Transaction association index monitoring method and device, equipment, storage medium and product

Abstract

The invention discloses a transaction association index monitoring method, device and equipment, a storage medium and a product, which can be applied to the field of financial science and technology. The method comprises the following steps: acquiring a transaction influence result corresponding to at least one transaction association monitoring index in a preset historical time period; determining a target monitoring index in the current time period according to the transaction influence result of each transaction associated monitoring index; determining a target monitoring strategy of the target monitoring index in the current time period; and performing index monitoring on the target monitoring index based on the target monitoring strategy. According to the technical scheme, the transaction influence result corresponding to the transaction associated monitoring index is obtained, the target monitoring index and the corresponding target monitoring strategy are determined, and index monitoring is performed on the target monitoring index, so that the transaction monitoring efficiency is improved, the influence of the abnormal transaction associated monitoring index on the transaction environment is reduced, and the transaction monitoring efficiency is improved. And the transaction stability is ensured.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to transaction-related indicator monitoring methods, devices, equipment, storage media and products. Background Art

[0002] Transaction monitoring is to monitor and collect performance information, abnormal monitoring indicators and performance information during the transaction loading process by responding to information collection operation requests, and then analyze various characteristics under the transaction environment. Ensure that during the transaction process, when abnormal monitoring indicators and / or error information are generated, the root cause of the problem can be quickly located and corresponding measures can be taken.

[0003] The existing transaction monitoring methods can only monitor and report the error information and page loading performance information generated on the pages run by users, but for many specific business scenarios, it is necessary to capture and report abnormal monitoring indicators. Therefore, when faced with complex and special scenarios, the existing transaction monitoring methods are difficult to quickly locate abnormal monitoring indicators that appear on the front end, and usually require human intervention, which greatly affects the efficiency of transaction monitoring and the stability of the transaction environment.

[0004] Therefore, how to capture and report abnormal monitoring indicators in the trading environment to improve the efficiency of transaction monitoring, reduce the impact of abnormal transaction-related monitoring indicators on the trading environment, and ensure the stability of transactions has become an urgent problem that technical personnel need to solve. Summary of the invention

[0005] The present invention provides a transaction-related indicator monitoring method, device, equipment, storage medium and product to improve the efficiency of transaction monitoring, reduce the impact of abnormal transaction-related monitoring indicators on the transaction environment, and ensure the security and stability of transactions.

[0006] According to one aspect of the present invention, a transaction-related indicator monitoring method is provided, comprising:

[0007] Obtaining transaction impact results corresponding to at least one transaction-related monitoring indicator in a preset historical time period;

[0008] Determine the target monitoring indicator for the current time period according to the transaction impact results of each of the transaction-related monitoring indicators;

[0009] Determine a target monitoring strategy for the target monitoring indicator in the current time period;

[0010] Based on the target monitoring strategy, the target monitoring indicator is monitored.

[0011] According to another aspect of the present invention, there is provided a transaction-related indicator monitoring device, comprising:

[0012] A transaction impact result acquisition module, used to acquire transaction impact results corresponding to at least one transaction-related monitoring indicator in a preset historical time period;

[0013] A target monitoring indicator determination module, used to determine the target monitoring indicator in the current time period according to the transaction impact results of each of the transaction-related monitoring indicators;

[0014] A target monitoring strategy determination module, used to determine the target monitoring strategy of the target monitoring indicator in the current time period;

[0015] The indicator monitoring module is used to monitor the target monitoring indicator based on the target monitoring strategy.

[0016] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the transaction-related indicator monitoring method described in any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the transaction correlation indicator monitoring method described in any embodiment of the present invention when executed.

[0021] According to another aspect of the present invention, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, the transaction correlation indicator monitoring method described in any embodiment of the present invention is implemented.

[0022] The technical solution of the embodiment of the present invention is to obtain the transaction impact results corresponding to at least one transaction-related monitoring indicator in a preset historical time period; determine the target monitoring indicator in the current time period according to the transaction impact results of each transaction-related monitoring indicator; determine the target monitoring strategy for the target monitoring indicator in the current time period; and monitor the target monitoring indicator based on the target monitoring strategy. This technical solution can obtain the transaction impact results corresponding to the transaction-related monitoring indicators in the historical event period, and determine the target monitoring indicators and the corresponding target monitoring strategy in the current time period. It can adjust the monitoring strategy according to the transaction impact results, improve the efficiency of transaction monitoring, and also reduce the impact of abnormal transaction-related monitoring indicators on the transaction environment; further, it can also implement indicator monitoring of the target monitoring indicator through the target monitoring strategy, ensure the stability of the transaction, and further improve the user experience.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 is a flow chart of a transaction-related indicator monitoring method provided according to Embodiment 1 of the present invention;

[0026] Figure 2 is a flow chart of a transaction-related indicator monitoring method provided according to Embodiment 2 of the present invention;

[0027] Figure 3 This is a schematic diagram of the structure of a transaction-related indicator monitoring device provided according to Embodiment 3 of the present invention;

[0028] Figure 4 It is a structural schematic diagram of an electronic device for implementing the transaction-related indicator monitoring method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] Figure 1 A flowchart of a transaction correlation indicator monitoring method is provided for the first embodiment of the present invention. This embodiment is applicable to situations where it is necessary to locate and monitor abnormal transaction correlation monitoring indicators during a transaction. The method can be performed by a transaction correlation indicator monitoring device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0033] S110: Obtain transaction impact results corresponding to at least one transaction-related monitoring indicator in a preset historical time period.

[0034] Among them, the transaction-related monitoring indicators can be indicator data used to evaluate the status of transaction activities, and the indicator data can include device peripheral module data, front-end page performance data, abnormal error data, and user behavior data. Among them, device peripheral module data can include status information and version information of peripheral modules such as card readers, password keyboards, receipt printers, second-generation ID card readers, and fingerprint scanners; front-end page performance data can include data such as white screen time, interactive time, resource loading time, and rendering time; abnormal error data can include promise errors (asynchronous operation exceptions or failures) and JavaScript errors (code execution exceptions or errors) and other error data; user behavior data can include page views, page dwell time, user clicks, and transaction time.

[0035] Among them, the transaction impact result may refer to the execution status of the transaction. Specifically, the codeless point-burying technology can be used to collect the transaction execution status corresponding to different transaction-related monitoring indicator data in a preset time period, such as once every ten minutes, ten times a day, or once at ten o'clock every day. Exemplarily, at ten o'clock every day, the transaction execution status corresponding to each indicator data in the user behavior data is obtained, and this embodiment does not make specific restrictions on this.

[0036] S120: Determine the target monitoring indicator in the current time period according to the transaction impact results of each transaction-related monitoring indicator.

[0037] Among them, the target monitoring indicator can be the transaction-related monitoring indicator data that causes the transaction process to fail to execute normally, and specifically can be the transaction-related monitoring indicator data that causes transaction delays or transaction failures. Exemplarily, continuing the above example, the target monitoring indicator in the current time period can be determined based on the transaction impact results corresponding to each indicator data in the user behavior data collected at 10 o'clock every day. If the transaction execution status determined based on the transaction time is transaction delay, the transaction time can be used as the target monitoring indicator.

[0038] Optionally, the transaction impact results include transaction success, a first blocking state, and a second blocking state; accordingly, according to the transaction impact results of each transaction-related monitoring indicator, the target monitoring indicator for the current time period is determined, including: determining the first number of occurrences of the first blocking state as a transaction impact result of each transaction-related monitoring indicator in the historical time period and the second number of occurrences of the second blocking state as a transaction impact result; determining the target monitoring indicator for the current time period according to the first number of occurrences and the second number of occurrences corresponding to each transaction-related monitoring indicator.

[0039] The first blocking state may refer to a serious blocking during the transaction, such as a transaction failure or other transaction-affecting result. The second blocking state may refer to a slight blocking during the transaction, such as a transaction resource loading time being too long or other transaction-affecting result.

[0040] Specifically, the number of occurrences of the first blocking state and the second blocking state for the transaction execution states corresponding to each transaction-related monitoring indicator in the historical time period can be obtained respectively. Furthermore, the target monitoring indicator in the current time period can be determined according to the number of occurrences of the transaction impact results corresponding to each transaction-related monitoring indicator. Among them, the determination method can be to set corresponding weight thresholds for different transaction impact results. For example, when the weight value of the number of times the first blocking state is met exceeds 50%, or the weight value of the sum of the number of times the first blocking state and the second blocking state exceeds 80%, any of the weight thresholds, then the transaction-related monitoring indicator can be determined as the target monitoring indicator in the current time period. This embodiment does not make specific restrictions for comparison.

[0041] For example, if the transaction execution status corresponding to the resource loading time consumption is collected, the number of times the transaction impact result is the first blocking state collected in the historical time period may be 18 times, the number of times the second blocking state is collected may be 7 times, and the number of times the transaction is normal may be 5 times. Furthermore, it can be calculated that the weight value of the transaction impact result being the first blocking state is 60%, which exceeds the preset threshold of 50%, and the resource loading time consumption can be determined as the target monitoring indicator in the current time period.

[0042] This technical solution can determine the target monitoring indicators in the current time period based on the transaction impact results of each transaction-related monitoring indicator in the historical time period, and can capture and report abnormal transaction-related monitoring indicators during the transaction process, thereby improving the efficiency of transaction monitoring.

[0043] S130: Determine the target monitoring strategy for the target monitoring indicator in the current time period.

[0044] The monitoring strategy may refer to a pre-set time plan for collecting transaction impact results corresponding to each transaction-related monitoring indicator. For example, the monitoring strategy corresponding to the device peripheral module data may be collected once at 10 o'clock every day, the monitoring strategy corresponding to the performance data of the front-end page may be collected once every ten minutes, and the monitoring strategy corresponding to the user behavior data may be collected ten times a day. The specific time plan may be pre-set by the technical staff based on experience.

[0045] The target monitoring strategy may be a time plan for collecting transaction-related monitoring indicators and corresponding transaction impact results that cause the transaction process to fail to execute normally, and may specifically be a time plan adjusted based on a pre-set collection time plan. For example, if the target monitoring indicator is the performance data of the front-end page, the pre-set monitoring measurement type may be adjusted from collecting once every ten minutes to collecting three times every ten minutes, and this embodiment does not impose any specific restrictions on this.

[0046] Optionally, determining a target monitoring strategy for a target monitoring indicator in a current time period includes: determining an indicator type of the target monitoring indicator; determining a monitoring strategy type for the target monitoring indicator based on the indicator type; and generating a target monitoring strategy for the target monitoring indicator based on the monitoring strategy type.

[0047] Among them, the indicator type can be quantitative data used to determine the transaction impact results corresponding to each transaction-related monitoring indicator, which can include device peripheral module data, front-end page performance data, abnormal error data and user behavior data, etc.

[0048] For example, continuing with the above example, if the target monitoring indicator is the page dwell time, the indicator type of the target monitoring indicator can be determined as user behavior data. The monitoring strategy corresponding to the user behavior data is to collect data ten times a day, and a target monitoring strategy can be generated based on the monitoring strategy, such as collecting data twenty times a day, and used as the target monitoring strategy for page dwell time.

[0049] This technical solution can determine the indicator type of the target monitoring indicator, and then determine the monitoring strategy of the target monitoring indicator and generate the target monitoring strategy, thereby realizing indicator monitoring of the target monitoring indicator, increasing the flexibility of the transaction monitoring strategy, and further improving the efficiency of transaction monitoring.

[0050] S140. Based on the target monitoring strategy, monitor the target monitoring indicators.

[0051] Specifically, the monitoring strategy of the target monitoring indicator can be determined according to the indicator type of the target monitoring indicator, and the target monitoring strategy of the target monitoring indicator can be generated. Then, the target monitoring indicator can be monitored according to the generated target monitoring strategy.

[0052] The technical solution of the embodiment of the present invention is to obtain the transaction impact results corresponding to at least one transaction-related monitoring indicator in a preset historical time period; determine the target monitoring indicator in the current time period according to the transaction impact results of each transaction-related monitoring indicator; determine the target monitoring strategy for the target monitoring indicator in the current time period; and monitor the target monitoring indicator based on the target monitoring strategy. This technical solution can obtain the transaction impact results corresponding to the transaction-related monitoring indicators in the historical event period, and determine the target monitoring indicators and the corresponding target monitoring strategy in the current time period. It can adjust the monitoring strategy according to the transaction impact results, improve the efficiency of transaction monitoring, and also reduce the impact of abnormal transaction-related monitoring indicators on the transaction environment; further, it can also implement indicator monitoring of the target monitoring indicator through the target monitoring strategy, ensure the security and stability of the transaction, and further improve the user experience.

[0053] Embodiment 2

[0054] Figure 2 This is a flow chart of a transaction-related indicator monitoring method provided in the second embodiment of the present invention. Based on the above embodiment, this embodiment further optimizes the above transaction-related indicator monitoring method.

[0055] Furthermore, before the step of "obtaining the transaction impact results corresponding to at least one transaction-related monitoring indicator in a preset historical time period", add the step of "obtaining the indicator monitoring data of the transaction-related monitoring indicator obtained by monitoring at the indicator monitoring time point; inputting the indicator monitoring data into the pre-trained transaction impact result prediction model to obtain the transaction impact result output by the model; wherein the transaction impact result prediction model is obtained by training a preset classification model based on the indicator monitoring data samples of the monitoring indicator samples of different indicator types." to improve the monitoring process of the transaction-related monitoring indicators. Figure 2 As shown, the method includes:

[0056] S210: Obtain indicator monitoring data of the transaction-related monitoring indicator obtained through monitoring at the indicator monitoring time point.

[0057] The indicator monitoring data may be an indicator value corresponding to a transaction-related monitoring indicator, such as an indicator monitoring data of a page dwell time may be 10 seconds.

[0058] Specifically, according to the monitoring strategy corresponding to each transaction-related monitoring indicator, when the time point meets the indicator monitoring strategy, the indicator monitoring value corresponding to the transaction monitoring indicator is collected. For example, if the monitoring strategy for transaction time consumption is to collect at 10 o'clock every day, the indicator monitoring data of transaction time consumption can be obtained at 10 o'clock every morning, such as 5 seconds.

[0059] S220. Input the indicator monitoring data into a pre-trained transaction impact result prediction model to obtain the transaction impact result output by the model; wherein the transaction impact result prediction model is obtained by training a preset classification model based on indicator monitoring data samples of monitoring indicator samples of different indicator types.

[0060] Specifically, a transaction impact result prediction model can be obtained through pre-training, and based on the input indicator monitoring data, the transaction impact result obtained by predicting the indicator monitoring data is output. The transaction impact result prediction model can be a decision data model or a random forest model, which can be specifically set by technical personnel based on experience.

[0061] Optionally, the model training method of the transaction impact result prediction model is as follows: obtain indicator monitoring data samples of monitoring indicator samples of different indicator types in a historical time period; perform sample screening on each monitoring indicator sample to obtain indicator training samples; perform category labeling on the indicator training samples to obtain the true category labels of the indicator training samples; input the indicator monitoring data samples of the indicator training samples and their corresponding true category labels into a preset classification model to obtain the predicted impact category output by the model; perform model training on the classification model according to the true category labels and the predicted impact category until the preset model training end conditions are met to obtain the transaction impact result prediction model.

[0062] Among them, the real category label may refer to the identification information used to represent the transaction impact result corresponding to the indicator monitoring data. For example, the category label corresponding to the first blocking state may be -1, the category label corresponding to the second blocking state may be 0, and the category label corresponding to normal transaction may be 1.

[0063] Specifically, it is possible to obtain indicator monitoring data of different indicator types under historical time periods, generate indicator monitoring data samples, and screen indicator training samples. Then, the indicator training samples are categorized and labeled to obtain the transaction impact results corresponding to each indicator training sample. Then, the indicator monitoring data of the indicator training samples and the corresponding true category labels are input into the preset classification model to obtain the predicted impact category output by the model. Then, the classification model can be trained based on the true category labels and the predicted impact categories, and the model parameters can be adjusted by minimizing the loss function (or maximizing the objective function). The specific training methods may include gradient descent and optimization algorithms, etc. Until the preset model training end condition is met, where the model training end condition may be that the model reaches the preset maximum number of iterations or meets the model training time, and the transaction impact result prediction model is obtained.

[0064] This technical solution can use the indicator training samples obtained in the historical time period and perform category labeling to train the preset classification model and obtain the transaction impact result prediction model. Then, the transaction impact results of each transaction-related monitoring indicator can be predicted through the trained transaction impact result prediction model, and the abnormal transaction-related monitoring indicators can be captured and reported in a timely manner, thereby improving the efficiency of transaction monitoring.

[0065] Optionally, sample screening is performed on each monitoring indicator sample to obtain indicator training samples, including: using at least one feature screening method to screen each monitoring indicator sample to obtain screening indicator samples under each feature screening method; and determining indicator training samples based on the screening indicator samples under each feature screening method.

[0066] Specifically, the indicator data with low correlation with the transaction impact results in the monitoring indicator samples can be eliminated through the feature screening method to generate the screening indicator samples under the corresponding feature screening method; then, the screening indicator samples generated under different feature screening methods can be calculated to obtain the indicator training samples. Among them, the feature screening method can include information gain, variance selection method and linear regression algorithm, etc., and the calculation of the screening indicator samples can specifically be the intersection or union between the calculation samples.

[0067] For example, the monitoring indicator samples of user behavior data may be sampled, wherein the monitoring samples may include sample data such as page views, page dwell time, user clicks, and transaction time. Based on the variance selection method, it can be determined that the variance values ​​of page views and user clicks are lower than the threshold, that is, the contribution to the interaction result is small, and then the first screening indicator sample may be generated and include sample data such as page dwell time and transaction time; and the second screening indicator sample may be generated and include sample data such as page dwell time, page dwell time, and transaction time according to the linear regression algorithm. The first screening indicator sample and the second screening indicator sample may be intersected to generate an indicator training sample including sample data such as page dwell time and transaction time, and this embodiment does not impose specific restrictions on this.

[0068] This technical solution can use feature screening to screen samples of each monitoring indicator, obtain screening indicator samples, and determine indicator training samples. It can eliminate data with low correlation with transaction impact results in each transaction-related indicator, and select transaction-related monitoring indicators with high correlation, thereby reducing the calculation cost and avoiding overfitting of the model during model training. At the same time, only transaction-related indicators with high correlation are retained for indicator monitoring, which improves the efficiency of transaction monitoring.

[0069] S230: Obtain transaction impact results corresponding to at least one transaction-related monitoring indicator in a preset historical time period.

[0070] S240: Determine the target monitoring indicator in the current time period according to the transaction impact results of each transaction-related monitoring indicator.

[0071] S250: Determine the target monitoring strategy for the target monitoring indicator in the current time period.

[0072] S260. Based on the target monitoring strategy, the target monitoring indicators are monitored.

[0073] The technical solution of the embodiment of the present invention obtains the indicator monitoring data of the transaction-related monitoring indicator obtained by monitoring at the indicator monitoring time point, and inputs it into the transaction impact result prediction model obtained by pre-training to obtain the transaction impact result output by the model. Furthermore, the target monitoring indicator in the current time period can be determined according to the transaction impact result of the indicator monitoring data of the transaction-related monitoring indicator predicted; the target monitoring strategy of the target monitoring indicator in the current time period is determined; and the target monitoring indicator is monitored based on the target monitoring strategy. This technical solution can predict the transaction impact result corresponding to the indicator monitoring data of the transaction-related monitoring indicator through the transaction impact result prediction model obtained by pre-training, and can timely obtain the impact of the indicator monitoring data of each transaction-related monitoring indicator on the transaction activity, thereby improving the efficiency of transaction monitoring; at the same time, according to the predicted transaction impact degree, the indicator data value that causes the transaction to be unable to proceed normally can be monitored, further reducing the impact of the abnormal transaction-related monitoring indicator on the transaction environment, and ensuring the security and stability of the transaction.

[0074] It should be noted that the relevant information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data comply with relevant laws, regulations and standards in relevant regions.

[0075] Embodiment 3

[0076] Figure 3 The present invention provides a structural diagram of a transaction correlation indicator monitoring device provided in the third embodiment of the present invention. The transaction correlation indicator monitoring device provided in the embodiment of the present invention can be applied to situations where it is necessary to locate and monitor abnormal transaction correlation monitoring indicators during a transaction. The transaction correlation indicator monitoring device can be implemented in the form of hardware and / or software, such as Figure 3As shown, it specifically includes: a transaction impact result acquisition module 310, a target monitoring indicator determination module 320, a target monitoring strategy determination module 330 and an indicator monitoring module 340. Among them,

[0077] The transaction impact result acquisition module 310 is used to obtain the transaction impact results corresponding to at least one transaction-related monitoring indicator in a preset historical time period.

[0078] The target monitoring indicator determination module 320 is used to determine the target monitoring indicator in the current time period according to the transaction impact results of each of the transaction-related monitoring indicators.

[0079] The target monitoring strategy determination module 330 is used to determine the target monitoring strategy of the target monitoring indicator in the current time period.

[0080] The indicator monitoring module 340 is used to monitor the target monitoring indicator based on the target monitoring strategy.

[0081] This technical solution can obtain the transaction impact results corresponding to the transaction-related monitoring indicators under the historical event cycle, and determine the target monitoring indicators and the corresponding target monitoring strategies under the current time period. The monitoring strategies can be adjusted according to the transaction impact results, thereby improving the efficiency of transaction monitoring, while also reducing the impact of abnormal transaction-related monitoring indicators on the transaction environment; furthermore, the target monitoring strategies can be used to implement indicator monitoring of the target monitoring indicators, thereby ensuring the stability of the transaction and further improving the user experience.

[0082] Optionally, the transaction impact result includes transaction success, a first blocking state, and a second blocking state; accordingly, the target monitoring indicator determination module 320 is specifically used to:

[0083] Determine the first occurrence number of the transaction impact result of each of the transaction-related monitoring indicators in the historical time period as the first blocking state and the second occurrence number of the transaction impact result as the second blocking state;

[0084] According to the first number of occurrences and the second number of occurrences respectively corresponding to each of the transaction-related monitoring indicators, a target monitoring indicator in the current time period is determined.

[0085] Optionally, the target monitoring strategy determination module 330 is specifically used to:

[0086] Determine the indicator type of the target monitoring indicator;

[0087] Determine the monitoring strategy type of the target monitoring indicator according to the indicator type;

[0088] A target monitoring strategy for the target monitoring indicator is generated according to the monitoring strategy type.

[0089] Optionally, the device further includes a transaction impact result prediction module, which is used to, before obtaining the transaction impact results respectively corresponding to at least one transaction-related monitoring indicator in a preset historical time period,

[0090] Obtaining indicator monitoring data of the transaction-related monitoring indicator obtained by monitoring at the indicator monitoring time point;

[0091] The indicator monitoring data is input into a pre-trained transaction impact result prediction model to obtain a transaction impact result output by the model; wherein the transaction impact result prediction model is obtained by training a preset classification model based on indicator monitoring data samples of monitoring indicator samples of different indicator types.

[0092] Optionally, the device further includes a result prediction model training module;

[0093] Optional, result prediction model training module, including:

[0094] A monitoring data sample acquisition unit, used to acquire indicator monitoring data samples of monitoring indicator samples of different indicator types in a historical time period;

[0095] A sample screening unit, used to screen the monitoring indicator samples to obtain indicator training samples;

[0096] A label generation unit, used to perform category labeling on the indicator training samples to obtain true category labels of the indicator training samples;

[0097] An impact category determination unit, used to input the indicator monitoring data samples of the indicator training samples and their corresponding true category labels into a preset classification model to obtain a predicted impact category output by the model;

[0098] The result prediction model generating unit is used to perform model training on the classification model according to the real category label and the predicted impact category until a preset model training end condition is met to obtain a transaction impact result prediction model.

[0099] Optional, sample screening unit, specifically for:

[0100] Using at least one characteristic screening method to screen the monitoring indicator samples, and obtaining screening indicator samples under each characteristic screening method;

[0101] According to the screening index samples under each of the feature screening methods, the index training samples are determined.

[0102] The transaction-related indicator monitoring device provided in the embodiment of the present invention can execute the transaction-related indicator monitoring method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0103] Embodiment 4

[0104] Figure 4 A schematic diagram of the structure of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0105] like Figure 4 As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In RAM43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, ROM42 and RAM43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0106] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0107] The processor 41 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 executes the various methods and processes described above, such as the transaction correlation indicator monitoring method.

[0108] In some embodiments, the transaction correlation indicator monitoring method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the transaction correlation indicator monitoring method described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to perform the transaction correlation indicator monitoring method in any other appropriate manner (e.g., by means of firmware).

[0109] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0110] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0111] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0112] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0113] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0114] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0115] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0116] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A transaction-related indicator monitoring method, characterized in that: include: Obtaining transaction impact results corresponding to at least one transaction-related monitoring indicator in a preset historical time period; Determine the target monitoring indicator for the current time period according to the transaction impact results of each of the transaction-related monitoring indicators; Determine a target monitoring strategy for the target monitoring indicator in the current time period; Based on the target monitoring strategy, the target monitoring indicator is monitored.

2. The method according to claim 1, characterized in that The transaction impact result includes transaction success, a first blocking state, and a second blocking state; accordingly, determining the target monitoring indicator in the current time period according to the transaction impact result of each transaction-related monitoring indicator includes: Determine the first occurrence number of the transaction impact result of each of the transaction-related monitoring indicators in the historical time period as the first blocking state and the second occurrence number of the transaction impact result as the second blocking state; According to the first number of occurrences and the second number of occurrences respectively corresponding to each of the transaction-related monitoring indicators, a target monitoring indicator in the current time period is determined.

3. The method according to claim 1, characterized in that The determining of the target monitoring strategy of the target monitoring indicator in the current time period includes: Determining the indicator type of the target monitoring indicator; Determine the monitoring strategy type of the target monitoring indicator according to the indicator type; A target monitoring strategy for the target monitoring indicator is generated according to the monitoring strategy type.

4. The method according to claim 1, characterized in that: Before obtaining the transaction impact results respectively corresponding to at least one transaction-related monitoring indicator in a preset historical time period, the method further includes: Obtaining indicator monitoring data of the transaction-related monitoring indicator obtained by monitoring at the indicator monitoring time point; The indicator monitoring data is input into a pre-trained transaction impact result prediction model to obtain a transaction impact result output by the model; wherein the transaction impact result prediction model is obtained by training a preset classification model based on indicator monitoring data samples of monitoring indicator samples of different indicator types.

5. The method according to claim 4, characterized in that The model training method of the transaction impact result prediction model is as follows: Obtain indicator monitoring data samples of monitoring indicator samples of different indicator types in historical time periods; Performing sample screening on each of the monitoring indicator samples to obtain indicator training samples; Performing category labeling on the indicator training samples to obtain true category labels of the indicator training samples; Inputting the indicator monitoring data samples of the indicator training samples and their corresponding true category labels into a preset classification model to obtain the predicted impact category output by the model; The classification model is trained according to the true category label and the predicted impact category until a preset model training end condition is met, thereby obtaining a transaction impact result prediction model.

6. The method according to claim 5, characterized in that The step of screening the monitoring indicator samples to obtain indicator training samples includes: Using at least one characteristic screening method to screen the monitoring indicator samples, and obtaining screening indicator samples under each characteristic screening method; According to the screening index samples under each of the feature screening methods, the index training samples are determined.

7. A transaction-related indicator monitoring device, characterized in that: include: A transaction impact result acquisition module, used to acquire transaction impact results corresponding to at least one transaction-related monitoring indicator in a preset historical time period; A target monitoring indicator determination module, used to determine the target monitoring indicator in the current time period according to the transaction impact results of each of the transaction-related monitoring indicators; A target monitoring strategy determination module, used to determine the target monitoring strategy of the target monitoring indicator in the current time period; The indicator monitoring module is used to monitor the target monitoring indicator based on the target monitoring strategy.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the transaction-related indicator monitoring method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the transaction-related indicator monitoring method according to any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the computer program implements the transaction correlation indicator monitoring method according to any one of claims 1 to 6.

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