Method, device, electronic device and storage medium for detecting buried data

Abstract

The present invention relates to the field of data analysis, and discloses a method, device, electronic device and readable storage medium for detecting buried point data, wherein the method comprises: determining the buried point event type corresponding to the buried point demand, configuring the target buried point parameters according to the buried point demand; generating a buried point data table according to the target buried point parameters, and sending it to a preset target client; running the buried point demand automatic operation script to obtain the buried point event; obtaining the preset rules, detecting the timing and logical abnormalities of the buried point event according to the preset rules, and outputting the timing and logical abnormality data file; obtaining the buried point data table from the target client, detecting the abnormalities of the parameters of the buried point event according to the buried point data table, and outputting the parameter abnormality data file; sending the timing and logical abnormality data file and the parameter abnormality data file to the corresponding R&D personnel. The present invention can improve the accuracy of buried point data detection.

Description

Technical Field

[0001] The present invention relates to the field of data analysis, and in particular to a method, device, electronic device and readable storage medium for detecting buried data. Background Art

[0002] Tracking points refer to some program codes added to the client platform. When triggered, these program codes can collect and count the user's browsing, access data and application usage on the client platform. The collected and counted data is called tracking point data.

[0003] Currently, there are two common methods for detecting buried data: 1. Manual detection, which lacks intelligence. Due to the large amount of buried data, it is easy to cause errors in buried data detection, resulting in low accuracy of buried data detection; 2. Automated testing: Collecting reported data through proxy packet capture. When checking the reported data, it is impossible to confirm whether the reporting timing is correct, which easily leads to low accuracy of buried data detection. Summary of the invention

[0004] The present invention provides a method, device, electronic device and readable storage medium for detecting buried data, the purpose of which is to improve the accuracy of buried data detection.

[0005] To achieve the above object, the present invention provides a method for detecting buried data, the method comprising:

[0006] Obtaining tracking point requirements, classifying the tracking point requirements, obtaining tracking point event types, and configuring target tracking point parameters according to the tracking point requirements;

[0007] Generate a burying point data table according to the target burying point parameters, and send the burying point data table to a preset target client;

[0008] Run the preset tracking point requirement automatic running script to obtain the tracking point event corresponding to the tracking point requirement;

[0009] Obtaining preset rules for the buried event type, detecting the timing and logical abnormalities of the buried event according to the preset rules, and outputting a timing and logical abnormality data file;

[0010] Acquire the burying point data table from the target client, detect abnormal conditions of parameters of the burying point event according to the burying point data table, and output a parameter abnormality data file;

[0011] The timing and logic exception data file and the parameter exception data file are added to a preset exception problem queue, and the exception problem queue is sent to corresponding R&D personnel.

[0012] Optionally, detecting the timing and logical abnormality of the buried event according to the preset rule includes:

[0013] Obtain the tracking data and event type corresponding to the tracking event;

[0014] Based on the event type, select corresponding timing and logic rules;

[0015] Determine whether the embedding data meets the timing and logic rules;

[0016] When the burying point data meets the timing and logic rules, the burying point event is determined to be a normal burying point event;

[0017] When the embedding data does not conform to the timing and logic rules, the embedding event is determined to be a timing and logic abnormal data file.

[0018] Optionally, the detecting an abnormality of a parameter of the burying point event according to the burying point data table includes:

[0019] Obtaining the event type and parameters of the event.

[0020] Searching the buried point event type consistent with the event type from the buried point data table;

[0021] Based on the burying point event type, the burying point data table is disassembled to obtain target burying point parameters corresponding to the burying point event type;

[0022] Compare the parameters of the burying point event with the target burying point parameters one by one to determine whether the parameters of the burying point event are completely consistent with the target burying point parameters;

[0023] When the parameters of the tracking event are completely consistent with the target tracking parameters, the data file is determined to be a normal data file;

[0024] When the parameters of the burying point event are not completely consistent with the target burying point parameters, the data file is determined to be an abnormal data file.

[0025] Optionally, generating a burying point data table according to the target burying point parameters includes:

[0026] Perform lineage tracing on the target embedding point parameters to obtain embedding point requirements corresponding to the target embedding point parameters;

[0027] Classifying the target burying point parameters according to the burying point event type corresponding to the burying point requirement to obtain the classified target burying point parameters;

[0028] The classified target burying point parameters are stored in a data table according to the categories to obtain a burying point data table.

[0029] Optionally, the classifying the tracking point requirements to obtain tracking point event types includes:

[0030] Extract features of the embedding point requirements to obtain a feature vector set;

[0031] The feature vector set is classified using a pre-built naive Bayes classifier to obtain the buried event type.

[0032] Optionally, configuring target tracking point parameters according to the tracking point requirement includes:

[0033] Obtain the tracking event type and business requirements corresponding to the tracking requirements.

[0034] Based on business needs, the embedding points corresponding to the target embedding point parameter configurations that meet the preset definitions are filtered out from the embedding point parameters corresponding to the target embedding point event types.

[0035] Optionally, sending the abnormal problem queue to a corresponding R&D personnel includes:

[0036] Identify the IP address of the developer subscribed to the abnormal problem queue;

[0037] The timing and logic exception data files and parameter exception data files stored in the exception problem queue are sent to the IP address in the order of storage time.

[0038] In order to solve the above problems, the present invention further provides a buried point data detection device, the device comprising:

[0039] A burying point data table sending module is used to obtain burying point requirements, classify the burying point requirements, obtain burying point event types, configure target burying point parameters according to the burying point requirements, generate a burying point data table according to the target burying point parameters, and send the burying point data table to a preset target client;

[0040] The tracking event collection module is used to run the preset tracking demand automatic operation script to obtain the tracking event corresponding to the tracking demand;

[0041] The abnormal data file collection module uses the preset rules for obtaining the type of the buried point event, detects the abnormal conditions of the timing and logic of the buried point event according to the preset rules, outputs the timing and logic abnormal data files, obtains the buried point data table from the target client, detects the abnormal conditions of the parameters of the buried point event according to the buried point data table, outputs the parameter abnormal data file, adds the timing and logic abnormal data file and the parameter abnormal data file to a preset abnormal problem queue, and sends the abnormal problem queue to the corresponding R&D personnel.

[0042] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0043] a memory storing at least one computer program; and

[0044] The processor executes the computer program stored in the memory to implement the above-mentioned buried point data detection method.

[0045] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one computer program is stored. The at least one computer program is executed by a processor in an electronic device to implement the above-mentioned buried point data detection method.

[0046] The embodiment of the present invention first classifies the burying point requirements and obtains the burying point event type, so as to reduce the difficulty of burying point data matching and improve the efficiency of burying point data matching. According to the burying point event type, the target burying point parameters are configured, and the burying point data table generated according to the target burying point parameters is sent to the preset target client, so that the target burying point events in the burying point behavior performed by the client user can be screened out to ensure the accuracy of the burying point data. Secondly, the preset rules of the burying point event type are obtained, and according to the preset rules, the timing and logical abnormalities of the burying point event are detected, and the timing and logical abnormality data files are output to ensure that the abnormal burying point data are screened out, thereby improving the accuracy of the burying point data. Finally, the burying point data table is obtained from the target client, and the abnormality of the parameters of the burying point event is detected according to the burying point data table, and the parameter abnormality data file is output, which ensures that the parameters of the burying point data will not increase, decrease or be wrong from the parameter dimension, and further improves the accuracy of the burying point data. Therefore, the burying point data detection method, device, electronic device and readable storage medium proposed in the embodiment of the present invention can improve the accuracy of the burying point data. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic diagram of a flow chart of a method for detecting buried point data provided by an embodiment of the present invention;

[0048] Figure 2A schematic diagram of a module of a buried point data detection device provided by an embodiment of the present invention;

[0049] Figure 3 A schematic diagram of the internal structure of an electronic device for implementing a method for detecting buried data provided by an embodiment of the present invention;

[0050] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0052] An embodiment of the present invention provides a method for detecting buried data. The execution subject of the buried data detection method includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the buried data detection method can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server may include an independent server, or may include a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0053] Reference Figure 1 FIG. 1 is a flow chart of a method for detecting buried data provided by an embodiment of the present invention. In the embodiment of the present invention, the method for detecting buried data includes the following steps S1-S6:

[0054] S1. Obtain burying point requirements, classify the burying point requirements, obtain burying point event types, and configure target burying point parameters according to the burying point requirements.

[0055] In an embodiment of the present invention, the tracking point requirement may be for capturing, processing and sending what kind of behavior or event of a specific user, for example, the number of times a user clicks on a certain icon, the length of time a certain video is watched, etc., wherein the tracking point may be the relevant technology and its implementation process for capturing, processing and sending specific user behaviors or events. The tracking point event types include exposure events, article reading completion events, etc. The target tracking point parameters may be the data that needs to be collected when a user generates a tracking point event.

[0056] In an optional embodiment of the present invention, the tracking demand can be selected according to the business needs provided by the business personnel. For example, when the business needs of a company are to know what kind of articles the users are interested in, the tracking demand can be the users' article reading completion, speed and time.

[0057] The embodiment of the present invention classifies the buried point requirements to obtain buried point event types, which facilitates subsequent search for corresponding buried point events, reduces the time for buried point data detection, and improves the efficiency of buried point data detection.

[0058] Furthermore, in an optional embodiment of the present invention, the classifying the tracking point requirements to obtain tracking point event types includes:

[0059] Extract features of the embedding point requirements to obtain a feature vector set;

[0060] The feature vector set is classified using a pre-built naive Bayes classifier to obtain the buried event type.

[0061] In the embodiment of the present invention, the naive Bayes classifier may be a series of simple probabilistic classifiers based on applying the Bayesian theorem under the assumption of strong (naive) independence between features.

[0062] The embodiment of the present invention configures target burying point parameters according to the burying point requirements, so as to facilitate subsequent burying point data comparison and find out redundant, missing or erroneous burying point data, thereby improving the accuracy of burying point data detection.

[0063] Further, in an optional embodiment of the present invention, configuring target tracking parameters according to the tracking requirement includes:

[0064] Obtain the tracking event type and business requirement corresponding to the tracking requirement;

[0065] Based on business needs, the embedding points corresponding to the target embedding point parameter configurations that meet the preset definitions are filtered out from the embedding point parameters corresponding to the embedding point event types.

[0066] In an embodiment of the present invention, the business demand may be a demand for embedded data in a company's business. For example, if you want to know what music a user is interested in, you need to obtain the user's listening time and type of music, etc. The preset definition may be a parameter that helps solve the business demand.

[0067] In an optional embodiment of the present invention, the burying point requirements are first analyzed to determine the specific burying point events corresponding to the burying point requirements, and then the business requirements are derived from the burying point events, so as to facilitate R&D personnel to determine the target burying point parameters and improve the accuracy of data analysis based on burying point data.

[0068] S2. Generate a burying point data table according to the target burying point parameters, and send the burying point data table to a preset target client.

[0069] In the embodiment of the present invention, the embedding data table includes embedding events corresponding to the target embedding parameters. The preset target client may be a specific page or APP in the terminal used by the user.

[0070] The embodiment of the present invention generates a burying point data table according to the target burying point parameters, provides a template for the burying point data to be collected, and improves the accuracy of burying point data collection.

[0071] Further, as an optional embodiment of the present invention, generating a burying point data table according to the target burying point parameters includes:

[0072] Perform lineage tracing on the target embedding point parameters to obtain embedding point requirements corresponding to the target embedding point parameters;

[0073] Classifying the target burying point parameters according to the burying point event type corresponding to the burying point requirement to obtain the classified target burying point parameters;

[0074] The classified target burying point parameters are stored in a data table according to the categories to obtain a burying point data table.

[0075] In an optional embodiment of the present invention, by tracking the source of the target burial point parameters, the category corresponding to each target burial point is confirmed, and then the target burial point parameters are classified and stored in a pre-constructed data table, which is beneficial for comparing subsequent burial point events with the target burial point parameters and improves the efficiency of burial point parameter comparison.

[0076] The embodiment of the present invention ensures that the target client can collect the buried point data required by the buried point data table by sending the buried point data table to a preset target client, thereby improving the accuracy of buried point data collection, thereby reducing the amount of buried point data collected, and thus improving the efficiency of buried point data detection.

[0077] S3. Run the preset tracking point requirement automatic operation script to obtain the tracking point event corresponding to the tracking point requirement.

[0078] In an embodiment of the present invention, the preset tracking demand automatic operation script may be a script written by a developer to simulate a user performing tracking events on the target client.

[0079] An optional embodiment of the present invention realizes the operation of the automatic operation script of the tracking point demand by compiling the tracking point demand automatic operation script, thereby simulating the user to perform the tracking point event on the target client, thereby improving the intelligence level of tracking point data collection.

[0080] In addition, in an optional embodiment of the present invention, manual simulation can also be used to realize the collection of buried point data.

[0081] S4. Obtain the preset rules of the buried event type, detect the timing and logical abnormalities of the buried event according to the preset rules, and output the timing and logical abnormality data file.

[0082] In an embodiment of the present invention, the preset rule may be a rule that defines different rules according to the event type. For example, when the buried event type is an exposure event, the preset rule may be that if the same event is exposed and reported multiple times within a certain period of time, it can be regarded as an abnormality. When the buried event type is an article reading event, the preset rule may be that when the article length exceeds one screen, it is determined whether the slider of the article reading length control slides to more than 80% of the bottom of the article and whether the effective reading speed per second is less than the preset speed. When the length does not exceed one screen, only the effective reading speed per second is determined.

[0083] In an optional embodiment of the present invention, by defining rules in advance and storing the rules in the target client, it is possible to obtain preset rules for the buried point event type, thereby improving the efficiency and accuracy of buried point data detection.

[0084] The embodiment of the present invention detects the timing and logical anomalies of the buried point events according to the preset rules, outputs the timing and logical anomaly data files, and filters out the buried point data that meets the preset rules, thereby improving the accuracy of the buried point data and reducing the company's losses caused by buried point data errors.

[0085] Further, as an optional embodiment of the present invention, detecting the timing and logical abnormality of the buried event according to the preset rule includes:

[0086] Obtain the tracking data and event type corresponding to the tracking event;

[0087] Based on the event type, select corresponding timing and logic rules;

[0088] Determine whether the embedding data meets the timing and logic rules;

[0089] When the burying point data meets the timing and logic rules, the burying point event is determined to be a normal burying point event;

[0090] When the embedding data does not conform to the timing and logic rules, the embedding event is determined to be a timing and logic abnormal data file.

[0091] In an embodiment of the present invention, the buried data may be specific values ​​of parameters corresponding to the buried events, such as the number of exposures of the same event, the degree of article reading completion, etc.

[0092] An optional embodiment of the present invention determines whether the buried point event is a timing and logical abnormality data file by specifically analyzing the buried point data corresponding to the buried point event, thereby preliminarily improving the accuracy of the buried point data.

[0093] S5. Obtain the burying point data table from the target client, detect abnormal conditions of parameters of the burying point event according to the burying point data table, and output a parameter abnormality data file.

[0094] In an embodiment of the present invention, the parameters of the burying event may be the number, time, address, etc. of the burying event. For example, when the burying event is opening the WeChat software, at this time, the parameters of the burying event may be the number of times the user opens the WeChat APP, the time of opening WeChat, etc.

[0095] In an optional embodiment of the present invention, the storage space of the target client can be searched to obtain the buried point data table, thereby performing parameter comparison to ensure that there are no additions, deletions, errors, etc. in the parameters of the buried point events, thereby improving the accuracy of the buried point data.

[0096] The embodiment of the present invention detects abnormal conditions of the parameters of the buried point event according to the buried point data table, outputs a parameter abnormality data file, and filters out the parameter abnormal buried point data, thereby further ensuring the accuracy of the buried point data.

[0097] Further, as an optional embodiment of the present invention, the detecting an abnormality of a parameter of the buried point event according to the buried point data table includes:

[0098] Obtaining the event type and parameters of the event.

[0099] Searching the buried point event type consistent with the event type from the buried point data table;

[0100] Based on the burying point event type, the burying point data table is disassembled to obtain target burying point parameters corresponding to the burying point event type;

[0101] Compare the parameters of the burying point event with the target burying point parameters one by one to determine whether the parameters of the burying point event are completely consistent with the target burying point parameters;

[0102] When the parameters of the tracking event are completely consistent with the target tracking parameters, the data file is determined to be a normal data file;

[0103] When the parameters of the burying point event are not completely consistent with the target burying point parameters, the data file is determined to be an abnormal data file.

[0104] In an optional embodiment of the present invention, the buried point event type consistent with the event type is searched from the buried point data table through the event type, thereby reducing the time consumed by parameter comparison and improving the efficiency of buried point data detection.

[0105] S6. Add the timing and logic exception data file and the parameter exception data file to a preset exception problem queue, and send the exception problem queue to corresponding R&D personnel.

[0106] In the embodiment of the present invention, the preset abnormal problem queue may be a message queue for transmitting abnormal problems to R&D personnel.

[0107] The embodiment of the present invention solves the problem of abnormal buried data by sending the abnormal problem queue to the corresponding R&D personnel, thereby improving the accuracy of the buried data.

[0108] Further, as an optional embodiment of the present invention, sending the abnormal problem queue to the corresponding R&D personnel includes:

[0109] Identify the IP address of the developer subscribed to the abnormal problem queue;

[0110] The timing and logic exception data files and parameter exception data files stored in the exception problem queue are sent to the IP address in the order of storage time.

[0111] In an embodiment of the present invention, R&D personnel who handle abnormal problems subscribe to the abnormal problem queue to obtain the timing, logical abnormal data file and parameter abnormal data file automatically sent by the abnormal message queue, ensuring that the R&D personnel can modify the target tracking point parameters according to the timing, logical abnormal data file and parameter abnormal data file, thereby further improving the accuracy of the tracking point data.

[0112] The embodiment of the present invention first classifies the burying point requirements and obtains the burying point event type, so as to reduce the difficulty of burying point data matching and improve the burying point data matching efficiency. According to the burying point event type, the target burying point parameters are configured, and the burying point data table generated according to the target burying point parameters is sent to the preset target client, so that the target burying point events in the burying point behavior performed by the client user can be screened out to ensure the accuracy of the burying point data. Secondly, the preset rules of the burying point event type are obtained, and according to the preset rules, the timing and logical abnormalities of the burying point event are detected, and the timing and logical abnormality data files are output to ensure that the abnormal burying point data are screened out, thereby improving the accuracy of the burying point data. Finally, the burying point data table is obtained from the target client, and the abnormal conditions of the parameters of the burying point event are detected according to the burying point data table, and the parameter abnormality data file is output, which ensures that the parameters of the burying point data will not increase, decrease or be wrong from the parameter dimension, thereby further improving the accuracy of the burying point data. Therefore, the burying point data detection method proposed in the embodiment of the present invention can improve the accuracy of the burying point data.

[0113] like Figure 2 The figure shows a functional module diagram of the buried point data detection device of the present invention.

[0114] The buried point data detection device 100 of the present invention can be installed in an electronic device. According to the functions to be implemented, the buried point data detection device 100 can include a buried point data table sending module 101, a buried point event collection module 102 and an abnormal data file collection module 103. The module of the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0115] In this embodiment, the functions of each module / unit are as follows:

[0116] The burying point data table sending module 101 is used to obtain burying point requirements, classify the burying point requirements, obtain burying point event types, configure target burying point parameters according to the burying point requirements, generate a burying point data table according to the target burying point parameters, and send the burying point data table to a preset target client.

[0117] In an embodiment of the present invention, the tracking point requirement may be what kind of behavior or event of a specific user is captured, processed and sent, for example, the number of times a user clicks on a certain icon, the length of time a certain video is watched, etc., wherein the tracking point may be the relevant technology and its implementation process for capturing, processing and sending specific user behaviors or events. The tracking point event types include exposure events, article reading completion events, etc. The target tracking point parameters may be the data that needs to be collected when a user generates a tracking point event.

[0118] In an optional embodiment of the present invention, the tracking demand can be selected according to the business needs provided by the business personnel. For example, when the business needs of a company are to know what kind of articles the users are interested in, the tracking demand can be the users' article reading completion, speed and time.

[0119] The embodiment of the present invention classifies the buried point requirements to obtain buried point event types, which facilitates subsequent search for corresponding buried point events, reduces the time for buried point data detection, and improves the efficiency of buried point data detection.

[0120] Furthermore, in an optional embodiment of the present invention, the classifying the tracking point requirements to obtain tracking point event types includes:

[0121] Extract features of the embedding point requirements to obtain a feature vector set;

[0122] The feature vector set is classified using a pre-built naive Bayes classifier to obtain the buried event type.

[0123] In the embodiment of the present invention, the naive Bayes classifier may be a series of simple probabilistic classifiers based on applying the Bayesian theorem under the assumption of strong (naive) independence between features.

[0124] The embodiment of the present invention configures target burying point parameters according to the burying point requirements, so as to facilitate subsequent burying point data comparison and find out redundant, missing or erroneous burying point data, thereby improving the accuracy of burying point data detection.

[0125] Further, in an optional embodiment of the present invention, configuring target tracking parameters according to the tracking requirement includes:

[0126] Obtain the tracking event type and business requirement corresponding to the tracking requirement;

[0127] Based on business needs, the embedding points corresponding to the target embedding point parameter configurations that meet the preset definitions are filtered out from the embedding point parameters corresponding to the embedding point event types.

[0128] In an embodiment of the present invention, the business demand may be a demand for embedded data in a company's business. For example, if you want to know what music a user is interested in, you need to obtain the user's listening time and type of music, etc. The preset definition may be a parameter that helps solve the business demand.

[0129] In an optional embodiment of the present invention, the burying point requirements are first analyzed to determine the specific burying point events corresponding to the burying point requirements, and then the business requirements are derived from the burying point events, so as to facilitate R&D personnel to determine the target burying point parameters and improve the accuracy of data analysis based on burying point data.

[0130] In the embodiment of the present invention, the embedding data table includes embedding events corresponding to the target embedding parameters. The preset target client may be a specific page or APP in the terminal used by the user.

[0131] The embodiment of the present invention generates a burying point data table according to the target burying point parameters, provides a template for the burying point data to be collected, and improves the accuracy of burying point data collection.

[0132] Further, as an optional embodiment of the present invention, generating a burying point data table according to the target burying point parameters includes:

[0133] Perform lineage tracing on the target embedding point parameters to obtain embedding point requirements corresponding to the target embedding point parameters;

[0134] Classifying the target burying point parameters according to the burying point event type corresponding to the burying point requirement to obtain the classified target burying point parameters;

[0135] The classified target burying point parameters are stored in a data table according to the categories to obtain a burying point data table.

[0136] In an optional embodiment of the present invention, by tracking the source of the target burial point parameters, the category corresponding to each target burial point is confirmed, and then the target burial point parameters are classified and stored in a pre-constructed data table, which is beneficial for comparing subsequent burial point events with the target burial point parameters and improves the efficiency of burial point parameter comparison.

[0137] The embodiment of the present invention ensures that the target client can collect the buried point data required by the buried point data table by sending the buried point data table to a preset target client, thereby improving the accuracy of buried point data collection, thereby reducing the amount of buried point data collected, and thus improving the efficiency of buried point data detection.

[0138] The tracking point event collection module 102 is used to run the preset tracking point demand automatic operation script to obtain the tracking point event corresponding to the tracking point demand.

[0139] In an embodiment of the present invention, the preset tracking demand automatic operation script may be a script written by a developer to simulate a user performing tracking events on the target client.

[0140] An optional embodiment of the present invention realizes the operation of the automatic operation script of the tracking point demand by compiling the tracking point demand automatic operation script, thereby simulating the user to perform the tracking point event on the target client, thereby improving the intelligence level of tracking point data collection.

[0141] In addition, in an optional embodiment of the present invention, manual simulation can also be used to realize the collection of buried point data.

[0142] The abnormal data file collection module 103 uses preset rules to obtain the type of the buried point event, detects the abnormal conditions of the timing and logic of the buried point event according to the preset rules, outputs the timing and logic abnormal data files, obtains the buried point data table from the target client, detects the abnormal conditions of the parameters of the buried point event according to the buried point data table, outputs the parameter abnormal data file, adds the timing and logic abnormal data file and the parameter abnormal data file to a preset abnormal problem queue, and sends the abnormal problem queue to the corresponding R&D personnel.

[0143] In an embodiment of the present invention, the preset rule may be a rule that defines different rules according to the event type. For example, when the buried event type is an exposure event, the preset rule may be that if the same event is exposed and reported multiple times within a certain period of time, it can be regarded as an abnormality. When the buried event type is an article reading event, the preset rule may be that when the article length exceeds one screen, it is determined whether the slider of the article reading length control slides to more than 80% of the bottom of the article and whether the effective reading speed per second is less than the preset speed. When the length does not exceed one screen, only the effective reading speed per second is determined.

[0144] In an optional embodiment of the present invention, by defining rules in advance and storing the rules in the target client, it is possible to obtain preset rules for the buried point event type, thereby improving the efficiency and accuracy of buried point data detection.

[0145] The embodiment of the present invention detects the timing and logical anomalies of the buried point events according to the preset rules, outputs the timing and logical anomaly data files, and filters out the buried point data that meets the preset rules, thereby improving the accuracy of the buried point data and reducing the company's losses caused by buried point data errors.

[0146] Further, as an optional embodiment of the present invention, detecting the timing and logical abnormality of the buried event according to the preset rule includes:

[0147] Obtain the tracking data and event type corresponding to the tracking event;

[0148] Based on the event type, select corresponding timing and logic rules;

[0149] Determine whether the embedding data meets the timing and logic rules;

[0150] When the burying point data meets the timing and logic rules, the burying point event is determined to be a normal burying point event;

[0151] When the embedding data does not conform to the timing and logic rules, the embedding event is determined to be a timing and logic abnormal data file.

[0152] In an embodiment of the present invention, the buried data may be specific values ​​of parameters corresponding to the buried events, such as the number of exposures of the same event, the degree of article reading completion, etc.

[0153] An optional embodiment of the present invention determines whether the buried point event is a timing and logical abnormality data file by specifically analyzing the buried point data corresponding to the buried point event, thereby preliminarily improving the accuracy of the buried point data.

[0154] In an embodiment of the present invention, the parameters of the burying event may be the number, time, address, etc. of the burying event. For example, when the burying event is opening the WeChat software, at this time, the parameters of the burying event may be the number of times the user opens the WeChat APP, the time of opening WeChat, etc.

[0155] In an optional embodiment of the present invention, the storage space of the target client can be searched to obtain the buried point data table, thereby performing parameter comparison to ensure that there are no additions, deletions, errors, etc. in the parameters of the buried point events, thereby improving the accuracy of the buried point data.

[0156] The embodiment of the present invention detects abnormal conditions of the parameters of the buried point event according to the buried point data table, outputs a parameter abnormality data file, and filters out the parameter abnormal buried point data, thereby further ensuring the accuracy of the buried point data.

[0157] Further, as an optional embodiment of the present invention, the detecting an abnormality of a parameter of the buried point event according to the buried point data table includes:

[0158] Obtaining the event type and parameters of the event.

[0159] Searching the buried point event type consistent with the event type from the buried point data table;

[0160] Based on the burying point event type, the burying point data table is disassembled to obtain target burying point parameters corresponding to the burying point event type;

[0161] Compare the parameters of the burying point event with the target burying point parameters one by one to determine whether the parameters of the burying point event are completely consistent with the target burying point parameters;

[0162] When the parameters of the tracking event are completely consistent with the target tracking parameters, the data file is determined to be a normal data file;

[0163] When the parameters of the burying point event are not completely consistent with the target burying point parameters, the data file is determined to be an abnormal data file.

[0164] In an optional embodiment of the present invention, the buried point event type consistent with the event type is searched from the buried point data table through the event type, thereby reducing the time consumed by parameter comparison and improving the efficiency of buried point data detection.

[0165] In the embodiment of the present invention, the preset abnormal problem queue may be a message queue for transmitting abnormal problems to R&D personnel.

[0166] The embodiment of the present invention solves the problem of abnormal buried data by sending the abnormal problem queue to the corresponding R&D personnel, thereby improving the accuracy of the buried data.

[0167] Further, as an optional embodiment of the present invention, sending the abnormal problem queue to the corresponding R&D personnel includes:

[0168] Identify the IP address of the developer subscribed to the abnormal problem queue;

[0169] The timing and logic exception data files and parameter exception data files stored in the exception problem queue are sent to the IP address in the order of storage time.

[0170] In an embodiment of the present invention, R&D personnel who handle abnormal problems subscribe to the abnormal problem queue to obtain the timing, logical abnormal data file and parameter abnormal data file automatically sent by the abnormal message queue, ensuring that the R&D personnel can modify the target tracking point parameters according to the timing, logical abnormal data file and parameter abnormal data file, thereby further improving the accuracy of the tracking point data.

[0171] like Figure 3 The figure is a schematic diagram of the structure of an electronic device for implementing the buried point data detection method of the present invention.

[0172] The electronic device may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a buried point data detection program.

[0173] Among them, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 can also be an external storage device of an electronic device, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Furthermore, the memory 11 can also include both an internal storage unit of the electronic device and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device, such as the code of the buried point data detection program, but also can be used to temporarily store data that has been output or is to be output.

[0174] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect the various components of the entire electronic device, and executes or executes programs or modules (such as buried point data detection programs, etc.) stored in the memory 11, and calls the data stored in the memory 11 to perform various functions of the electronic device and process data.

[0175] The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The communication bus 12 is configured to realize connection and communication between the memory 11 and at least one processor 10, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0176] Figure 3 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 3The structure shown does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0177] For example, although not shown, the electronic device may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0178] Optionally, the communication interface 13 may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices.

[0179] Optionally, the communication interface 13 may also include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0180] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0181] The buried point data detection program stored in the memory 11 in the electronic device is a combination of multiple computer programs. When running in the processor 10, it can achieve:

[0182] Obtaining tracking point requirements, classifying the tracking point requirements, obtaining tracking point event types, and configuring target tracking point parameters according to the tracking point requirements;

[0183] Generate a burying point data table according to the target burying point parameters, and send the burying point data table to a preset target client;

[0184] Run the preset tracking point requirement automatic running script to obtain the tracking point event corresponding to the tracking point requirement;

[0185] Obtaining preset rules for the buried event type, detecting the timing and logical abnormalities of the buried event according to the preset rules, and outputting a timing and logical abnormality data file;

[0186] Acquire the burying point data table from the target client, detect abnormal conditions of parameters of the burying point event according to the burying point data table, and output a parameter abnormality data file;

[0187] The timing and logic exception data file and the parameter exception data file are added to a preset exception problem queue, and the exception problem queue is sent to corresponding R&D personnel.

[0188] Specifically, the specific implementation method of the processor 10 for the above computer program can refer to Figure 1 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0189] Furthermore, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable medium can be non-volatile or volatile. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM).

[0190] An embodiment of the present invention may further provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program may implement:

[0191] Obtaining tracking point requirements, classifying the tracking point requirements, obtaining tracking point event types, and configuring target tracking point parameters according to the tracking point requirements;

[0192] Generate a burying point data table according to the target burying point parameters, and send the burying point data table to a preset target client;

[0193] Run the preset tracking point requirement automatic running script to obtain the tracking point event corresponding to the tracking point requirement;

[0194] Obtaining preset rules for the buried event type, detecting the timing and logical abnormalities of the buried event according to the preset rules, and outputting a timing and logical abnormality data file;

[0195] Acquire the burying point data table from the target client, detect abnormal conditions of parameters of the burying point event according to the burying point data table, and output a parameter abnormality data file;

[0196] The timing and logic exception data file and the parameter exception data file are added to a preset exception problem queue, and the exception problem queue is sent to corresponding R&D personnel.

[0197] Furthermore, the computer-usable storage medium may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function, etc.; the data storage area may store data created according to the use of the blockchain node, etc.

[0198] In the several embodiments provided by the present invention, it should be understood that the disclosed electronic device, apparatus and method can be implemented in other ways. For example, the apparatus embodiment described above is only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0199] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0200] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0201] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0202] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any attached figure mark in the claims should not be regarded as limiting the claims involved.

[0203] The blockchain referred to in this invention is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0204] In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the system claim can also be implemented by one unit or device through software or hardware. The second and other words are used to indicate names, but not to indicate any particular order.

[0205] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for detecting buried data, characterized in that: The method comprises: Obtaining tracking point requirements, classifying the tracking point requirements, obtaining tracking point event types, and configuring target tracking point parameters according to the tracking point requirements; Generate a burying point data table according to the target burying point parameters, and send the burying point data table to a preset target client; Run the preset tracking point requirement automatic running script to obtain the tracking point event corresponding to the tracking point requirement; Obtain the preset rules of the buried point event type, determine whether the buried point data corresponding to the buried point event conforms to the preset rules, the buried point data is the specific value of the parameter corresponding to the buried point event, detect the timing and logical abnormalities of the buried point event, and output the timing and logical abnormality data file; Acquire the burying point data table from the target client, detect abnormal conditions of parameters of the burying point event according to the burying point data table, and output a parameter abnormality data file; The timing and logic exception data file and the parameter exception data file are added to a preset exception problem queue, and the exception problem queue is sent to corresponding R&D personnel.

2. The method for detecting buried point data according to claim 1, characterized in that: The detecting, according to the preset rules, the timing of the buried event and the abnormality of the logic includes: Obtain the tracking data and event type corresponding to the tracking event; Based on the event type, select corresponding timing and logic rules; Determine whether the embedding data meets the timing and logic rules; When the burying point data meets the timing and logic rules, the burying point event is determined to be a normal burying point event; When the embedding data does not conform to the timing and logic rules, the embedding event is determined to be a timing and logic abnormal data file.

3. The method for detecting buried point data according to claim 1, characterized in that: The detecting an abnormality of a parameter of the burying point event according to the burying point data table includes: Obtaining the event type and parameters of the event. Searching the buried point event type consistent with the event type from the buried point data table; Based on the burying point event type, the burying point data table is disassembled to obtain target burying point parameters corresponding to the burying point event type; Compare the parameters of the burying point event with the target burying point parameters one by one to determine whether the parameters of the burying point event are completely consistent with the target burying point parameters; When the parameters of the tracking event are completely consistent with the target tracking parameters, the data file is determined to be a normal data file; When the parameters of the burying point event are not completely consistent with the target burying point parameters, the data file is determined to be an abnormal data file.

4. The method for detecting buried point data according to claim 1, characterized in that: The step of generating a burying point data table according to the target burying point parameters includes: Perform lineage tracing on the target embedding point parameters to obtain embedding point requirements corresponding to the target embedding point parameters; Classifying the target burying point parameters according to the burying point event type corresponding to the burying point requirement to obtain the classified target burying point parameters; The classified target burying point parameters are stored in a data table according to the categories to obtain a burying point data table.

5. The method for detecting buried point data according to claim 1, characterized in that: The classifying the tracking point requirements to obtain tracking point event types includes: Extracting a feature vector of the embedding demand; The feature vector is classified using a pre-built naive Bayes classifier to obtain the buried event type.

6. The method for detecting buried point data according to claim 1, characterized in that: The configuring target tracking point parameters according to the tracking point requirements includes: Obtain the tracking event type and business requirements corresponding to the tracking requirements. Based on business needs, the embedding points corresponding to the target embedding point parameter configurations that meet the preset definitions are filtered out from the embedding point parameters corresponding to the target embedding point event types.

7. The method for detecting buried point data according to claim 1, characterized in that: The sending of the abnormal problem queue to the corresponding R&D personnel includes: Identify the IP address of the developer subscribed to the abnormal problem queue; The timing and logic exception data files and parameter exception data files stored in the exception problem queue are sent to the IP address in the order of storage time.

8. A buried point data detection device, characterized in that: The device comprises: A burying point data table sending module is used to obtain burying point requirements, classify the burying point requirements, obtain burying point event types, configure target burying point parameters according to the burying point requirements, generate a burying point data table according to the target burying point parameters, and send the burying point data table to a preset target client; The tracking event collection module is used to run the preset tracking demand automatic operation script to obtain the tracking event corresponding to the tracking demand; The abnormal data file collection module uses the preset rules for obtaining the type of the buried point event to determine whether the buried point data corresponding to the buried point event conforms to the preset rules, the buried point data is the specific value of the parameter corresponding to the buried point event, detects the abnormal conditions of the timing and logic of the buried point event, outputs the timing and logic abnormal data files, obtains the buried point data table from the target client, detects the abnormal conditions of the parameters of the buried point event according to the buried point data table, outputs the parameter abnormal data file, adds the timing and logic abnormal data file and the parameter abnormal data file to the preset abnormal problem queue, and sends the abnormal problem queue to the corresponding R&D personnel.

9. 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 computer program instructions that can be executed by the at least one processor, and the computer program instructions are executed by the at least one processor so that the at least one processor can execute the buried point data detection method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the buried point data detection method as described in any one of claims 1 to 7 is implemented.

Images