Method, apparatus and device for verifying input parameters of featured floor, and storage medium

Abstract

A method, apparatus and device for verifying input parameters of a featured floor, and a storage medium. The method comprises: acquiring each piece of featured floor data placed in each placeable component within a preset historical time period, and converting each piece of featured floor data into input parameter data of a target interface; acquiring a plurality of pieces of user data, and for each piece of user data, replacing a personalized parameter in the input parameter data with the user data to obtain user input parameter data; for each piece of user input parameter data, requesting the target interface to obtain feedback results of the target interface; on the basis of each feedback result, collecting statistics about each piece of abnormal index data, and on the basis of each piece of abnormal index data, determining an abnormal index value; determining a data packet of each feedback result containing an interface feedback data packet, and determining a personalized index value obtained by each data packet performing personalized analysis on each piece of featured floor data; and on the basis of the abnormal index value or each personalized index value, determining a verification result of each piece of featured floor data, and if the verification result is abnormal, giving an alarm.

Description

A method, device, equipment and storage medium for verifying selected floor input parameters

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on November 13, 2023, with application number 202311499131.4 and invention name “A method, device, equipment and storage medium for verifying the parameters of selected floors”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present invention relates to the field of computer technology, and more specifically, to a method, device, equipment and storage medium for verifying selected floor input parameters. Background Art

[0003] With the development of Internet technology, product websites for users will provide product information to users in partitioned manner, such as [70% off], [Today's special sale], etc. The pages embedded with such partition modules contain product information of multiple categories and brands. This mode of embedding partition modules in pages is called the featured floor.

[0004] Selected floors are a crucial component of daily operations, subject to constant adjustments based on sales data. Operational flexibility is high, with high real-time availability and high frequency of use. Operational adjustment strategies include, but are not limited to, adjusting inventory pools, modifying personalized strategies, conducting diversion experiments, and adjusting layouts. Because these strategies are subject to frequent and diverse modifications, it is crucial to ensure that functionality in all scenarios is not impacted. Furthermore, the data output must be highly personalized and closely linked to the user.

[0005] How to verify the input parameters of the selected floors to check whether the system and component configurations are normal and whether the personalized strategy is reasonable is an issue that needs attention.

[0006] Summary of the Invention

[0007] In view of the above problems, the present application is proposed to provide a method, device, equipment and storage medium for verifying the parameters of selected floors, so as to check whether the system and component configurations are normal and verify whether the personalized strategy is reasonable.

[0008] In order to achieve the above objectives, the following specific plans are proposed:

[0009] A method for verifying selected floor input parameters includes:

[0010] Obtaining each selected floor data delivered to each deliverable component within a preset historical period, and converting each selected floor data into input parameter data of the target interface;

[0011] Obtaining multiple user data, and for each user data, replacing the personalized parameters in the input parameter data with the user data to obtain user input parameter data;

[0012] For each user input parameter data, request the target interface to obtain the feedback result of the target interface;

[0013] According to each feedback result, various abnormal indicator data are counted, and the abnormal indicator value is determined based on the various abnormal indicator data;

[0014] Determining each data message including a feedback result of an interface feedback data message, and determining a personalized index value obtained by performing a personalized analysis on each selected floor data in each data message, wherein the interface feedback data message is generated based on an application result obtained by applying user data in the user input data to each selected floor data;

[0015] According to the abnormal index value or each of the personalized index values, the verification result of each of the selected floor data is determined, and an alarm is issued when the verification result is abnormal.

[0016] Optionally, after converting the selected floor data into input parameter data of the target interface, the method further includes:

[0017] The input parameter data is stored in the database through the target interface.

[0018] Optionally, the abnormal indicator data is collected based on each feedback result, including:

[0019] Counting the number of disaster recovery identifiers in all data packets in each feedback result, dividing the number of disaster recovery identifiers by the total number of requests to the target interface to obtain a disaster recovery rate;

[0020] Count the number of interface return errors in each feedback result, and divide the number of interface return errors by the total number of requests to the target interface to obtain the error rate;

[0021] The number of empty results in each feedback result is counted, and the number of empty results is divided by the total number of requests to the target interface to obtain the empty report rate.

[0022] Optionally, each data packet includes multiple product brands and multiple product categories;

[0023] The determining of the personalized index value obtained by performing personalized analysis on each selected floor data for each data message includes:

[0024] For each data message, the number of occurrences of each product brand on the selected floor corresponding to each selected floor data is counted to determine the number of repetitions of the product brand on the selected floor;

[0025] For each data message, count the number of repetitions of each product brand in all the selected floors to determine the total number of repetitions of each product brand in all the selected floors;

[0026] For each data message, counting the frequency of occurrence of each commodity category in each selected floor, and averaging the frequency of occurrence of the commodity category in each selected floor to obtain an average frequency of occurrence;

[0027] For each data message, average the average occurrence frequencies of various commodity categories in each of the selected floors to obtain the total average frequency of the categories;

[0028] A personalized index value is determined based on the total number of repetitions of the brand and the total average frequency of the category.

[0029] Optionally, determining the verification result of each selected floor data according to the abnormality index value or each personalized index value includes:

[0030] When the abnormality index value is higher than the abnormality index preset threshold value, determining that the verification result of each selected floor data is a verification abnormality;

[0031] When at least one of the personalized index values ​​is lower than a preset personalized index threshold, it is determined that the verification result of the selected floor data is abnormal.

[0032] A device for verifying selected floor parameters, comprising:

[0033] The selected floor data input unit is used to obtain each selected floor data delivered to each deliverable component within a preset historical period, and convert the each selected floor data into input parameter data of the target interface;

[0034] A parameter replacement unit is used to obtain a plurality of user data and, for each user data, replace the personalized parameters in the input parameter data with the user data to obtain the user input parameter data;

[0035] An interface request feedback unit, configured to request the target interface for each user input parameter data to obtain a feedback result of the target interface;

[0036] An abnormality statistics unit is used to count various abnormality indicator data according to various feedback results, and determine the abnormality indicator value based on the various abnormality indicator data;

[0037] a personalized statistical unit, configured to determine each data message including a feedback result of an interface feedback data message, and determine a personalized index value obtained by performing personalized analysis on each selected floor data in each data message, wherein the interface feedback data message is generated based on an application result obtained by applying user data in the user input data to each selected floor data;

[0038] An alarm unit is used to determine the verification results of each selected floor data according to the abnormal index value or each personalized index value, and to issue an alarm when the verification result is abnormal.

[0039] Optionally, the device further includes:

[0040] The warehousing unit is used to convert the selected floor data into input parameter data of the target interface and then store the input parameter data into the warehousing through the target interface.

[0041] Optionally, the abnormality statistics unit includes:

[0042] A disaster recovery rate statistics unit is used to count the number of disaster recovery identifiers in all data packets in each feedback result, and divide the number of disaster recovery identifiers by the total number of requests to the target interface to obtain a disaster recovery rate;

[0043] an error rate statistics unit, configured to count the number of interface return errors in each feedback result, and divide the number of interface return errors by the total number of requests to the target interface to obtain an error rate;

[0044] The empty report rate statistics unit is used to count the number of empty results in each feedback result, divide the number of empty results by the total number of requests to the target interface to obtain the empty report rate, and determine the abnormal indicator value based on the abnormal indicator data.

[0045] Optionally, each data packet includes multiple product brands and multiple product categories;

[0046] The personalized statistical unit includes:

[0047] The first personalized statistical sub-unit is used to determine the number of repetitions of each product brand on each selected floor by counting the number of occurrences of each product brand on each selected floor data for each data message;

[0048] The second personalized statistical sub-unit is used to count the number of repetitions of each commodity brand in all the selected floors for each data message, and determine the total number of repetitions of various commodity brands in all the selected floors;

[0049] a third personalized statistical subunit, configured to count the occurrence frequency of each commodity category on each selected floor for each data message, and average the occurrence frequencies of the commodity category on each selected floor to obtain an average occurrence frequency;

[0050] a fourth personalized statistical subunit, configured to average the average occurrence frequencies of various commodity categories in each of the selected floors for each data message to obtain an overall average frequency of the categories;

[0051] The fifth personalized statistical subunit is used to determine a personalized index value based on the total number of repetitions of the brand and the total average frequency of the category.

[0052] Optionally, the alarm unit includes:

[0053] A first alarm subunit is configured to determine that the verification result of each selected floor data is a verification abnormality and issue an alarm when the abnormality index value is higher than a preset abnormality index threshold;

[0054] The second alarm subunit is used to determine that the verification result of each selected floor data is abnormal and issue an alarm when at least one personalized indicator value among each personalized indicator value is lower than a preset personalized indicator threshold.

[0055] A verification device for selecting floor input parameters, comprising a memory and a processor;

[0056] The memory is used to store programs;

[0057] The processor is used to execute the program to implement the various steps of the verification method for the selected floor input as described above.

[0058] A storage medium stores a computer program thereon, which, when executed by a processor, implements the various steps of the method for verifying the selected floor input parameters as described above.

[0059] By means of the above technical solution, the present application obtains each selected floor data delivered to each deliverable component within a preset historical period, converts the each selected floor data into input parameter data of a target interface, obtains a plurality of user data, and for each user data, replaces the personalized parameters in the input parameter data with the user data to obtain user input parameter data, requests the target interface for each user input parameter data to obtain a feedback result of the target interface, counts each abnormal indicator data according to each feedback result, and determines an abnormal indicator value based on the each abnormal indicator data, determines each data message containing the feedback result of the interface feedback data message, and determines a personalized indicator value obtained by personalized analysis of the each selected floor data for each data message, the interface feedback data message is an application result obtained by applying the user data in the user input parameter data to the each selected floor data, and is generated based on the application result, determines a verification result of the each selected floor data according to the abnormal indicator value or each personalized indicator value, and issues an alarm when the verification result is abnormal. It can be seen from this that by counting the data of various abnormal indicators, it is possible to evaluate from the dimension of the system, and by replacing user data with parameter data, it is possible to evaluate from the dimension of personalization to determine whether the personalized strategy composed of the current selected floors is reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present application. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0061] FIG1 is a schematic diagram of a process for implementing parameter verification for selected floors according to an embodiment of the present application;

[0062] FIG2 is a schematic diagram of a structure of a device for implementing parameter verification of selected floors provided in an embodiment of the present application;

[0063] FIG3 is a schematic structural diagram of a device for implementing parameter verification of selected floors provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0065] The present application solution can be implemented based on a terminal with data processing capabilities, which can be a computer, server, cloud, etc.

[0066] Next, in conjunction with FIG1 , the verification method for the selected floor input parameter of the present application may include the following steps:

[0067] Step S110: Acquire each selected floor data delivered to each deliverable component within a preset historical period, and convert each selected floor data into input parameter data of a target interface.

[0068] The placeable component can represent a slot for placement on a selected floor. One placeable component represents one slot, and each selected floor can be placed on one placeable component. Selected floor data can come from the selected floor system. The target interface can be the itemFloor interface, which can be used to feedback the results of the selected floor analysis.

[0069] It is understandable that in the past historical period (such as the past 12 hours), there may be selected floor requests from the selected floor system that are delivered to the deliverable components. At this time, it is necessary to count whether these selected floors are delivered normally and whether the personalized strategy is reasonable. Then, the data of each selected floor can be obtained for analysis.

[0070] For example, you can create a scheduled task to periodically pull all selected floor data that has been delivered to deliverable components in the past 12 hours, and convert all selected floor data into input parameter data for the itemFloor interface.

[0071] Step S120: Acquire several pieces of user data, and for each piece of user data, replace the personalized parameters in the input parameter data with the user data to obtain the user input parameter data.

[0072] Specifically, each user data may include user device information and user ID information.

[0073] The input data may include personalized parameters.

[0074] It is understandable that each user data can represent each independent personalized data. In order to verify the personalization effect, it is necessary to replace the user data with the personalized parameters in the parameter data and enrich the user information, so as to play a role in complete verification.

[0075] Step S130: Request the target interface for each user input parameter data to obtain the feedback result of the target interface.

[0076] It is understandable that for multiple user input data, multiple target interfaces need to be requested. For example, for 100 user input data, 100 interfaces need to be requested to apply the user data in each user input data to each selected floor data for analysis to obtain analysis results.

[0077] If the feedback result of the target interface is normal, the feedback result may be a data message, which is also the analysis result. If the feedback result of the target interface is abnormal, the feedback result is interface feedback status information.

[0078] Step S140: Count various abnormal indicator data according to various feedback results, and determine abnormal indicator values ​​based on the various abnormal indicator data.

[0079] Specifically, various abnormal indicator data may include disaster recovery rate, error rate, empty return rate, and number failure ratio.

[0080] It can be understood that the abnormal index value can represent the numerical value used to measure various abnormal index data. The larger the abnormal index value, the more obvious the abnormal state of each selected floor data. The smaller the abnormal index value, the less obvious the abnormal state of each selected floor data.

[0081] Step S150: Determine each data message containing the feedback result of the interface feedback data message, and determine the personalized index value obtained by performing personalized analysis on each selected floor data in each data message.

[0082] Specifically, the interface feedback data message may be generated based on the application result obtained by the target interface applying the user data in the user input data to the data of each selected floor. The data message in the feedback result may include, but is not limited to, schedule information, schedule quantity, information on various product brands within the schedule, information on various product categories within the schedule, product quantity, and disaster recovery identification.

[0083] It is understood that the personalization index value can represent a numerical value used to measure the overall richness and relevance of each selected floor data. A higher personalization index value can indicate a more reliable personalization strategy for each selected floor data, while a lower personalization index value can indicate a less practical personalization strategy for each selected floor data.

[0084] Step S160: Determine the verification result of each selected floor data according to the abnormal index value or each personalized index value, and issue an alarm when the verification result is abnormal.

[0085] Specifically, the warning may be issued by sending an email notification to the responsible person.

[0086] It is understandable that by automatically setting alarms, we can get rid of the time-consuming and labor-intensive manual monitoring.

[0087] The method for verifying selected floor input parameters provided in this embodiment obtains each selected floor data delivered to each deliverable component within a preset historical period, converts each selected floor data into input parameter data of a target interface, obtains a plurality of user data, and replaces personalized parameters in the input parameter data with the user data for each user data to obtain user input parameter data. For each user input parameter data, a request is made to the target interface to obtain a feedback result of the target interface. Based on each feedback result, various abnormal indicator data are counted, and abnormal indicator values ​​are determined based on the various abnormal indicator data. Each data packet containing the feedback result of an interface feedback data packet is determined, and a personalized indicator value obtained by performing personalized analysis on each selected floor data in each data packet is determined. The interface feedback data packet is an application result obtained by applying the user data in the user input parameter data to the each selected floor data, and is generated based on the application result. The verification result of each selected floor data is determined based on the abnormal indicator value or each personalized indicator value, and an alarm is issued when the verification result is abnormal. It can be seen from this that by counting the data of various abnormal indicators, it is possible to evaluate from the dimension of the system, and by replacing user data with parameter data, it is possible to evaluate from the dimension of personalization to determine whether the personalized strategy composed of the current selected floors is reasonable.

[0088] Taking into account that input parameter data is needed when analyzing each selected floor data through each user data, based on this, in some embodiments of the present application, after converting each selected floor data into input parameter data of the target interface mentioned in the above embodiments, the input parameter data can be stored in the database through the target interface so that the input parameter data can be used when the user input parameter data requests the target interface.

[0089] In some embodiments of the present application, the process of collecting statistics of various abnormal indicator data based on various feedback results mentioned in the above embodiments is introduced. This process may include:

[0090] S1. Count the number of disaster recovery identifiers in all data packets in each feedback result, divide the number of disaster recovery identifiers by the total number of requests to the target interface, and obtain the disaster recovery rate.

[0091] Specifically, the disaster recovery rate can be negatively correlated with the anomaly index value. A higher disaster recovery rate and a lower anomaly index value indicate that the anomaly status of the selected floor data is less obvious. A lower disaster recovery rate and a higher anomaly index value indicate that the anomaly status of the selected floor data is more obvious.

[0092] For example, if 100 requests are sent to the target interface and the number of disaster recovery identifiers in all data packets is 5, it can be seen that disaster recovery occurred 5 times, and the disaster recovery rate is 5%.

[0093] S2. Count the number of interface return errors in each feedback result, divide the number of interface return errors by the total number of requests to the target interface to obtain the error rate.

[0094] It is understandable that not all feedback results contain data packets. For abnormal feedback results, the interface feedback status information may be a return error. Therefore, the number of interface return errors in each feedback result can be counted, and the number of interface return errors can be divided by the total number of times the target interface is requested to obtain the error rate.

[0095] Specifically, the error rate can be positively correlated with the anomaly index value. A higher error rate and a larger anomaly index value indicate a more pronounced anomaly in the selected floor data. A lower error rate and a smaller anomaly index value indicate a less pronounced anomaly in the selected floor data.

[0096] S3. Count the number of empty results in each feedback result, divide the number of empty results by the total number of requests to the target interface, and obtain the empty report rate.

[0097] It is understandable that not all feedback results contain data packets. For abnormal feedback results, the interface feedback status information may be empty. Therefore, the number of empty results in each feedback result can be counted, and the number of empty results can be divided by the total number of requests to the target interface to obtain the empty rate.

[0098] Specifically, the empty-listing rate can be positively correlated with the abnormality index value. A higher empty-listing rate and a larger abnormality index value indicate a more pronounced abnormality in the selected floor data. A lower empty-listing rate and a smaller abnormality index value indicate a less pronounced abnormality in the selected floor data.

[0099] The verification method for selected floor input provided in this embodiment calculates each disaster recovery rate, error rate and empty return rate based on each feedback result, performs abnormal rule verification on each selected floor, and can perform verification more accurately from multiple dimensions of the system.

[0100] In some embodiments of the present application, the process of collecting statistics of various abnormal indicator data based on various feedback results mentioned in the above embodiments is introduced. This process may include:

[0101] S1. For each data message, the number of occurrences of each product brand in the selected floor corresponding to each selected floor data is counted to determine the number of repetitions of the product brand in the selected floor.

[0102] It's understandable that each data packet returned by the target interface represents the personalized application of each user's data to all selected floors. Each product brand may appear once or multiple times on the same selected floor. Therefore, the number of occurrences of each product brand on each selected floor data item can be counted to determine the number of repetitions of that product brand on that selected floor.

[0103] S2. For each data message, count the number of repetitions of each product brand in all selected floors, and determine the total number of repetitions of various product brands in all selected floors.

[0104] Specifically, after counting the number of repetitions of each product brand on each selected floor, all repetitions of a single product brand on all selected floors may be accumulated to obtain the number of repetitions of the product brand on all selected floors.

[0105] Furthermore, after counting the number of repetitions of each product brand in all selected floors, all repetitions of all product brands on all selected floors may be accumulated to obtain the total number of repetitions of various product brands in all selected floors.

[0106] It is understood that the total number of brand repetitions can represent the richness of brands on each selected floor. A larger total number of brand repetitions can indicate a higher concentration of brands on each selected floor, while a smaller total number of brand repetitions can indicate a more dispersed and richer brand on each selected floor.

[0107] S3. For each data message, count the occurrence frequency of each commodity category in each selected floor, and average the occurrence frequency of the commodity category in each selected floor to obtain an average occurrence frequency.

[0108] It is understandable that there may be multiple product brands in each selected floor, some of which may belong to the same product category. In this case, the frequency of occurrence of each product category in each selected floor can be counted to analyze the richness of this product category in the selected floor.

[0109] Furthermore, after determining the occurrence frequency of a specific product category in each selected floor, the occurrence frequencies of the specific product category on each selected floor may be averaged to obtain the average occurrence frequency of the specific product category.

[0110] S4. For each data message, average the average occurrence frequencies of various commodity categories in each selected floor to obtain the total average frequency of the category.

[0111] Specifically, after determining the average occurrence frequency of each product category for all selected floors, the average occurrence frequencies of each product category for all selected floors may be averaged to obtain the total average frequency of each product category for all selected floors.

[0112] It can be understood that the category average frequency can represent the richness of the category on each selected floor. A larger category average frequency indicates a more concentrated category on each selected floor, while a smaller category average frequency indicates a more dispersed and richer brand on each selected floor.

[0113] S5. Determine the personalized index value based on the total number of brand repetitions and the total average frequency of the category.

[0114] Specifically, the total number of brand repetitions can be negatively correlated with the personalization index value, and the total average frequency of a category can also be negatively correlated with the personalization index value. Regarding the brand personalization dimension, a greater total number of brand repetitions is associated with a smaller personalization index value, and a smaller total number of brand repetitions is associated with a larger personalization index value. Regarding the category personalization dimension, a greater total average frequency of a category is associated with a smaller personalization index value, and a smaller total average frequency of a category is associated with a larger personalization index value.

[0115] The verification method for the selected floor input provided in this embodiment analyzes and calculates the total average frequency of various commodity categories for all selected floors based on the data message of the feedback results, and calculates the total number of brand repetitions of various commodity brands in all selected floors, and performs personalized effect rule verification on each selected floor, which can perform personalized effect verification more finely.

[0116] In some embodiments of the present application, the process of determining the verification result of each selected floor data according to the abnormality index value or each personalized index value mentioned in the above embodiment is introduced. This process may include:

[0117] S1. When the abnormality indicator value is higher than the abnormality indicator preset threshold, the verification result of each selected floor data is determined to be a verification abnormality.

[0118] Specifically, the abnormal indicator preset threshold value may represent an abnormality determination standard value for abnormal rule verification, and the abnormal indicator preset threshold value may be customized.

[0119] S2. When at least one personalized indicator value among the personalized indicator values ​​is lower than a preset personalized indicator threshold, the verification result of each selected floor data is determined to be a verification abnormality.

[0120] Specifically, the personalized indicator preset threshold value may represent a personalized standard value for verification of the personalized effect rule, and the personalized indicator preset threshold value may be customized.

[0121] The following describes the device for implementing the selected floor entry parameter verification provided in an embodiment of the present application. The device for implementing the selected floor entry parameter verification described below and the verification method for implementing the selected floor entry described above can be referenced to each other.

[0122] See Figure 2, which is a schematic diagram of the structure of a device for implementing selected floor input parameter verification disclosed in an embodiment of the present application.

[0123] As shown in FIG2 , the apparatus may include:

[0124] The selected floor data input unit 11 is used to obtain each selected floor data delivered to each deliverable component within a preset historical period, and convert the each selected floor data into input parameter data of the target interface;

[0125] The parameter replacement unit 12 is used to obtain a plurality of user data and, for each user data, replace the personalized parameters in the input parameter data with the user data to obtain the user input parameter data;

[0126] The interface request feedback unit 13 is used to request the target interface for each user input parameter data to obtain the feedback result of the target interface;

[0127] The abnormality statistics unit 14 is used to count various abnormality indicator data according to various feedback results, and determine the abnormality indicator value based on the various abnormality indicator data;

[0128] The personalized statistical unit 15 is configured to determine each data packet containing a feedback result of an interface feedback data packet, and determine a personalized index value obtained by performing personalized analysis on each selected floor data for each data packet, wherein the interface feedback data packet is generated based on an application result obtained by applying user data in the user input data to each selected floor data;

[0129] The alarm unit 16 is used to determine the verification result of each selected floor data according to the abnormal index value or each personalized index value, and to issue an alarm when the verification result is abnormal.

[0130] Optionally, the device further includes:

[0131] The warehousing unit is used to convert the selected floor data into input parameter data of the target interface and then store the input parameter data into the warehousing through the target interface.

[0132] Optionally, the abnormality statistics unit includes:

[0133] A disaster recovery rate statistics unit is used to count the number of disaster recovery identifiers in all data packets in each feedback result, and divide the number of disaster recovery identifiers by the total number of requests to the target interface to obtain a disaster recovery rate;

[0134] an error rate statistics unit, configured to count the number of interface return errors in each feedback result, and divide the number of interface return errors by the total number of requests to the target interface to obtain an error rate;

[0135] The empty report rate statistics unit is used to count the number of empty results in each feedback result, divide the number of empty results by the total number of requests to the target interface to obtain the empty report rate, and determine the abnormal indicator value based on the abnormal indicator data.

[0136] Optionally, each data packet includes multiple product brands and multiple product categories;

[0137] The personalized statistical unit includes:

[0138] The first personalized statistical sub-unit is used to determine the number of repetitions of each product brand on each selected floor by counting the number of occurrences of each product brand on each selected floor data for each data message;

[0139] The second personalized statistical sub-unit is used to count the number of repetitions of each commodity brand in all the selected floors for each data message, and determine the total number of repetitions of various commodity brands in all the selected floors;

[0140] a third personalized statistical subunit, configured to count the occurrence frequency of each commodity category on each selected floor for each data message, and average the occurrence frequencies of the commodity category on each selected floor to obtain an average occurrence frequency;

[0141] a fourth personalized statistical subunit, configured to average the average occurrence frequencies of various commodity categories in each of the selected floors for each data message to obtain an overall average frequency of the categories;

[0142] The fifth personalized statistical subunit is used to determine a personalized index value based on the total number of repetitions of the brand and the total average frequency of the category.

[0143] Optionally, the alarm unit includes:

[0144] A first alarm subunit is configured to determine that the verification result of each selected floor data is a verification abnormality and issue an alarm when the abnormality index value is higher than a preset abnormality index threshold;

[0145] The second alarm subunit is used to determine that the verification result of each selected floor data is abnormal and issue an alarm when at least one personalized indicator value among each personalized indicator value is lower than a preset personalized indicator threshold.

[0146] The apparatus for checking selected floor entry parameters provided in the embodiment of the present application can be applied to devices for checking selected floor entry parameters, such as terminals: mobile phones, computers, etc. Optionally, FIG3 shows a hardware structure block diagram of the apparatus for checking selected floor entry parameters. Referring to FIG3 , the hardware structure of the apparatus for checking selected floor entry parameters may include: at least one processor 1, at least one communication interface 2, at least one memory 3, and at least one communication bus 4;

[0147] In the embodiment of the present application, the number of the processor 1, the communication interface 2, the memory 3, and the communication bus 4 is at least one, and the processor 1, the communication interface 2, and the memory 3 communicate with each other through the communication bus 4;

[0148] The processor 1 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention;

[0149] The memory 3 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory;

[0150] The memory stores a program, and the processor can call the program stored in the memory, wherein the program is used to:

[0151] Obtaining each selected floor data delivered to each deliverable component within a preset historical period, and converting each selected floor data into input parameter data of the target interface;

[0152] Obtaining multiple user data, and for each user data, replacing the personalized parameters in the input parameter data with the user data to obtain user input parameter data;

[0153] For each user input parameter data, request the target interface to obtain the feedback result of the target interface;

[0154] According to each feedback result, various abnormal indicator data are counted, and the abnormal indicator value is determined based on the various abnormal indicator data;

[0155] Determining each data message including a feedback result of an interface feedback data message, and determining a personalized index value obtained by performing a personalized analysis on each selected floor data in each data message, wherein the interface feedback data message is generated based on an application result obtained by applying user data in the user input data to each selected floor data;

[0156] Determine the verification results of each selected floor data according to the abnormal index value or each personalized index value, and issue an alarm when the verification result is abnormal

[0157] Optionally, the detailed functions and extended functions of the program may refer to the above description.

[0158] The present application also provides a storage medium that can store a program suitable for execution by a processor, wherein the program is used to:

[0159] Obtaining each selected floor data delivered to each deliverable component within a preset historical period, and converting each selected floor data into input parameter data of the target interface;

[0160] Obtaining multiple user data, and for each user data, replacing the personalized parameters in the input parameter data with the user data to obtain user input parameter data;

[0161] For each user input parameter data, request the target interface to obtain the feedback result of the target interface;

[0162] According to each feedback result, various abnormal indicator data are counted, and the abnormal indicator value is determined based on the various abnormal indicator data;

[0163] Determining each data message including a feedback result of an interface feedback data message, and determining a personalized index value obtained by performing a personalized analysis on each selected floor data in each data message, wherein the interface feedback data message is generated based on an application result obtained by applying user data in the user input data to each selected floor data;

[0164] Determine the verification results of each selected floor data according to the abnormal index value or each personalized index value, and issue an alarm when the verification result is abnormal

[0165] Optionally, the detailed functions and extended functions of the program may refer to the above description.

[0166] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0167] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referenced to each other.

[0168] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for verifying the input parameters of a selected floor, wherein the selected floor is a mode in which a partition module in a commodity website is embedded in a page. It is characterized in that The method includes: Acquire each selected floor data placed on each placeable component within a preset historical period, and convert each selected floor data into input parameter data of a target interface; Acquire a plurality of user data, and for each user data, replace the personalized parameters in the input parameter data with the user data to obtain the user input parameter data; For each user input parameter data, request the target interface to obtain the feedback result of the target interface; According to each feedback result, various abnormal indicator data are counted, and the abnormal indicator value is determined based on the various abnormal indicator data; Determine each data message including the feedback result of the interface feedback data message, and determine that each data message performs personalized analysis on the selected floor data, each data message includes multiple commodity brands and multiple commodity categories, and determines the personalized index value based on the total number of brand repetitions and the total average frequency of the category, and the interface feedback data message is an application result obtained by applying the user data in the user input data to the selected floor data, and is generated based on the application result; Determine the verification result of each selected floor data according to the abnormal index value or each personalized index value, and issue an alarm when the verification result is abnormal; The personalized index value is determined based on the total number of brand repetitions and the total average frequency of the category, including: For each data message, the number of occurrences of each commodity brand in the selected floor corresponding to each selected floor data is counted to determine the number of repetitions of the commodity brand in the selected floor; For each data message, count the number of repetitions of each commodity brand in all the selected floors to determine the total number of repetitions of various commodity brands in all the selected floors; For each data message, the occurrence frequency of each commodity category in each selected floor is counted, and the occurrence frequency of the commodity category in each selected floor is averaged to obtain an average occurrence frequency; For each data message, average the average occurrence frequencies of various commodity categories in each of the selected floors to obtain a total average frequency of the category; A personalized index value is determined based on the total number of repetitions of the brand and the total average frequency of the category.

2. The method according to claim 1, It is characterized in that After converting each selected floor data into input parameter data of the target interface, it also includes: The input parameter data is stored in the database through the target interface.

3. The method according to claim 1, It is characterized in that According to each feedback result, various abnormal indicator data are counted, including: Counting the number of disaster recovery identifiers in all data packets in each feedback result, dividing the number of disaster recovery identifiers by the total number of requests to the target interface, to obtain a disaster recovery rate; Counting the number of interface return errors in each feedback result, dividing the number of interface return errors by the total number of requests to the target interface, to obtain an error rate; The number of empty results in each feedback result is counted, and the number of empty results is divided by the total number of requests to the target interface to obtain the empty report rate.

4. The method according to any one of claims 1 to 3, It is characterized in that Determining the verification result of each selected floor data according to the abnormal index value or each personalized index value includes: When the abnormal index value is higher than the abnormal index preset threshold value, determining that the verification result of each selected floor data is a verification abnormality; When at least one of the personalized index values ​​is lower than a preset personalized index threshold, it is determined that the verification result of each selected floor data is abnormal.

5. A verification device for selected floor input, wherein the selected floor is a mode in which a partition module in a commodity website is embedded in a page. It is characterized in that The device includes: A selected floor data input parameter unit, used to obtain each selected floor data placed on each placeable component within a preset historical period, and convert the each selected floor data into input parameter data of a target interface; A parameter replacement unit, used to obtain a plurality of user data, and for each user data, replace the personalized parameters in the input parameter data with the user data to obtain the user input parameter data; An interface request feedback unit, used for requesting the target interface for each user input parameter data to obtain a feedback result of the target interface; The abnormal statistics unit is used to count various abnormal indicator data according to various feedback results, and based on The abnormal indicator data are used to determine the abnormal indicator value; A personalized statistical unit, used to determine each data message including the feedback result of the interface feedback data message, and determine that each data message performs personalized analysis on the selected floor data, each data message includes multiple commodity brands and multiple commodity categories, and the personalized index value is determined based on the total number of brand repetitions and the total average frequency of the category, and the interface feedback data message is an application result obtained by applying the user data in the user input data to the selected floor data, and is generated based on the application result; An alarm unit, used to determine the verification result of each selected floor data according to the abnormal index value or each personalized index value, and to issue an alarm when the verification result is abnormal; The personalized statistics unit comprises: The first personalized statistical subunit is used to determine the number of repetitions of each commodity brand in the selected floor by counting the number of occurrences of each commodity brand in the selected floor corresponding to each selected floor data for each data message; The second personalized statistical subunit is used to count the number of repetitions of each commodity brand in all the selected floors for each data message, and determine the total number of repetitions of various commodity brands in all the selected floors; A third personalized statistical subunit is used to count the occurrence frequency of each commodity category in each selected floor for each data message, and average the occurrence frequency of the commodity category in each selected floor to obtain an average occurrence frequency; A fourth personalized statistical subunit is used to average the average occurrence frequency of various commodity categories in each of the selected floors for each data message to obtain a total average frequency of the category; The fifth personalized statistical subunit is used to determine the personalized index value based on the total number of repetitions of the brand and the total average frequency of the category.

6. The device according to claim 5, It is characterized in that Also includes: The warehousing unit is used to store the input parameter data of the target interface after converting the data of each selected floor into the input parameter data of the target interface through the target interface.

7. The device according to claim 5, It is characterized in that The abnormal statistics unit comprises: The disaster recovery rate statistics unit is used to count the number of disaster recovery identifiers in all data packets in each feedback result. The number of disaster recovery identifiers is divided by the total number of requests to the target interface to obtain a disaster recovery rate; An error rate statistics unit, used to count the number of interface return errors in each feedback result, and divide the number of interface return errors by the total number of requests to the target interface to obtain an error rate; The empty report rate statistics unit is used to count the number of empty results in each feedback result, divide the number of empty results by the total number of requests to the target interface to obtain the empty report rate, and determine the abnormal indicator value based on the abnormal indicator data.

8. A calibration device for selecting floor input parameters, It is characterized in that including memory and processor; The memory is used to store programs; The processor is used to execute the program to implement the various steps of the method for verifying the selected floor input parameters as claimed in any one of claims 1-4.

9. A storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, each step of the method for verifying the selected floor input parameters as claimed in any one of claims 1 to 4 is implemented.

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