Detection behavior analysis method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a detection behavior analysis method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining target detection data which comprises data which is recorded by recycled electronic equipment and is related to a detection behavior in the process that a first user detects the recycled electronic equipment; data analysis is conducted on the target detection data on the basis of a target analysis strategy, an analysis result associated with the detection behavior is obtained, and the target analysis strategy is an analysis strategy preset on the basis of the recycled electronic equipment; and outputting an analysis result associated with the detection behavior. Under the business scene that the detection data needs to be analyzed and processed, manual participation is not needed, and the analysis result can be output more quickly while the situation that the analysis result is not stable enough under the condition of manual analysis is avoided.

Description

Technical Field

[0001] The present application relates to the technical field of article recycling, and in particular to an analysis method, device, electronic device and storage medium for detecting behavior. Background Art

[0002] With the development of social economy, consumers buy new goods more and more frequently, which leads to a large number of second-hand goods being idle or discarded, resulting in a waste of resources. To solve this problem, the second-hand goods recycling business came into being, which can collect these second-hand goods and put them back on the market after refurbishment or repair, thus realizing the reuse of resources.

[0003] At present, in the process of recycling second-hand goods, experienced inspectors are usually required to conduct visual inspections and functional tests on the goods, and collect and record relevant data during the inspection process through tracking. Finally, with the help of the tracking platform, relevant inspection data can be queried.

[0004] However, due to the limitation of the function of the tracking point platform, it can only provide simple data query function. In some business scenarios, manual secondary processing of the queried detection data is required. The whole process is not only time-consuming, but also the results of the secondary processing are greatly affected by the professional ability of the personnel and are not stable enough. Summary of the invention

[0005] Based on the above technical status, the present application proposes a detection behavior analysis method, device, electronic device and storage medium, which can realize automatic analysis of detection data and output analysis results more quickly.

[0006] According to a first aspect of an embodiment of the present application, a method for analyzing detection behavior is provided, the method comprising: acquiring target detection data, wherein the target detection data comprises: data associated with the detection behavior recorded by a recycled electronic device during a process in which a first user detects and recycles the electronic device; performing data analysis on the target detection data based on a target analysis strategy to obtain an analysis result associated with the detection behavior, wherein the target analysis strategy is an analysis strategy pre-set based on the recycled electronic device; and outputting the analysis result associated with the detection behavior.

[0007] In some optional embodiments, the data associated with the detection behavior recorded by the recycling electronic device includes: behavior data characterizing the detection behavior collected by the recycling electronic device and performance data of the recycling electronic device under the detection behavior;

[0008] The target detection data is analyzed based on the target analysis strategy to obtain an analysis result associated with the detection behavior, including: based on the target analysis strategy and the performance data, the detection behavior represented by the behavior data is analyzed to obtain an analysis result representing whether the detection behavior is compliant.

[0009] In some optional embodiments, obtaining the target detection data includes: obtaining the behavior data and the performance data reported in real time by the recycled electronic device during the detection process;

[0010] Outputting an analysis result associated with the detection behavior includes: sending the analysis result to the recycled electronic device when the analysis result indicates that the detection behavior is non-compliant.

[0011] In some optional embodiments, the behavior data includes: behavior data characterizing appearance detection behavior; the performance data includes: posture information of the recycled electronic device and the duration of stay in each posture.

[0012] In some optional embodiments, the data associated with the detection behavior recorded by the recycling electronic device further includes: identity information of the first user;

[0013] After obtaining an analysis result characterizing whether the detection behavior is compliant, the method also includes: when the analysis result characterizes that the detection behavior is non-compliant and the cumulative number of non-compliant detection behaviors of the first user is greater than a number threshold, banning the electronic account indicated by the identity information or sending a reminder message to a second user associated with the identity information.

[0014] In some optional embodiments, the target detection data further includes: device information of the recycled electronic device;

[0015] Before performing data analysis on the target detection data based on the target analysis strategy to obtain an analysis result associated with the detection behavior, the method further includes: determining a target analysis strategy corresponding to the recycled electronic device in a policy library based on device information of the recycled electronic device; wherein a plurality of analysis strategies are provided in the policy library, and each analysis strategy corresponds to a different electronic device.

[0016] In some optional embodiments, obtaining target detection data includes: receiving target detection data in a unified data format reported by multiple clients through embedding points, wherein the multiple clients include clients under different operating systems.

[0017] In some optional embodiments, after acquiring the target detection data, the method further includes: storing the target detection data in a first database and a second database respectively, wherein the first database retains the data for a longer period than the second database retains the data.

[0018] According to a second aspect of an embodiment of the present application, a detection behavior analysis device is provided, the device comprising: an acquisition module, used to acquire target detection data, wherein the target detection data comprises: data associated with the detection behavior recorded by the recycled electronic device during a first user's detection of recycled electronic devices; an analysis module, used to perform data analysis on the target detection data based on a target analysis strategy to obtain an analysis result associated with the detection behavior, wherein the target analysis strategy is an analysis strategy pre-set based on the recycled electronic device; and an output module, used to output the analysis result associated with the detection behavior.

[0019] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising a memory and a processor; the memory is connected to the processor and is used to store programs; the processor is used to implement the analysis method of detection behavior as described in the first aspect by running the program in the memory.

[0020] According to a fourth aspect of an embodiment of the present application, a storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the analysis method for the detection behavior described in the first aspect is implemented.

[0021] According to the fifth aspect of the embodiments of the present application, a computer program product is provided, which includes a computer program, and the computer program can be stored in a computer-readable storage medium or in the cloud; the processor of the computer device reads the computer program, and when the processor executes the computer program, the steps of the analysis method of the detection behavior described in the first aspect are implemented.

[0022] In an embodiment of the present application, target detection data associated with the detection behavior recorded by the recycled electronic device during the detection and recycling of the electronic device by the first user can be obtained. In addition, instead of relying on the tracking point platform and its original functions, a pre-set target analysis strategy is used to implement data analysis of the target detection data, thereby obtaining analysis results associated with the detection behavior. Finally, the analysis results associated with the detection behavior are output. In a business scenario where the detection data needs to be analyzed and processed, no human participation is required, and while avoiding the instability of the analysis results under manual analysis, the analysis results can be output faster. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this specification. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0024] Figure 1 A flow chart of an analysis method for detecting behavior provided in an embodiment of the present application;

[0025] Figure 2 A schematic diagram of an application architecture of an analysis method for detecting behavior provided in an embodiment of the present application;

[0026] Figure 3 A structural block diagram of an analysis device for detecting behavior provided in an embodiment of the present application;

[0027] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] Unless otherwise defined, the technical terms or scientific terms used in the embodiments of this specification shall have the common meanings understood by persons with ordinary skills in the field to which this specification belongs. The words "first", "second" and similar words used in the embodiments of this specification do not indicate any order, quantity or importance, but are only used to avoid confusion of constituent elements.

[0029] Unless the context requires otherwise, throughout the specification, "plurality" means "at least two", and "including" is interpreted as an open, inclusive meaning, that is, "including, but not limited to". In the description of the specification, the terms "one embodiment", "some embodiments", "exemplary embodiments", "examples", "specific examples" or "some examples" are intended to indicate that a particular feature, structure, material or characteristic associated with the embodiment or example is included in at least one embodiment or example of the specification. The schematic representation of the above terms does not necessarily refer to the same embodiment or example.

[0030] The following will be combined with the drawings in the embodiments of this specification to clearly and completely describe the technical solutions in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this specification.

[0031] Overview

[0032] As described in the background technology, in the scenario of second-hand goods recycling, it is usually necessary to manually inspect the recovered second-hand goods to determine their status and value. For example, the application required for detection can be installed in the second-hand goods. In the process of detecting second-hand goods, the staff follows the prompts of the application. When the detection is completed, the relevant detection data will also be sent to the point-of-sale platform through the point-of-sale method. Finally, the original functions of the point-of-sale platform are used to perform simple processing on the detection data.

[0033] However, existing tracking platforms usually only provide simple filtering and query functions. In the scenario of second-hand goods recycling, it is usually necessary to supervise the detection behavior in order to form a closed loop. In other words, not only the detection data of second-hand goods is required, but also the result data after the analysis of the detection behavior is required, so as to form a complete data chain and form a business closed loop. For this reason, the existing processing method is usually to manually query the detection data in the tracking platform, and then continue to use manual methods to analyze and process the queried detection data. The whole process is not only time-consuming, but also the results of the analysis and processing of the detection data are greatly affected by the professional ability of the personnel and are not stable enough.

[0034] In response to the above problems, this specification provides an analysis method, device, electronic device and storage medium for detection behavior, the purpose of which is to avoid manual analysis in business scenarios where detection data needs to be analyzed and processed, and to output analysis results faster while avoiding the instability of analysis results in manual analysis. Furthermore, in the scenario of second-hand goods recycling, a complete data chain can be formed more conveniently. The specific scheme is described in detail below through embodiments.

[0035] Exemplary Methods

[0036] Taking the application to a server as an example, the present application embodiment exemplifies the analysis method of the detection behavior, wherein the application scope of the analysis method of the detection behavior is not limited to the server, but can also be any other electronic device with data communication and data processing capabilities, which is not limited here. Figure 1 As shown, the analysis method of the detection behavior includes:

[0037] S101: Acquire target detection data.

[0038] In this step, the target detection data includes: data associated with the detection behavior recorded by the recycled electronic device during the detection of the recycled electronic device by the first user. The first user is the user who detects the recycled electronic device, and his identity is not limited. For example, the first user can be a staff member sent by the merchant to provide recycling detection services. The recycled electronic device is any electronic device that the merchant prepares to recycle, for example, the recycled electronic device can be a second-hand mobile phone, a new mobile phone, a second-hand tablet computer, a new tablet computer, etc.

[0039] In some embodiments, during the process of detecting and recycling electronic devices, a designated application may be first installed in the recycled electronic devices. The designated application is used to prompt the first user to perform relevant operations during the process of the first user detecting and recycling the electronic device, and to record and report the data under the relevant operations, that is, the data associated with the detection behavior.

[0040] It is worth noting that the target detection data is used to analyze the detection behavior, and the data associated with the detection behavior is not the same under different analysis dimensions. Therefore, the specific data content of the data associated with the detection behavior is not limited here, as long as it can complete the subsequent corresponding data analysis. The way to report the target detection data of the recycled electronic device is not limited here. For example, it can be reported through Hypertext Transfer Protocol (HTTP) and Message Queue (MQ). In some embodiments, a bottom-up strategy can also be set in the recycled electronic device, and in the case of reporting failure, the detection data that has not been successfully reported can be re-reported using the bottom-up strategy. In order to improve the security of the whole process, in some embodiments, after receiving the data reported by the recycled electronic device, the received data can be screened, and the illegal data can be filtered out, and only the legal data can be retained. Among them, the judgment process of whether the data is legal can be, for example, whether the client that reports the data is an authenticated client, if so, the data is legal, otherwise the data is illegal.

[0041] S102: Perform data analysis on the target detection data based on the target analysis strategy to obtain analysis results associated with the detection behavior.

[0042] In this step, the target analysis strategy is a pre-set analysis strategy based on the recycled electronic device. For example, the analysis strategy can be designed based on the performance or characteristics of the recycled electronic device. It is understandable that factors such as the model and manufacturer of the electronic device usually lead to great differences between the electronic devices. A unified analysis strategy usually cannot take into account the differences between the electronic devices. Therefore, in this embodiment, a unified analysis strategy is not used, but an analysis strategy designed for the recycled electronic device that meets its performance or characteristics.

[0043] When performing data analysis, the detection behavior involved can be analyzed, so that the analysis result associated with the detection behavior can be obtained. The specific content of the analysis result is not limited here.

[0044] S103: Output analysis results associated with the detection behavior.

[0045] In this step, the analysis results may be outputted in any one or more output modes. For example, the analysis results may be outputted to a display device in the form of a report or a chart. For another example, the analysis results may be converted into a voice form by voice technology, and then sent to an audio playback device, and the analysis results may be played by the audio playback device.

[0046] In some embodiments, the analysis results can also be stored in a data lake / database for use by other data analysis platforms or enabled by other data analysis platforms. For example, the analysis results are obtained from the data lake / database using an existing data analysis platform, and the analysis results are processed again. Then the secondary processed results are obtained from the data analysis platform for storage or output. Thus, the functions of the existing data analysis platform are used for empowerment. Among them, the data lake is a data storage architecture that can accommodate a large amount of data of different types and formats, and supports advanced queries and processing for data analysis and machine learning.

[0047] In other embodiments, while storing the analysis results in the data lake / database, the target detection data can also be stored in the data lake / database. Thus, more data analysis can be completed with the help of the data analysis platform while enriching the data lake / database. In other embodiments, the target detection data can also be synchronized to the search engine separately to facilitate the query of the detection data therein.

[0048] In an embodiment of the present application, target detection data associated with the detection behavior recorded by the recycled electronic device during the detection and recycling of the electronic device by the first user can be obtained. In addition, instead of relying on the tracking point platform and its original functions, a pre-set target analysis strategy is used to implement data analysis of the target detection data, thereby obtaining analysis results associated with the detection behavior. Finally, the analysis results associated with the detection behavior are output. In business scenarios where the detection data needs to be analyzed and processed, no human participation is required, and while avoiding the instability of the analysis results under manual analysis, the analysis results can be output faster.

[0049] In some embodiments of the present application, the data associated with the detection behavior recorded by the recycling electronic device includes: behavior data characterizing the detection behavior collected by the recycling electronic device and performance data of the recycling electronic device under the detection behavior;

[0050] Based on the target analysis strategy, the target detection data is analyzed to obtain analysis results associated with the detection behavior, including: based on the target analysis strategy and performance data, the detection behavior represented by the behavior data is analyzed to obtain analysis results representing whether the detection behavior is compliant.

[0051] It should be noted that in the scenario where recycled electronic devices are inspected according to the inspection items, the inspection behavior corresponds to the inspection items. Therefore, the behavior data can be the information of the inspection items. Taking a mobile phone as an example, for example, the inspection item can be an appearance inspection, and correspondingly, the inspection behavior can be an appearance inspection behavior, and the behavior data can be behavior data that characterizes the appearance inspection behavior (such as the operation record generated by clicking to complete the appearance inspection control in the aforementioned specified application). For another example, the inspection item can be a call function inspection, and correspondingly, the inspection behavior can be a call function inspection behavior, and the behavior data can be behavior data that characterizes the call function inspection behavior (such as the operation record generated by the first user dialing a phone number).

[0052] It is understandable that when the first user performs a detection behavior in the recycled electronic device, the recycled electronic device will respond to the detection behavior and perform a certain degree of performance / response, and the data related to the performance / response is the performance data. For example, the performance data can be the response parameters of each sensor or soft and hard functional module in the recycled electronic device under the detection behavior. And the performance data corresponds to the detection behavior one by one. For example, under the above-mentioned appearance detection behavior, the performance data includes: the posture information of the recycled electronic device and the length of stay in each posture. For another example, under the above-mentioned call function detection behavior, the performance data includes: the data generated by the call module in the recycled electronic device, and the data generated by the call module can be used to determine whether the recycled electronic device successfully completes the call, and can also determine information related to the call quality.

[0053] The specific detection behavior can be known through the behavior data, and the specific performance of the recycled electronic equipment under the detection behavior can be known through the performance data. The target analysis strategy includes the judgment criteria for whether the detection behavior is compliant. Therefore, whether the detection behavior is compliant can be analyzed through the behavior data, performance data and target analysis strategy. Continuing with the above-mentioned appearance detection behavior as an example, the target analysis strategy may include: multiple target postures and the target detection duration corresponding to each target posture. In the case of determining that the detection behavior is an appearance detection behavior, it is determined based on the performance data whether each target posture in the target analysis strategy is involved, and whether the detection duration under each target posture has reached the corresponding target detection duration. In the case of determining that the performance data involves all target postures, and the stay time under each target posture is not less than the corresponding target detection duration, the analysis result of the compliance of the appearance detection behavior is obtained, otherwise the analysis result of the non-compliance of the appearance detection behavior is obtained. Similarly, under the above-mentioned call function detection behavior, the analysis result of whether the call function detection behavior is legal can also be obtained, which will not be described in detail here.

[0054] In the embodiment of the present application, when performing data analysis on target detection data, with the help of behavior data and performance data, an analysis result of whether the detection behavior is compliant can be obtained.

[0055] In some embodiments of the present application, obtaining target detection data includes: obtaining behavior data and performance data reported in real time by the recycled electronic device during the detection process;

[0056] Outputting analysis results associated with the detection behavior includes: sending the analysis results to the recycling electronic device when the analysis results indicate that the detection behavior is non-compliant.

[0057] It should be noted that when analyzing whether the detection behavior is compliant, the analysis results can be promptly informed to the tester / first user to facilitate subsequent processing and improve the detection efficiency of recycled electronic devices. For example, when the detection behavior is not compliant, the analysis results are sent to the recycled electronic device, and the first user can promptly learn the specific circumstances of its detection behavior through the recycled electronic device, and then re-test. For another example, when the analysis results indicate that the detection behavior is compliant, the analysis results are sent to the recycled electronic device. The first user can promptly learn the specific circumstances of its detection behavior through the recycled electronic device, and then continue with the next test or end the test.

[0058] In order to avoid the first user having to wait too long for the analysis result, in some embodiments, the recycled electronic device sends the behavior data and performance data to the server in real time. In addition, the server processes the received data in real time, that is, processes the obtained data in real time, and sends the analysis result to the recycled electronic device in real time.

[0059] In the embodiment of the present application, the detection behavior can be analyzed in real time, and the first user can be notified in time when the detection behavior is not compliant, thereby improving the detection efficiency.

[0060] In order to reduce the adverse effects caused by non-compliant detection behavior, in some embodiments of the present application, the data associated with the detection behavior recorded by the recycled electronic device further includes: identity information of the first user; after obtaining the analysis result indicating whether the detection behavior is compliant, the method further includes:

[0061] If the analysis result indicates that the detection behavior is non-compliant and the cumulative number of non-compliant detection behaviors of the first user is greater than the number threshold, the electronic account indicated by the identity information is blocked or a reminder message is sent to the second user associated with the identity information.

[0062] It should be noted that the first user can be a provider of electronic equipment testing services provided by the merchant, and will continuously test the recycled electronic equipment during work. In some embodiments, the analysis results of each work process of the first user can be recorded, or only the cumulative number of non-compliant detection behaviors can be recorded. The cumulative number of non-compliant detection behaviors can then be used as an indicator to measure the testing services provided by the first user. It is understandable that in the case of non-compliant detection behaviors, the quality inspection information of the electronic equipment being tested / recycled electronic equipment may be false. If this happens too many times, it will seriously affect the related services provided by the merchant, thereby causing adverse effects.

[0063] To this end, it is necessary to intervene even after the cumulative number of non-compliant detection behaviors reaches a certain threshold value to avoid subsequent adverse effects. For example, the electronic account of the relevant user can be banned or the person in charge of the relevant user can be notified to borrow in time. In an embodiment of the present application, when the cumulative number of non-compliant detection behaviors of the first user is greater than the number threshold, the electronic account of the first user will be banned. Among them, the electronic account is an account that belongs exclusively to the first user and is used for the first user to carry out detection business. A reminder message can also be sent to the relevant responsible person of the first user, wherein the relevant responsible person can be, for example, the leader of the first user or the person in charge of this business. The number threshold is a pre-set empirical value. If the cumulative number of non-compliant detection behaviors of a certain user is less than or equal to the number threshold, it can be regarded that the behavior of the user will not cause adverse effects. If the cumulative number of non-compliant detection behaviors of a certain user is greater than the number threshold, it can be regarded that the behavior of the user will cause adverse effects.

[0064] In the embodiment of the present application, it is possible to avoid the cumulative number of non-compliant detection behaviors being too large, thereby reducing the adverse effects caused by the non-compliant detection behaviors.

[0065] In order to enrich the categories of electronic devices targeted by the detection behavior, in some embodiments of the present application, the target detection data also includes: device information of the recovered electronic device; before performing data analysis on the target detection data based on the target analysis strategy to obtain the analysis result associated with the detection behavior, the method also includes:

[0066] Based on the device information of the recycled electronic device, a target analysis strategy for recycling the electronic device corresponding to the strategy library is determined; wherein the strategy library is provided with a plurality of analysis strategies, and each analysis strategy corresponds to a different electronic device.

[0067] It should be noted that the device information of the recycled electronic device includes the device type, manufacturer and software related information. Taking a mobile phone as an example, for example, the device information may include: mobile phone model, manufacturer, operating system and other information. It is understandable that factors such as the model and manufacturer of the electronic device usually lead to great differences between the electronic devices. A unified analysis strategy usually cannot take into account the differences between the electronic devices. Therefore, in this embodiment, a unified analysis strategy is not used, but an analysis strategy designed for each / each electronic device that conforms to its performance or characteristics. For example, different analysis strategies are set for mobile phones of different models and different operating systems, so that multiple analysis strategies can form a strategy library. After determining the device information of the recycled electronic device, for example, according to the model and operating system, the corresponding analysis strategy can be located, and then the data analysis is roughly completed using the located analysis. In some embodiments, the target detection data may also include other information in addition to the above data, for example, it may also include the time when the detection behavior occurs, but is not limited to this.

[0068] In the embodiment of the present application, a strategy library consisting of multiple analysis strategies may be provided, wherein each analysis strategy corresponds to a different electronic device, thereby enriching the categories of electronic devices targeted by the detection behavior.

[0069] In some embodiments of the present application, obtaining target detection data includes:

[0070] Receive target detection data in a unified data format reported by multiple clients through embedded points, where the multiple clients include clients under different operating systems.

[0071] It should be noted that the tracking point can also be called event tracking, which can refer to the relevant technologies and implementation processes for capturing, processing and sending specific user behaviors or events within websites, applications, and applets. In the process of collecting data using traditional tracking point technology, differentiated settings are usually made based on different operating systems, so that the data reporting process is more in line with the original mechanism of the operating system. In this way, the data formats reported by clients under different operating systems are different. Similarly, even in clients under the same operating system, the reported data formats are usually differentiated due to different specific business scenarios, so that the data formats reported by clients under different business scenarios are different. Correspondingly, the existing tracking point platform usually accommodates the log tracking point data of all clients, and provides a kind of operation log retention with the ability to handle large amounts of data.

[0072] Since the data reporting adopts different data formats, it is difficult to use a unified parsing method to process the reported data, which leads to the need to set up multiple parsing methods, and will cause the data of each client to be too fragmented. To this end, the clients under different operating systems in the embodiment of the present application will use a unified data format to package and report the reported data. Therefore, when parsing the corresponding data, it is only necessary to use a unified parsing method, without setting up multiple parsing methods, and avoiding the problem of too fragmented data of each client. Among them, the clients under different operating systems include: clients under the Android operating system, clients under the Apple operating system, clients under the Hongmeng operating system, and multiple clients under the computer operating system.

[0073] In some embodiments, target detection data can also be obtained by using aspect interception. Aspect-Oriented Interception is a core concept of aspect-oriented programming (AOP). AOP is a programming paradigm that aims to improve modularity by separating cross-cutting concerns from business logic, which will not be described in detail here.

[0074] In the embodiment of the present application, clients under different operating systems will use a unified data format to package and report the buried data. Therefore, when parsing the corresponding data, only a unified parsing method is needed, without setting multiple parsing methods, and the problem of too scattered data of each client is avoided.

[0075] In order to avoid the problem of long response time caused by excessive data volume in the database, in some embodiments of the present application, after acquiring the target detection data, the method further includes:

[0076] The target detection data is stored in a first database and a second database respectively, wherein the first database retains the data for a longer period than the second database retains the data.

[0077] It should be noted that the data in the first database and the second database can be deleted manually or automatically after being stored for a certain period of time. The certain period of time is the period of time for retaining the data. For example, after the data is stored in the first database, the storage period of the data can be monitored. When it is monitored that the storage period reaches a target period of time, this part of the data is automatically cleared. This can avoid the excessive amount of data in the first database to a certain extent. In some embodiments, the first database is a full database for storing all detection data. The second database is a hot database for storing detection data within a recent period of time, such as storing detection data within the past month. When querying detection data within the past month, you only need to query in the second database. Compared with querying detection data from the first database, it is undoubtedly possible to get a faster response.

[0078] In the embodiment of the present application, the horizontally scalable first database and the second database are used to store the detection data respectively, which can solve the bottleneck problem of data storage in the medium and long term, and at the same time avoid the problem of long response time when querying recent detection data.

[0079] For ease of understanding, the following takes the detection of second-hand electronic devices as an example to illustrate the analysis method of the detection behavior provided in this embodiment. First, data modeling can be done for the actions of the assembly line detection process to clarify the data standards for the buried data. The buried data uses a unified data format, for example, it can be: business public participant + actor + behavior + time + operating environment information (for example: various sensors on mobile phones). Then formulate a complete mechanism for buried data reporting. For example, it can be: scene triggering, standard data extraction, data reporting, bottom-up retry, data coarse screening, data storage, big data synchronization, and data analysis. The application architecture of this method can be as follows Figure 2 As shown, it includes: view layer, application layer, data layer and data lake.

[0080] The main content of the data layer: The clients under each operating system report the detection data in a unified format through the tracking technology. Among them, each client can Figure 2Android APP, iOS APP, Hongmeng APP, notebook client, etc. in. For example, after opening the client, the staff detects the recycling process of the corresponding electronic device. During the detection process, relevant detection data will be reported. Among them, for the detection data, please refer to the target detection data in the above embodiments, which will not be repeated here. The buried point gateway will filter the received data and filter out the detection data with incorrect data format (whether it is a unified data format for buried points). Only the detection data with correct data format is stored in the data center. Here, two databases can be extended in the data center, one of which is used to store the full amount of detection data. The other database only stores the detection data in the most recent period of time. Furthermore, the detection data can also be synchronized to the search engine. For example, the detection data is synchronized to the search engine through an asynchronous synchronization mechanism to provide the underlying data operation capabilities for subsequent multi-scenario complex data queries.

[0081] Regarding the main content of the application layer: The application layer is equipped with a policy center and a standard center, wherein the policy center includes a plurality of different analysis strategies, which is equivalent to the policy library in the above embodiment and will not be repeated here. The standard center includes the compliance standards for each detection behavior. After the detection data is transmitted from the data center to the application layer, the compliance of the detection behavior is judged based on the corresponding analysis strategy and standard. And the judgment result is stored in the policy center of the data layer.

[0082] The main content about the data lake: This data lake is equivalent to the data lake in the above embodiment. Here, the detection data of the data center and the judgment results of the policy center are synchronized to the data lake as data of different dimensions, so as to facilitate the use of other data analysis platforms. Other data analysis platforms can be used for empowerment.

[0083] The main content of the view layer: As a layer directly facing users, it can display relevant data before and during the entire detection behavior analysis process. For example, business scenarios related to point-of-sale can be displayed through business scenario applications. Another example is to display big data reports related to the detection process, such as sorting the data reported by each node of the detection pipeline according to the time point, and obtaining a point-of-sale data report for the entire life cycle of the pipeline detection of a second-hand product. For another example, personalized aggregate queries in multiple dimensions can be provided, query results can be displayed, query results can be exported, and query results can be further analyzed.

[0084] In the embodiments of the present application, a set of point-of-sale solutions based on pipeline detection is abstractly designed to ensure the structure, atomicity, objectivity and scalability of the point-of-sale data, and at the same time, a unified data standard is abstracted to build a set of point-of-sale data solutions that can cover the pipeline detection of second-hand goods. Furthermore, the point-of-sale reporting mechanism is clarified to form a complete solution including point-of-sale trigger points, reporting methods, reporting formats, asynchronous backup, etc., while solving the mid- and long-term bottleneck problems of data storage. Furthermore, a multi-dimensional data analysis capability is constructed, from the real-time analysis and recording of the initial reporting point of the point-of-sale data to the data processing, data backup, data mining, and data display based on the big data system, forming a complete and multi-dimensional data analysis system.

[0085] Exemplary Devices

[0086] In the embodiment of the present application, a detection behavior analysis device is also provided, such as Figure 3 As shown, the analysis device for detecting behavior includes:

[0087] The acquisition module 31 is used to acquire target detection data, wherein the target detection data includes: data associated with the detection behavior recorded by the recycling electronic device during the detection of the recycling electronic device by the first user;

[0088] An analysis module 32, configured to perform data analysis on the target detection data based on a target analysis strategy to obtain an analysis result associated with the detection behavior, wherein the target analysis strategy is a pre-set analysis strategy based on the recycled electronic device;

[0089] The output module 33 is used to output the analysis results associated with the detection behavior.

[0090] In an optional embodiment, the data associated with the detection behavior recorded by the recycling electronic device includes: behavior data characterizing the detection behavior collected by the recycling electronic device and performance data of the recycling electronic device under the detection behavior;

[0091] The analysis module 32 is specifically used to analyze the detection behavior represented by the behavior data based on the target analysis strategy and the performance data, and obtain an analysis result representing whether the detection behavior is compliant.

[0092] In an optional embodiment, the acquisition module 31 is specifically used to acquire the behavior data and performance data reported in real time by the recycled electronic device during the detection process;

[0093] The output module 33 is specifically configured to send the analysis result to the recycling electronic device when the analysis result indicates that the detection behavior is not in compliance.

[0094] In an optional implementation, the behavior data includes: behavior data characterizing appearance detection behavior; the performance data includes: posture information of the recovered electronic device and the duration of stay in each posture.

[0095] In an optional embodiment, the data associated with the detection behavior recorded by the recycled electronic device further includes: identity information of the first user;

[0096] The device also includes: a processing module, which is used to ban the electronic account indicated by the identity information or send a reminder message to the second user associated with the identity information when the analysis result indicates that the detection behavior is non-compliant and the cumulative number of non-compliant detection behaviors of the first user is greater than a number threshold.

[0097] In an optional embodiment, the target detection data further includes: device information of the recycled electronic device;

[0098] The device also includes a strategy module, which is used to determine a target analysis strategy for recycling electronic devices corresponding to a strategy library based on device information of the recycled electronic devices; wherein the strategy library is provided with a plurality of analysis strategies, and each analysis strategy corresponds to a different electronic device.

[0099] In an optional implementation, the acquisition module 31 is specifically used to receive target detection data in a unified data format reported by multiple clients through embedding points, wherein the multiple clients include clients under different operating systems.

[0100] In an optional embodiment, the device further includes: a storage module, configured to store the target detection data in the first database and the second database respectively, wherein the time length for which the first database retains the data is longer than the time length for which the second database retains the data.

[0101] For the specific definition of the analysis device for detecting behavior, please refer to the definition of the analysis method for detecting behavior above, which will not be repeated here. Each module in the above-mentioned analysis device for detecting behavior can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0102] Exemplary Electronic Devices

[0103] Another embodiment of the present application also provides an electronic device, see Figure 4As shown, an exemplary embodiment of the present specification also provides an electronic device, including: a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the vehicle control method according to various embodiments of the present specification described in the above embodiments of the present specification are executed.

[0104] The internal structure of the electronic device can be as follows Figure 4 As shown, the electronic device includes a processor, a memory, a network interface and an input device connected via a system bus. The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the electronic device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the steps of the vehicle control method according to various embodiments of the present specification are described in the above embodiments of the present specification.

[0105] The processor may include a main processor and may also include a baseband chip, a modem, etc.

[0106] The memory stores a program for executing the technical solution of the present invention, and may also store an operating system and other key services. Specifically, the program may include a program code, and the program code includes computer operation instructions. More specifically, the memory may include a read-only memory (ROM), other types of static storage devices that can store static information and instructions, a random access memory (RAM), other types of dynamic storage devices that can store information and instructions, a disk storage, a flash, and the like.

[0107] The processor may be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the program of the scheme of the present invention. It may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component.

[0108] The input device may include a device for receiving data and information input by a user, such as a keyboard, a mouse, a camera, a scanner, a light pen, a voice input device, a touch screen, a pedometer, or a gravity sensor.

[0109] Output devices may include means that allow information to be output to a user, such as display screens, printers, speakers, etc.

[0110] The communication interface may include using any transceiver or the like to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0111] The processor executes the program stored in the memory and calls other devices, which can be used to implement each step of any vehicle control method provided in the above embodiments of the present application.

[0112] The electronic device may also include a display component and a voice component. The display component may be a liquid crystal display or an electronic ink display. The input device of the electronic device may be a touch layer covered on the display component, or a button, trackball or touchpad provided on the housing of the electronic device, or an external keyboard, touchpad or mouse.

[0113] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the scheme of this specification, and does not constitute a limitation on the electronic device to which the scheme of this specification is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0114] Exemplary computer program products and storage media

[0115] In addition to the above methods and devices, the analysis method for detecting behavior provided in the embodiments of this specification can also be a computer program product, which includes a computer program, which, when executed by a processor, enables the processor to perform the steps in the analysis method for detecting behavior according to various embodiments of this specification described in the above "Exemplary Method" section of this specification. The computer program can be stored in a computer-readable storage medium or in the cloud.

[0116] The computer program product may be written in any combination of one or more programming languages ​​to write program code for performing the operations of the embodiments of the present specification, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0117] In addition, an embodiment of the present specification also provides a computer-readable storage medium on which a computer program is stored, and the computer program is executed by a processor to execute the steps of the analysis method of detection behavior according to various embodiments of the present specification described in the above "Exemplary Method" section of the present specification.

[0118] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this specification can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0119] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0120] The above-mentioned embodiments only express several implementation methods of this specification, and the descriptions are relatively specific and detailed, but they cannot be understood as limiting the scope of the solutions provided by the embodiments of this specification. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of this specification, which all belong to the protection scope of this specification. Therefore, the protection scope of the patent of this specification shall be based on the attached claims.

Claims

1. A method for analyzing detection behavior, characterized in that: The method comprises: Acquiring target detection data, wherein the target detection data includes: data associated with detection behavior recorded by the recycling electronic device during the process of the first user detecting the recycling electronic device; Performing data analysis on the target detection data based on a target analysis strategy to obtain an analysis result associated with the detection behavior, wherein the target analysis strategy is an analysis strategy pre-set based on the recycled electronic device; Outputting analysis results associated with the detection behavior.

2. The method according to claim 1, characterized in that The data associated with the detection behavior recorded by the recycled electronic device includes: Behavior data representing the detection behavior collected by the recycled electronic device and performance data of the recycled electronic device under the detection behavior; Performing data analysis on the target detection data based on the target analysis strategy to obtain analysis results associated with the detection behavior, including: The detection behavior represented by the behavior data is analyzed based on the target analysis strategy and the performance data to obtain an analysis result representing whether the detection behavior is compliant.

3. The method according to claim 2, characterized in that Obtain target detection data, including: Acquire the behavior data and the performance data reported in real time by the recycled electronic device during the detection process; Output analysis results associated with the detection behavior, including: In the case where the analysis result indicates that the detection behavior is non-compliant, the analysis result is sent to the recycled electronic device.

4. The method according to claim 2, characterized in that: The behavior data includes: behavior data characterizing appearance detection behavior; the performance data includes: posture information of the recycled electronic device and the duration of stay in each posture.

5. The method according to claim 2, characterized in that: The data associated with the detection behavior recorded by the recycled electronic device also includes: identity information of the first user; After obtaining the analysis result indicating whether the detection behavior is compliant, the method further includes: When the analysis result indicates that the detection behavior is non-compliant and the cumulative number of non-compliant detection behaviors of the first user is greater than a number threshold, the electronic account indicated by the identity information is banned or a reminder message is sent to a second user associated with the identity information.

6. The method according to claim 1, characterized in that The target detection data also includes: equipment information of the recycled electronic equipment; Before performing data analysis on the target detection data based on the target analysis strategy to obtain an analysis result associated with the detection behavior, the method further includes: Based on the device information of the recycled electronic device, determining a target analysis strategy of the recycled electronic device corresponding to the strategy library; Therein, a plurality of analysis strategies are arranged in the strategy library, and each analysis strategy corresponds to a different electronic device.

7. The method according to claim 1, characterized in that Obtain target detection data, including: Receive target detection data in a unified data format reported by multiple clients through embedded points, wherein the multiple clients include clients under different operating systems.

8. The method according to claim 1, characterized in that After acquiring the target detection data, the method further includes: The target detection data is stored in a first database and a second database respectively, wherein the first database retains the data for a longer period than the second database retains the data.

9. An analysis device for detecting behavior, characterized in that: The device comprises: An acquisition module, configured to acquire target detection data, wherein the target detection data includes: data associated with detection behavior recorded by the recycling electronic device during the detection of the recycling electronic device by the first user; An analysis module, configured to perform data analysis on the target detection data based on a target analysis strategy to obtain an analysis result associated with the detection behavior, wherein the target analysis strategy is a pre-set analysis strategy based on the recycled electronic device; An output module is used to output analysis results associated with the detection behavior.

10. An electronic device, characterized in that: including memory and processor; The memory is connected to the processor and is used to store programs; The processor is used to implement the analysis method of detection behavior as described in any one of claims 1 to 8 by running the program in the memory.

11. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the method for analyzing the detection behavior according to any one of claims 1 to 8 is implemented.

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