionally, the online platform 10 has an interface accessible to the merchant, when the user purchases the commodity at the offline store of the merchant, the staff of the merchant can input the commodity information purchased by the user through the interface of the online platform 10, and the online platform 10 can generate order data according to the input information. The generated order data is attributed to the merchant entering the information and the online platform 10 may calculate user attribute data based on the order data according to pre-configured rules.
Further, order data generated by the online platform 10 may be stored in the business database 20 and the shadow library 30, respectively.
As shown in fig. 1, the online platform 10 may be coupled to the service database 20 and the shadow library 30, respectively, and the service database 20 and the shadow library 30 may be two databases independent of each other, in other words, the service database 20 and the shadow library 30 are data-isolated.
In particular implementations, the shadow library 30 is updated in real-time with the business database 20.
Specifically, each time the online platform 10 generates order data, the order data may be sent to and stored in the service database 20, and the online platform 10 may copy the order data and send and store the copied order data in the shadow library 30. Thus, whenever order data enters the business database 20, the order data also enters the shadow library 30, i.e., a backup of the order data of the business database may be stored in the shadow library 30.
In particular implementations, the business database 20 may be configured with a standard rule base (not shown) that may include a plurality of pieces of rule description information, where the rule description information in the standard rule base is rule description information in an operational state.
In the scheme of the embodiment of the application, the rule description information can be used for describing the rule operator and the order condition corresponding to the rule operator, wherein the order condition can be order data for limiting the calculation of the user attribute data by applying the rule operator, and the rule operator can refer to a calculation mode of the user attribute data. For example, the rule description information may be: double the first order score of the sun, wherein the order condition is: the first order of the sun and moon is given, and the rule operator is the integral double.
Specifically, each time order data enters the service database 20, user attribute data corresponding to the order data may be calculated according to a rule description text to which the order data is matched, wherein the user attribute data may be points, grades, coupons, etc. of the user, but is not limited thereto. Taking the points as an example, each time the user orders and purchases goods, the points and the like can be distributed to the user aiming at the current purchase of the user according to the rule description information, and the distributed points are the user attribute data.
More specifically, whenever order data enters the business database 20, the rule description text that the order data matches may be searched in a standard rule base, where the rule description text that the order data matches may refer to rule description information that the order data meets the order condition. Further, the rule operators in the searched rule description information are used for calculating the user attribute data corresponding to the order data, and then the existing user attribute data of the user can be updated according to the calculated user attribute data.
Referring to fig. 2, fig. 2 is a flow chart of a method for verifying user attribute data of an online platform according to an embodiment of the application. The method may be performed by a terminal, which may be a terminal used by a merchant, and which may be any suitable terminal, for example, but not limited to, a mobile phone, a computer, an internet of things device, a tablet computer, etc. The method shown in fig. 2 may include:
step S21: receiving newly added rule description information, wherein the newly added rule description information is used for describing a rule operator and order conditions corresponding to the rule operator;
step S22: according to the newly added rule description information, trial calculation is carried out based on order data in a shadow database to obtain a trial calculation result, wherein the trial calculation result refers to attribute data to be obtained by a user applying the newly added rule description information, and the shadow database is updated along with a service database in real time;
step S23: and responding to a confirmation instruction of the user for the trial calculation result, adding the newly added rule description information into a standard rule base, wherein the rule description information in the standard rule base is used for calculating attribute data of the user based on order data in the service database.
It will be appreciated that in a specific implementation, the method may be implemented in a software program running on a processor integrated within a chip or a chip module; alternatively, the method may be implemented in hardware or a combination of hardware and software, for example, implemented in a dedicated chip or chip module, or implemented in a dedicated chip or chip module in combination with a software program.
In the specific implementation of step S21, newly added rule description information may be received, where the newly added rule description information may refer to rule description information to be calculated or verified.
As a possible implementation, the newly added rule description information may be rule description information that has not yet been run. Specifically, the newly added rule description information may not have been added to the standard rule base. For example, the newly added rule description information may be newly created rule description information of the merchant side, or the newly added rule description information may also be rule description information to be checked by the merchant side, or the like.
As another possible implementation, the newly added rule description information may also be running rule description information. Specifically, the newly added rule description information may be rule description information in a standard rule base. For example, in step S21, the merchant may select rule description information to be calculated or verified from the standard rule base, and in response to the selection instruction of the merchant, the rule description information selected by the merchant may be read from the standard rule base, and may be used as the newly added rule description information to perform the subsequent steps.
In the implementation of step S22, trial calculation may be performed based on the order data in the shadow library according to the rule description information that is newly added, so as to obtain a trial calculation result. The trial calculation result may be user attribute data to be obtained by the user for the order data by applying the rule description information newly added.
The configuration of the shadow library may be global, i.e., all merchants have a shadow library, which may be uniform or may be set individually for each merchant. Alternatively, the configuration of the shadow library may be local and may be validated upon request by the merchant. That is, if a merchant requests to set up a shadow library, a unique shadow library is set up for the merchant alone, while a merchant that does not issue a request does not have a unique shadow library. In this way, the system load of the online platform can be reduced as much as possible. The shadow library remains synchronously updated with the data updates of the business database, i.e., each time the order data in the business database is updated, the shadow library also remains mirrored updated. However, the reverse updates are not synchronized, i.e., changes in the shadow library data do not affect the business database.
Specifically, trial calculations based on order data in the shadow library may include: and reading order data for trial calculation verification from the shadow library according to order conditions described by the newly added rule description information, searching target order data, and performing trial calculation based on the read order data to obtain a trial calculation result.
More specifically, target order data may be searched in the shadow library according to the order condition described by the rule description information added, wherein the target order data may refer to order data satisfying the order condition. In addition, non-target order data, which may be order data that does not satisfy the order condition, may also be read from the shadow library.
For example, if the rule description information is "double points of the first order of the sun and moon" and the target order data is the order data purchased by the consumer for the first time of the sun and moon, the non-target order data may be the order data purchased by the consumer at other times than the sun and moon, or the order data purchased by the consumer for the second time of the sun and moon, etc.
Further, performing trial calculations based on the target order data may include: and calculating the order amount in the order data by adopting a rule operator described by the newly added rule description information, thereby obtaining a trial calculation result.
It should be noted that, because the non-target order data does not satisfy the order condition, when trial calculation is performed based on the non-target order data, calculation is not performed by using the rule operators described by the newly added rule description information. Illustratively, the calculation may be based on a general rule operator to obtain trial results for non-target order data. The universal rule operator may be a preset universal operator, for example, the universal rule operator may be a single integral.
More specifically, if the target order data is not searched in the shadow library, custom order data may also be obtained. The custom order data may be generated according to the order condition configuration described by the rule description information added. In other words, the custom order data satisfies the order conditions described by the newly added rule description information. For example, custom order data may be input after custom by the merchant according to the order conditions; as another example, custom order data may be automatically generated based on the order conditions described by the newly added rule description information and a random generation algorithm.
Further, trial calculation can be performed based on the custom order data, and a trial calculation result is obtained. The custom order data may be stored in a shadow library.
Further, after the calculation result is obtained, the calculation result may be saved in the shadow library. In addition, the trial calculation result can be output to the merchant side, and the staff of the merchant side can confirm the trial calculation result. For example, order data for trial verification and trial results may be presented to the user in the form of text, charts, voice, or the like, which is not limited in this embodiment.
In step S23, in response to the confirmation instruction for the trial calculation result, the newly added rule description information may be added to the standard rule base.
Specifically, if the trial result of the order data for trial verification is confirmed, it may be characterized that the order data passes the trial verification and may be run online. In addition, if the trial result merchant side of the order data for trial verification denies, it may be characterized that the order data fails the trial verification and cannot be run online.
In one possible implementation manner, the newly added rule description information is read from the standard rule base, and if a confirmation instruction for the trial calculation result is received, the newly added rule description information can be kept in the standard rule base; if a denial instruction of the staff is received, that is, the trial-and-error structure is denied, the newly added rule description information can be removed from the standard rule base.
In another possible implementation manner, the new rule description information is not read from the standard rule base, and if a confirmation instruction for the trial calculation result is received, the new rule description information may be added to the standard rule base, so that the online operation is performed; if a denial instruction for the trial calculation result is received, the new rule description information can be deleted.
By the scheme provided by the embodiment of the application, the online flow is copied to the gray rule test run through the setting of the shadow library, the historical data is tested back through the test calculation of the rule, and the accuracy of the rule is ensured after verification, and then the formal online run is carried out.
Referring to fig. 3, fig. 3 is a flowchart illustrating another method for verifying user attribute data of an online platform according to an embodiment of the present application. The method shown in fig. 3 may include step S31 and step S32, and may further include S21 to step S23 after step S32. The following description will be mainly made with respect to step S31 and step S32, and the details of step S21 to step S23 may refer to the relevant descriptions of fig. 1 and fig. 2, which are not repeated herein.
And step S31, responding to the checking instruction, and checking the rule operator and/or the attribute expression of the order condition based on the test order data to obtain a checking result.
In particular, the rule description information may include a plurality of attribute expressions, which may be expressions that code the rule operators and/or order conditions described above.
In step S31, the merchant party may input a checking instruction, which may be used to trigger checking of the attribute expression selected by the merchant party. Thus, in response to the checking instruction, the attribute expression selected by the merchant party can be checked based on the test order data, and a checking result is obtained.
Wherein the test order data may be preset, more specifically, the test order data may be order data dedicated to the verification of the attribute expression. The attribute expression selected by the merchant side can be the attribute expression of the order condition or the attribute expression of the rule operator. The inspection results may be information in the test order data from the run attribute expression. For example, the attribute expression is an attribute expression of the user's birthday, and the user's birthday in the test order data is 1 month 1 day 1990, and the result of the inspection may be 1 month 1 day 1990.
And step S32, outputting the checking result. Specifically, the checking result may be output to the merchant side for the merchant side to determine whether the writing of the attribute expression is correct. If the result is correct, the merchant side can input or select the newly added rule description information, the terminal can further execute step S21, and if the result is incorrect, the merchant side can modify the attribute expression.
According to the scheme, the fact that the rule description information consists of the attribute expressions is considered, the complexity is high, the correctness is difficult to guarantee, and therefore the accuracy of writing of the attribute expressions is guaranteed by adding the attribute checking function, the condition that the attribute expressions cannot be checked and verified correctly due to the fact that the attribute expressions are wrongly written can be avoided, and the accuracy of checking and verifying is improved.
Referring to fig. 4, fig. 4 is a flowchart of a user attribute data trial-computing verification method of a further online platform according to an embodiment of the present application. The method shown in fig. 4 may include steps S41 to S45.
Step S41, receiving the newly added rule description information.
And step S42, according to the newly added rule description information, trial calculation is carried out based on the historical order data in the shadow library, and a first trial calculation result is obtained.
The historical order data in the shadow library may be existing order data in the shadow library when the new rule description information is received.
The details regarding step S41 and step S42 may be referred to above regarding the details of step S21 and step S22.
Step S43, in response to the confirmation instruction for the first trial calculation result, adding the newly added rule description information into the intermediate rule base.
Specifically, in the method shown in fig. 4, an intermediate rule base is also configured, which may be used to store rule description information, and the rule description information stored in the intermediate rule base is newly added rule description information in which the first trial result is confirmed.
In other words, if the first trial result is confirmed, it may be determined that the trial result of the newly added rule description information based on the historical order data is accurate, but further trial calculation based on the real-time order data is still required.
And step S44, responding to the target order data to enter a shadow library, and performing trial calculation based on the target order data to obtain a second trial calculation result.
In a specific implementation, each time the online platform generates order data, the backup of the generated order data may enter the shadow library, and further, each time the order data enters the shadow library, it may be determined whether the entered order data meets the order condition described by the newly added rule description information, that is, each time the order data enters the shadow library, it may be determined whether the entered order data is target order data. If the judgment result is yes, trial calculation can be carried out based on the target order data entering the shadow library, and a second trial calculation result is obtained. That is, the second trial result may be a result of trial calculation based on order data generated in real time.
Further, the second trial calculation result may be pushed to the merchant, and specifically, the reminding information may be sent to the merchant to prompt the newly added rule description information to be based on the trial calculation result of the real-time order data.
And step S45, the new rule description information is added into a standard rule base in response to a confirmation instruction aiming at the second trial calculation result.
Specifically, if a confirmation instruction of the merchant party for the second trial calculation result is received, the newly added rule description information may be added to the standard rule base.
By the scheme, the history order data can be adopted to perform trial calculation and verification on the newly added rule description information, and the real-time order data can be used for performing trial calculation and verification, so that the real-time operation effect after the newly added rule is online can be simulated, and the accuracy of the trial calculation verification result is more facilitated to be ensured.
It should be noted that, for more details of the user attribute data trial-and-error verification method for the online platform shown in fig. 4, reference may be made to the above description related to fig. 1 to 3, which is not repeated here.
Referring to fig. 5, fig. 5 is a schematic structural diagram of a user attribute data trial-computing verification device of an online platform according to an embodiment of the present application. As shown in fig. 5, the apparatus shown in fig. 5 may include:
the receiving module 51 is configured to receive newly added rule description information, where the rule description information is used to describe a rule operator and an order condition corresponding to the rule operator;
the trial calculation module 52 is configured to perform a trial calculation based on order data in a shadow database according to the new rule description information, so as to obtain a trial calculation result, where the trial calculation result is attribute data to be obtained by a user applying the new rule description information, and the shadow database is updated in real time along with a service database;
and an updating module 53, configured to add the newly added rule description information to a standard rule base in response to a confirmation instruction for the trial calculation result, where the rule description information in the standard rule base is used to calculate the user attribute data based on the order data in the service database.
Regarding more contents such as the working principle, the working method and the beneficial effects of the on-line platform user attribute data trial-calculation verification device in the embodiment of the present application, reference may be made to the above description about the on-line platform user attribute data trial-calculation verification method, which is not repeated here.
The embodiment of the application also provides a computer readable storage medium, on which a computer program is stored, which when being run by a processor, performs the steps of the above method. The storage medium may include ROM, RAM, magnetic or optical disks, and the like. The storage medium may also include a non-volatile memory (non-volatile) or a non-transitory memory (non-transitory) or the like.
The embodiment of the application also provides a terminal which comprises a memory and a processor, wherein the memory stores a computer program which can be run on the processor, and the processor executes the steps of the method when running the computer program. The terminal comprises, but is not limited to, a mobile phone, a computer, a tablet personal computer and other terminal equipment.
It should be appreciated that in the embodiment of the present application, the processor may be a central processing unit (central processing unit, abbreviated as CPU), and the processor may also be other general purpose processors, digital signal processors (digital signal processor, abbreviated as DSP), application specific integrated circuits (application specific integrated circuit, abbreviated as ASIC), off-the-shelf programmable gate arrays (field programmable gate array, abbreviated as FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It should also be appreciated that the memory in embodiments of the present application may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically erasable ROM (electrically EPROM, EEPROM), or a flash memory. The volatile memory may be a random access memory (random access memory, RAM for short) which acts as an external cache. By way of example and not limitation, many forms of random access memory (random access memory, RAM) are available, such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (double data rate SDRAM, DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), and direct memory bus RAM (direct rambus RAM, DR RAM)
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer program may be stored in or transmitted from one computer readable storage medium to another, for example, by wired or wireless means from one website, computer, server, or data center.
In the several embodiments provided in the present application, it should be understood that the disclosed method, apparatus and system may be implemented in other manners. For example, the device embodiments described above are merely illustrative; for example, the division of the units is only one logic function division, and other division modes can be adopted in actual implementation; for example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may be physically included separately, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in hardware plus software functional units. For example, for each device or product applied to or integrated on a chip, each module/unit included in the device or product may be implemented in hardware such as a circuit, or at least part of the modules/units may be implemented in software program, where the software program runs on a processor integrated inside the chip, and the rest (if any) of the modules/units may be implemented in hardware such as a circuit; for each device and product applied to or integrated in the chip module, each module/unit contained in the device and product can be realized in a hardware manner such as a circuit, different modules/units can be located in the same component (such as a chip, a circuit module and the like) or different components of the chip module, or at least part of the modules/units can be realized in a software program, the software program runs on a processor integrated in the chip module, and the rest (if any) of the modules/units can be realized in a hardware manner such as a circuit; for each device, product, or application to or integrated with the terminal, each module/unit included in the device, product, or application may be implemented by using hardware such as a circuit, different modules/units may be located in the same component (for example, a chip, a circuit module, or the like) or different components in the terminal, or at least part of the modules/units may be implemented by using a software program, where the software program runs on a processor integrated inside the terminal, and the remaining (if any) part of the modules/units may be implemented by using hardware such as a circuit.
It should be understood that the term "and/or" is merely an association relationship describing the associated object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, the character "/" indicates that the front and rear associated objects are an "or" relationship.
The term "plurality" as used in the embodiments of the present application means two or more. The first, second, etc. descriptions in the embodiments of the present application are only used for illustrating and distinguishing the description objects, and no order is used, nor is the number of the devices in the embodiments of the present application limited, and no limitation on the embodiments of the present application should be construed.
Although the present application is disclosed above, the present application is not limited thereto. Various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the application, and the scope of the application should be assessed accordingly to that of the appended claims.

Claims (10)

1. A user attribute data trial calculation verification method of an online platform is characterized by comprising the following steps:
receiving newly added rule description information, wherein the rule description information is used for describing a rule operator and order conditions corresponding to the rule operator;
according to the newly added rule description information, trial calculation is carried out based on order data in a shadow database to obtain a trial calculation result, wherein the trial calculation result refers to attribute data to be obtained by a user applying the newly added rule description information, and the shadow database is updated along with a service database in real time;
and responding to a confirmation instruction aiming at the trial calculation result, adding the newly added rule description information into a standard rule base, wherein the rule description information in the standard rule base is used for calculating user attribute data based on order data in the service database.
2. The method of claim 1, wherein the trial calculation based on order data in the shadow library comprises:
according to the newly added rule description information, trial calculation is carried out based on the historical order data in the shadow library, and a first trial calculation result is obtained;
responding to a confirmation instruction aiming at the first trial calculation result, and adding the newly added rule description information into an intermediate rule base;
and responding to target order data entering the shadow library, and performing trial calculation based on the target order data to obtain a second trial calculation result, wherein the target order data is order data meeting the order condition.
3. The method of claim 2, wherein prior to said adding the newly added rule description information to a standard rule base, the method further comprises:
outputting the second trial calculation result;
the adding the newly added rule description information into a standard rule base comprises the following steps:
and responding to a confirmation instruction aiming at the second trial calculation result, and adding the newly added rule description information into the standard rule base.
4. The method of claim 1, wherein performing a trial calculation based on order data in a shadow library, the obtaining the trial calculation result comprising:
searching target order data in the historical order data in the shadow library according to the order condition; and if the target order data is not found in the shadow library, acquiring custom order data, wherein the custom order data is generated according to the order condition construction.
5. The method according to claim 1, wherein the method further comprises:
and saving the trial calculation result in the shadow library.
6. The method of claim 1, wherein prior to said receiving the newly added rule description information, the method further comprises:
responding to an input checking instruction, and checking the rule operator and/or the attribute expression of the order condition based on test order data to obtain a checking result;
the receiving the newly added rule description information comprises the following steps:
and receiving the newly added rule description information in response to a confirmation instruction for the checking result.
7. The method of claim 1, wherein the trial calculation based on order data in the shadow library comprises:
trial calculation is carried out based on target order data in the shadow library, and trial calculation is carried out based on non-target order data in the shadow library;
the target order data is order data meeting the order condition, and the target order data is order data not meeting the order condition.
8. A user attribute data trial-computing verification device of an online platform, comprising:
the receiving module is used for receiving the newly added rule description information, and the rule description information is used for describing rule operators and order conditions corresponding to the rule operators;
the trial calculation module is used for carrying out trial calculation based on order data in a shadow database according to the newly-added rule description information to obtain a trial calculation result, wherein the trial calculation result is attribute data to be obtained by a user applying the newly-added rule description information, and the shadow database is updated along with a service database in real time;
and the updating module is used for responding to a confirmation instruction aiming at the trial calculation result, adding the newly added rule description information into a standard rule base, wherein the rule description information in the standard rule base is used for calculating the user attribute data based on the order data in the service database.
9. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program, when being executed by a processor, performs the steps of the user attribute data trial verification method of an on-line platform according to any one of claims 1 to 7.
10. A computing device comprising a memory and a processor, the memory having stored thereon a computer program executable on the processor, wherein the processor, when executing the computer program, performs the steps of the user attribute data trial verification method of an on-line platform of any one of claims 1 to 7.
CN202310299833.1A 2023-03-20 2023-03-20 User attribute data trial calculation verification method and device of online platform and terminal Pending CN116645136A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310299833.1A CN116645136A (en) 2023-03-20 2023-03-20 User attribute data trial calculation verification method and device of online platform and terminal

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310299833.1A CN116645136A (en) 2023-03-20 2023-03-20 User attribute data trial calculation verification method and device of online platform and terminal

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