CN113841175A

CN113841175A - Data analysis method and related product

Info

Publication number: CN113841175A
Application number: CN201980096567.4A
Authority: CN
Inventors: 安琪
Original assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd; Shenzhen Huantai Technology Co Ltd
Current assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd; Shenzhen Huantai Technology Co Ltd
Priority date: 2019-07-05
Filing date: 2019-07-05
Publication date: 2021-12-24
Anticipated expiration: 2039-07-05
Also published as: WO2021003608A1; CN113841175B

Abstract

The embodiment of the application discloses a data analysis method and a related product, wherein the method comprises the following steps: acquiring first use data of first electronic equipment; acquiring second use data of the second electronic device, wherein the first electronic device and the second electronic device correspond to the same target user ID, the first electronic device is a currently used electronic device, and the second electronic device is a previously used electronic device; comparing the first usage data with the second usage data to obtain a target comparison result; and determining the reason for changing the machine of the target according to the target comparison result. By adopting the embodiment of the application, the reason for changing the machine of the user can be analyzed, so that data support is provided for equipment updating research and development.

Description

Data analysis method and related product

Technical Field

The present application relates to the field of communications technologies, and in particular, to a data analysis method and a related product.

Background

With the widespread use of electronic devices (such as mobile phones, tablet computers, etc.), the electronic devices have more and more applications and more powerful functions, and the electronic devices are developed towards diversification and personalization, and become indispensable electronic products in the life of users.

At present, electronic equipment beauty has become an indispensable part of user life, and it is a very common thing to change electronic equipment, but the reason why the user changed electronic equipment cannot be known in the background, so that the support of data cannot be provided for the later equipment updating and research of equipment manufacturers.

Disclosure of Invention

The embodiment of the application provides a data analysis method and a related product, which can be used for analyzing the reason for changing a machine by a user so as to provide data support for equipment updating research and development.

In a first aspect, an embodiment of the present application provides a data analysis method, including:

acquiring first use data of first electronic equipment;

acquiring second use data of the second electronic device, wherein the first electronic device and the second electronic device correspond to the same target user ID, the first electronic device is a currently used electronic device, and the second electronic device is a previously used electronic device;

comparing the first usage data with the second usage data to obtain a target comparison result;

and determining the reason for changing the machine of the target according to the target comparison result.

In a second aspect, an embodiment of the present application provides a data analysis apparatus, including:

a first acquisition unit configured to acquire first usage data of a first electronic device;

a second obtaining unit, configured to obtain second usage data of the second electronic device, where the first electronic device and the second electronic device correspond to a same target user ID, the first electronic device is a currently used electronic device, and the second electronic device is a previously used electronic device;

the comparison unit is used for comparing the first use data with the second use data to obtain a target comparison result;

and the determining unit is used for determining the reason for changing the target according to the target comparison result.

In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program enables a computer to perform some or all of the steps described in the first aspect of the embodiment of the present application.

In a fifth aspect, embodiments of the present application provide a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, where the computer program is operable to cause a computer to perform some or all of the steps as described in the first aspect of the embodiments of the present application. The computer program product may be a software installation package.

Drawings

Reference will now be made in brief to the drawings that are needed in describing embodiments or prior art.

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1A is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;

FIG. 1B is a schematic flow chart diagram of a data analysis method disclosed in an embodiment of the present application;

FIG. 1C is a schematic illustration of an exemplary demonstration of natural person ID determination as disclosed in an embodiment of the present application;

FIG. 1D is a schematic diagram illustrating a user portrait configuration according to an embodiment of the present disclosure;

FIG. 2 is a schematic flow chart diagram of another data analysis method disclosed in embodiments of the present application;

FIG. 3 is a schematic flow chart diagram of another data analysis method disclosed in embodiments of the present application;

fig. 4 is a schematic structural diagram of another electronic device disclosed in the embodiments of the present application;

fig. 5A is a schematic structural diagram of a data analysis apparatus disclosed in an embodiment of the present application;

FIG. 5B is a schematic structural diagram of another data analysis apparatus disclosed in the embodiments of the present application;

fig. 5C is a schematic structural diagram of another data analysis apparatus disclosed in the embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

The electronic device related to the embodiment of the present application, whether the electronic device is a first electronic device or a second electronic device, may include various handheld devices, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem, and various forms of User Equipment (UE), a Mobile Station (MS), smart home devices (smart tv, smart air conditioner, smart range hood, smart fan, smart wheelchair, smart dining table, etc.), and the like. For convenience of description, the above-mentioned devices are collectively referred to as electronic devices, and the electronic devices may also be servers, service platforms, and the like.

The following describes embodiments of the present application in detail.

Referring to fig. 1A, fig. 1A is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application, and the electronic device 100 may include a control circuit, which may include a storage and processing circuit 110. The storage and processing circuitry 110 may be a memory, such as a hard drive memory, a non-volatile memory (e.g., flash memory or other electronically programmable read-only memory used to form a solid state drive, etc.), a volatile memory (e.g., static or dynamic random access memory, etc.), etc., and the embodiments of the present application are not limited thereto. Processing circuitry in storage and processing circuitry 110 may be used to control the operation of electronic device 100. The processing circuit may be implemented based on one or more microprocessors, microcontrollers, baseband processors, power management units, audio codec chips, application specific integrated circuits, display driver integrated circuits, and the like.

The storage and processing circuitry 110 may be used to run software in the electronic device 100, such as an internet browsing application, a Voice Over Internet Protocol (VOIP) telephone call application, an email application, a media playing application, operating system functions, and so forth. Such software may be used to perform control operations such as, for example, camera-based image capture, ambient light measurement based on an ambient light sensor, proximity sensor measurement based on a proximity sensor, information display functionality based on status indicators such as status indicator lights of light emitting diodes, touch event detection based on a touch sensor, functionality associated with displaying information on multiple (e.g., layered) displays, operations associated with performing wireless communication functions, operations associated with collecting and generating audio signals, control operations associated with collecting and processing button press event data, and other functions in the electronic device 100, and the like, without limitation of embodiments of the present application.

The electronic device 100 may also include input-output circuitry 150. The input-output circuit 150 may be used to enable the electronic device 100 to input and output data, i.e., to allow the electronic device 100 to receive data from an external device and also to allow the electronic device 100 to output data from the electronic device 100 to the external device. The input-output circuit 150 may further include a sensor 170. The sensors 170 may include ambient light sensors, proximity sensors based on light and capacitance, touch sensors (e.g., based on optical touch sensors and/or capacitive touch sensors, where the touch sensors may be part of a touch display screen or used independently as a touch sensor structure), acceleration sensors, gravity sensors, and other sensors, among others.

Input-output circuitry 150 may also include one or more displays, such as display 130. Display 130 may include one or a combination of liquid crystal displays, organic light emitting diode displays, electronic ink displays, plasma displays, displays using other display technologies. Display 130 may include an array of touch sensors (i.e., display 130 may be a touch display screen). The touch sensor may be a capacitive touch sensor formed by a transparent touch sensor electrode (e.g., an Indium Tin Oxide (ITO) electrode) array, or may be a touch sensor formed using other touch technologies, such as acoustic wave touch, pressure sensitive touch, resistive touch, optical touch, and the like, and the embodiments of the present application are not limited thereto.

The audio component 140 may be used to provide audio input and output functionality for the electronic device 100. The audio components 140 in the electronic device 100 may include a speaker, a microphone, a buzzer, a tone generator, and other components for generating and detecting sound.

The communication circuit 120 may be used to provide the electronic device 100 with the capability to communicate with external devices. The communication circuit 120 may include analog and digital input-output interface circuits, and wireless communication circuits based on radio frequency signals and/or optical signals. The wireless communication circuitry in communication circuitry 120 may include radio-frequency transceiver circuitry, power amplifier circuitry, low noise amplifiers, switches, filters, and antennas. For example, the wireless communication circuitry in communication circuitry 120 may include circuitry to support Near Field Communication (NFC) by transmitting and receiving near field coupled electromagnetic signals. For example, the communication circuit 120 may include a near field communication antenna and a near field communication transceiver. The communications circuitry 120 may also include a cellular telephone transceiver and antenna, a wireless local area network transceiver circuitry and antenna, and so forth.

The electronic device 100 may further include a battery, power management circuitry, and other input-output units 160. The input-output unit 160 may include buttons, joysticks, click wheels, scroll wheels, touch pads, keypads, keyboards, cameras, light emitting diodes and other status indicators, and the like.

A user may input commands through input-output circuitry 150 to control the operation of electronic device 100, and may use output data of input-output circuitry 150 to enable receipt of status information and other outputs from electronic device 100.

Referring to fig. 1B, fig. 1B is a schematic flow chart of a data analysis method according to an embodiment of the present disclosure, where the data transmission method described in the embodiment is applied to the electronic device or the server shown in fig. 1A, and the data analysis method includes:

101. first usage data of a first electronic device is acquired.

The first electronic device may be an electronic device after the switch is switched, the current first usage data may be understood as data used by the first electronic device for a period of time, and the first usage data may be usage data from at least one application in the first electronic device, in this embodiment of the present application, the at least one application may be a third-party application or a system application, and the usage data may include at least one of: registering application data, application cache data, or instant messaging data, etc., which are not limited herein, for example, the application data may include: the first usage data may also be at least one of the following user IDs, such as a cookie of the user, an APP end browsing behavior identification ID, and an account ID, and the like: CPU working frequency, CPU core number, CPU working mode, GPU frame rate, GPU resolution, device brightness, device sound, partial parameters or all parameters in memory parameters. The user ID of the user ID may be a device hardware ID or a character identifier. The first electronic device may correspond to a target object, i.e., an owner.

Certainly, the first electronic device may be used by multiple persons, a multi-dimensional feature layer and an ID-mapping relation layer may be constructed by integrating the IMEI, the SSOID, the openid, the user location data, the internet behavior data, and the like of the devices, and the accurate identification of the natural person is completed by using a multi-code relation trusted identification filtering algorithm and a graph communication algorithm in a natural person identification layer, so that the owner of the electronic device can be accurately identified, and the owner of the electronic device is still used by the owner of the electronic device most of the time after all.

In one possible example, the step 101 of acquiring the first usage data of the first electronic device may include the following steps:

11. acquiring a user ID of the first electronic equipment;

12. and determining target application data of the first electronic equipment in a specified time period according to the user ID, and taking the target application data as the first usage data.

The specified time period can be set by the user or defaulted by the system, and the specified time period can be understood as a time period of the most recent use of the electronic device. In this embodiment, the user ID may be at least one of the following: a phone number, an Integrated Circuit Card Identity (ICCID), an International Mobile Equipment Identity (IMEI), a Single Sign On ID (SSOID), an ID of a third-party application, an openid, and the like, which are not limited herein.

Further, the electronic device may obtain a user ID of the first electronic device, and further, may determine target application data of the first electronic device in a specified time period according to the user ID, and use the target application data as the first usage data.

In one possible example, when the target user ID is a natural person ID, before step 101, the following steps may be further included:

a1, acquiring historical use data of the first electronic equipment;

a2, constructing a multi-dimensional feature layer and an ID-mapping relation layer according to the historical use data;

a3, determining the natural person ID according to the multi-dimensional feature layer and the ID-mapping relation layer.

In this embodiment, the historical usage data may be understood as usage data corresponding to a user from a first time of using the electronic device to a current time, or all usage data corresponding to at least one user ID of the target object, where the historical usage data may be from at least one application, and in this embodiment, the at least one application may be a third-party application or a system application, and the usage data may include at least one of: registering application data, application cache data, or instant messaging data, etc., which are not limited herein, for example, the application data may include: the user ID of the user identity such as cookie, APP end browsing behavior identification ID, and account ID, the usage data may also be at least one of the following: CPU working frequency, CPU core number, CPU working mode, GPU frame rate, GPU resolution, device brightness, device sound, partial parameters or all parameters in memory parameters. The user ID of the user ID may be a device hardware ID or a character identifier.

In a specific implementation, as shown in fig. 1C, the electronic device may obtain historical usage data of the first electronic device, where the historical usage data may be obtained from a data source, and the data source may include at least one of: browsers, software stores, account systems, grand data, shopping data, communication data, gaming data, social data, office data, smart home data, and the like, are not limited thereto. ID-MAPPing relationship layer data may be obtained from the historical usage data, and may include at least one of: OSSID < - > IMEI (mapping relationship between OSSID and IMEI), TEL < - > IMEI, OppenId < - > ICCID, etc., which are not limited herein, and multidimensional feature layer data can be obtained according to historical usage data, and the multidimensional feature layer data can include at least one of the following: device features, APP features, location features, and the like, without limitation, each of the natural person IDs may correspond to a user representation according to the multidimensional feature layer and the ID-mapping relationship layer, as shown in fig. 1D, and the user representation may include at least one of the following: demographic attributes, geographic relationships, hobbies, equipment attributes, asset conditions, business interests, etc., without limitation.

Additionally, the device features may include at least one of: the device attributes (e.g., device daily dotting, model configuration, activation date, etc.), network connection conditions (e.g., WIFI connection, network IP, base station, connectivity distribution, etc.), ID attributes (e.g., ID format, character length, etc.), etc., which are not limited herein. APP features may include at least one of: APP installation, start-up, uninstallation, APP type preferences (e.g., games, applications), APP periods of constant activity (weekdays, holidays, etc.), and the like, without limitation, the positioning features may include at least one of: location attributes (e.g., home or business, resident business, frequent), travel preferences (e.g., mode of travel, time of travel, frequency of travel, trajectory of travel, etc.), POI preferences (POI arrival, POI search).

102. And acquiring second use data of the second electronic equipment, wherein the first electronic equipment and the second electronic equipment correspond to the same target user ID, the first electronic equipment is currently used electronic equipment, and the second electronic equipment is previously used electronic equipment.

The second electronic device may be an electronic device before the machine is changed, the second usage data may be partial or all usage data in the second electronic device, of course, the second usage data may also be stored in a cloud server, the second usage data may be understood as data used by the second electronic device for a period of time, and the second usage data may be usage data of at least one application in the second electronic device, in this embodiment of the present application, the at least one application may be a third-party application or a system application, and the usage data may include at least one of the following: registering application data, application cache data, or instant messaging data, etc., which are not limited herein, for example, the application data may include: the second usage data may also be at least one of the following user IDs, such as a cookie of the user, an APP end browsing behavior identification ID, and an account ID, and the like: CPU working frequency, CPU core number, CPU working mode, GPU frame rate, GPU resolution, device brightness, device sound, partial parameters or all parameters in memory parameters. The user ID of the user ID may be a device hardware ID or a character identifier. The second electronic device may correspond to a target object, i.e., an owner.

In one possible example, the step 102 of obtaining the second usage data of the second electronic device may include the following steps:

21. obtaining source identification information of a data source corresponding to the first use data to obtain at least one source identification information;

22. and acquiring second use data of the second electronic equipment according to the at least one source identification information.

The source identification information may be used to mark a data source, and the identification data source may be at least one of the following: application name, application version number, application location, etc., without limitation. In a specific implementation, the source identification information of the data source corresponding to the first usage data may be obtained to obtain at least one source identification information, and further, the second usage data of the second electronic device may be obtained from the cloud server or a memory of the second electronic device according to the at least one source identification information.

Further, in a possible example, the step 22 of obtaining the second usage data of the second electronic device according to the at least one source identification information may include the following steps:

221. acquiring original use data of the second electronic equipment in a preset time period according to the at least one source identification information;

222. and screening out the use data corresponding to the target user ID from the original use data to obtain the second use data.

The preset time period can be set by the user or defaulted by the system. Because the second electronic device is not only used by the target object, but also used by another person, in a specific implementation, the original usage data of the second electronic device in a preset time period can be obtained according to at least one source identification information, and the usage data corresponding to the target user ID is screened from the original usage data to obtain the second usage data.

103. And comparing the first use data with the second use data to obtain a target comparison result.

The first using data reflect the current performance of the electronic equipment and the using habits of users to a certain extent, the second using data reflect the historical performance of the electronic equipment and the using habits of users to a certain extent, the first using data and the second using data are compared to obtain a target comparison result, and the target comparison result reflects the performance change of the electronic equipment and the requirement change of the users to a certain extent.

In one possible example, when the first usage data includes a plurality of first application data for a plurality of applications, wherein each application corresponds to a first application data; in the step 103, comparing the first usage data with the second usage data to obtain a target comparison result, the method may include the following steps:

31. determining a plurality of second application data corresponding to the plurality of applications from the second usage data, wherein each application corresponds to one second application data;

32. comparing the plurality of first application data with the plurality of second application data to obtain a plurality of comparison values;

33. determining a weight value corresponding to each application in the plurality of applications to obtain a plurality of weight values;

34. and carrying out weighting operation on the comparison values and the weight values to obtain the target comparison result.

In this embodiment, when the first usage data may include a plurality of first application data of a plurality of applications, each application corresponds to one first application data, in a specific implementation, a plurality of second application data corresponding to the plurality of applications may be determined from the second usage data, each application corresponds to one second application data, and then, the plurality of first application data may be compared with the plurality of second application data.

Specifically, feature extraction may be performed on each of the first application data in the plurality of first application data to obtain a plurality of first parameter feature sets, and feature extraction may be performed on each of the second application data in the plurality of second application data to obtain a plurality of second parameter feature sets, where each of the first parameter feature set and the second parameter feature set may include at least one of the following features: user grade, integral consumption, activity, preference type, online time, operation habit, communication times, communication time, user ID and the like, which are not limited herein, and further, the plurality of first parameter feature sets and the plurality of second parameter feature sets may be compared based on a preset algorithm to obtain a plurality of comparison values, where the preset algorithm may be: local-Sensitive Hashing (LSH), a two-sequence local alignment algorithm, SSIM, and the like, without limitation. Of course, the weight value corresponding to each application may be preset, and then, the weight value corresponding to each application in the multiple applications may be determined to obtain multiple weight values, and then, a weighting operation may be performed based on the multiple comparison values and the multiple weight values to obtain a target comparison result.

104. And determining the reason for changing the machine of the target according to the target comparison result.

Wherein, different comparison results can correspond to different switch reasons. The reason for changing the machine may be at least one of the following: a screen reason, a camera reason, a system reason, a battery reason, an appearance reason, and the like, which are not limited herein. The screen reason may be at least one of: the reason for the camera is at least one of the following reasons, without limitation, that the screen is too small, the touch capability of the screen is poor, the screen flickers, and the like: the camera is damaged, the shooting capability of the camera is not good, the configuration of the camera is low, and the like, which are not limited herein, and the system reason may be at least one of the following reasons: the upgrade experience is not good, the system is stuck, the system is not used to any habit, and the reason of the battery is at least one of the following: the battery has a poor endurance, a small battery capacity, a battery is easy to generate heat, and the like, but is not limited thereto, and the appearance reason may be at least one of the following: appearance lag, appearance damage, etc., and is not limited herein.

In one possible example. When the target comparison result is a similarity value, the step 104 may be implemented as follows:

and determining the target change reason corresponding to the target comparison result according to a mapping relation between a preset similarity value and a change reason.

In specific implementation, a mapping relationship between a preset similarity value and a reason for replacing the machine may be stored in advance, and further, when the target comparison result is the similarity value, the target reason for replacing the machine corresponding to the target comparison result may be determined according to the mapping relationship, so as to provide a mapping relationship between the similarity value and the reason for replacing the machine, as shown in the following table:

similarity value	Reason for changing machine
a0～a1	Change machine reason 1
a1～a2	Reason for changing machine 2
a2～a3	Reason for changing machine 3
…	…
an-1～an	Reason n for changing machine

In one possible example, when the target alignment result is an alignment list, the alignment list includes a plurality of alignment data;

in the step 104, determining the reason for replacing the target according to the target comparison result may include the following steps:

41. selecting comparison data meeting preset requirements from the multiple comparison data to obtain at least one comparison data;

42. determining a switch reason corresponding to each item of comparison data in the at least one item of comparison data to obtain at least one switch reason;

43. determining the target change machine reason according to the at least one change machine reason.

The target comparison result may be presented in an alignment list, where the alignment list may include a plurality of pieces of alignment data, each piece of proportion data may include an alignment of one dimension, and may include the following dimensions: screen, system, camera, player, memory, etc., without limitation. The preset requirement may be set by a user or default by a system, for example, the preset requirement may be comparison data of a specified dimension, and for example, the preset requirement may be comparison data corresponding to a similarity value smaller than a preset threshold, and the like, which is not limited herein. In a specific implementation, comparison data meeting preset requirements can be selected from multiple pieces of comparison data to obtain at least one piece of comparison data, and then a switch reason corresponding to each piece of comparison data in the at least one piece of comparison data can be determined to obtain at least one switch reason.

For example, taking a mobile phone as an example, when it is detected that a user changes the mobile phone, the user can be identified and determined to be the same user, data before the user is changed and data after the user is changed are determined, a new mobile phone model and an old mobile phone model of the user are determined, usage data before and after the user is changed are put into a new data pool and an old data pool, and the new data pool and the old data pool are analyzed and compared to determine a reason for changing the new mobile phone model to the old mobile phone model. The user change reason may also be graphically represented.

In addition, when it is detected that the user changes the mobile phone, the first time of changing the mobile phone can be determined, sample data before the first time is the sample data before the old mobile phone is determined by taking the first time as a boundary, the sample data after the second time is the sample data of the new mobile phone is determined, and the two sample data are analyzed to determine the reason for changing the mobile phone of the user. The user change reason may be graphically represented.

In a possible example, before the step 101, the following steps may be further included:

b1, acquiring a first time when the first electronic device uses the target user ID, wherein the first time is the time when the first electronic device is used for the first time;

b2, acquiring the current time;

b3, when the time difference between the current time and the first time is longer than a preset time, executing the step of obtaining the first usage data of the first electronic device.

The preset duration can be set by the user or defaulted by the system. In a specific implementation, a first time when the first electronic device uses the target user ID may be obtained, where the first time is a time when the first electronic device is used for the first time, and the current time may also be obtained, where the time difference between the current time and the first time is greater than a preset time, step 101 is executed, otherwise step 101 is not executed, and sometimes a user borrows a mobile phone of another person, a situation of logging in the user ID may also occur.

In one possible example, when the target user ID is a natural person ID, the following steps may be further included:

c1, obtaining the latest use data of the second electronic equipment before the first time;

c2, carrying out fault detection on the second electronic equipment according to the latest use data to obtain a detection result;

and C3, when the detection result indicates that the second electronic device has no hardware fault, executing the step of determining a reason for replacing the target according to the target comparison result.

When the reason for changing the machine is analyzed, it may be that the device is bad, and the user may select to change the machine, so that in a specific implementation, the latest usage data of the second electronic device before the first time may be obtained, and fault detection is performed on the second electronic device according to the latest usage data to obtain a detection result, when the detection result is a hardware fault, the reason for changing the machine may be directly that the device is bad, and when the detection result is that the second electronic device does not have the hardware fault, step 104 may be executed to analyze a deeper-layer reason of the machine.

In a possible example, between the above steps 101 to 102, the following steps may be further included:

d1, acquiring target identity information;

d2, matching the target identity information with preset identity information;

and D3, executing the step 102 when the target identity information is successfully matched with the preset identity information.

The preset identity information may be at least one of the following: fingerprint images, iris images, face images, voiceprint information, character strings, and the like, without limitation. In specific implementation, the target identity information may be obtained, the target identity information may be matched with the preset identity information, step 102 may be executed when the matching between the target identity information and the preset identity information is successful, and step 102 may not be executed when the matching between the target identity information and the preset identity information is failed, so that the security may be improved.

In a possible example, when the target identity information is a target face image and the preset identity information is a preset face template, the step D2 of matching the target identity information with the preset identity information may include the following steps:

d21, carrying out image segmentation on the target face image to obtain a target face region image;

d22, analyzing the feature point distribution of the target face area image;

d23, performing circular image interception on the target face region image according to M different circle centers to obtain M circular face region images, wherein M is an integer larger than 3;

d24, selecting a target circular face area image from the M circular face area images, wherein the number of the feature points contained in the target circular face area image is larger than that of other circular face area images in the M circular face area images;

d25, dividing the target circular face region image to obtain N circular rings, wherein the widths of the N circular rings are the same;

d26, sequentially matching the N circular rings with a preset face template for feature points from the circular ring with the smallest radius in the N circular rings, and accumulating the matching values of the matched circular rings;

d27, stopping feature point matching immediately when the accumulated matching value is larger than the preset matching threshold value, and inputting a prompt message of successful identity recognition.

Wherein, the electronic device can perform image segmentation on a target face image to obtain a target face region image, further analyze the distribution of feature points of the target face region image, perform circular image interception on the target face region image according to M different circle centers to obtain M circular face region images, M is an integer greater than 3, select the target circular face region image from the M circular face region images, the number of the feature points contained in the target circular face region image is greater than that of other circular face region images in the M circular face region images, divide the target circular face region image to obtain N circular rings, the ring widths of the N circular rings are the same, perform feature point matching on the N circular rings with a preset face template in sequence from the circular ring with the smallest radius among the N circular rings, and accumulate the matching values of the matched circular rings, thus, in the face recognition process, the feature points of different positions or different faces can be used for matching, namely, the whole face image is sampled, and the sampling can cover the whole face area, so that corresponding representative features can be found from each area for matching, when the accumulated matching value is larger than a preset matching threshold value, the feature point matching is immediately stopped, and a prompt message indicating that the identity recognition is successful is output, so that the face recognition can be quickly and accurately recognized.

It can be seen that, in the data analysis method described in the embodiment of the present application, first usage data of a first electronic device is obtained, second usage data of a second electronic device is obtained, the first electronic device and the second electronic device correspond to a same target user ID, the first electronic device is a currently used electronic device, the second electronic device is a previously used electronic device, the first usage data and the second usage data are compared to obtain a target comparison result, and a target reason for changing the machine is determined according to the target comparison result.

In accordance with the above, please refer to fig. 2, fig. 2 is a schematic flow chart of another data analysis method provided in the embodiment of the present application, and the data analysis method described in the embodiment is applied to the electronic device or the server shown in fig. 1A, and the method may include the following steps:

201. the method includes the steps that first time when a first electronic device uses a target user ID is obtained, and the first time is the time when the first electronic device is used for the first time.

202. And acquiring the current time.

203. And when the time difference between the current time and the first time is longer than a preset time, acquiring first use data of the first electronic equipment.

204. And acquiring second use data of the second electronic equipment, wherein the first electronic equipment and the second electronic equipment correspond to the same target user ID, the first electronic equipment is currently used electronic equipment, and the second electronic equipment is previously used electronic equipment.

205. And comparing the first use data with the second use data to obtain a target comparison result.

206. And determining the reason for changing the machine of the target according to the target comparison result.

The specific implementation process of the steps 201-206 can refer to the corresponding description in the method shown in fig. 1B, and will not be described herein again.

It can be seen that, in the data analysis method described in the embodiment of the present application, a first time when the first electronic device uses the target user ID is obtained, the first time is a time when the first electronic device is used for the first time, the current time is obtained, when a time difference between the current time and the first time is greater than a preset time, first usage data of the first electronic device is obtained, second usage data of the second electronic device is obtained, the first electronic device and the second electronic device correspond to the same target user ID, the first electronic device is a currently used electronic device, the second electronic device is a previously used electronic device, the first usage data and the second usage data are compared to obtain a target comparison result, and a target change reason is determined according to the target comparison result, so that not only a mistaken identification of a change behavior can be avoided, but also a user comparison of a new device and an old device can be performed, the reason for changing the user is analyzed, and data support can be provided for equipment updating and research.

In accordance with the above, please refer to fig. 3, which is a schematic flow chart of another data analysis method provided in the present embodiment, where the data analysis method described in the present embodiment is applied to the electronic device or the server shown in fig. 1A, and the method may include the following steps:

301. historical usage data of the first electronic device is obtained.

302. And constructing a multi-dimensional feature layer and an ID-mapping relation layer according to the historical use data.

303. And determining a natural person ID according to the multi-dimensional feature layer and the ID-mapping relation layer, and taking the natural person ID as a target user ID.

304. First usage data of the first electronic device is obtained.

305. And acquiring second use data of the second electronic equipment, wherein the first electronic equipment and the second electronic equipment correspond to the same target user ID, the first electronic equipment is currently used electronic equipment, and the second electronic equipment is previously used electronic equipment.

306. And comparing the first use data with the second use data to obtain a target comparison result.

307. And determining the reason for changing the machine of the target according to the target comparison result.

The specific implementation process of steps 301-307 can refer to the corresponding description in the method shown in fig. 1B, and is not described herein again.

It can be seen that, in the data analysis method described in the embodiment of the present application, the historical usage data of the first electronic device is obtained, the multidimensional feature layer and the ID-mapping relationship layer are constructed according to the historical usage data, the natural person ID is determined according to the multidimensional feature layer and the ID-mapping relationship layer, the natural person ID is used as the target user ID, the first usage data of the first electronic device is obtained, the second usage data of the second electronic device is obtained, the first electronic device and the second electronic device correspond to the same target user ID, the first electronic device is the currently used electronic device, the second electronic device is the previously used electronic device, the first usage data and the second usage data are compared to obtain the target comparison result, the target change reason is determined according to the target comparison result, so that not only the natural person ID can be accurately identified, but also the user comparison of the new and old devices can be performed, the reason for changing the user is analyzed, and data support can be provided for equipment updating and research.

In accordance with the foregoing, please refer to fig. 4, where fig. 4 is an electronic device provided in an embodiment of the present application, where the electronic device may be a server, a mobile phone, or another electronic product, and includes: a processor and a memory; and one or more programs stored in the memory and configured to be executed by the processor, the programs including instructions for performing the steps of:

acquiring first use data of first electronic equipment;

It can be seen that, in the electronic device described in the embodiment of the present application, first usage data of a first electronic device is obtained, second usage data of a second electronic device is obtained, the first electronic device and the second electronic device correspond to a same target user ID, the first electronic device is a currently used electronic device, the second electronic device is a previously used electronic device, the first usage data and the second usage data are compared to obtain a target comparison result, and a target reason for changing the machine is determined according to the target comparison result.

In one possible example, in said obtaining second usage data of the second electronic device, the program comprises instructions for performing the steps of:

obtaining source identification information of a data source corresponding to the first use data to obtain at least one source identification information;

and acquiring second use data of the second electronic equipment according to the at least one source identification information.

In one possible example, in said obtaining second usage data of said second electronic device in dependence on said at least one source identification information, said program comprises instructions for performing the steps of:

acquiring original use data of the second electronic equipment in a preset time period according to the at least one source identification information;

and screening out the use data corresponding to the target user ID from the original use data to obtain the second use data.

In one possible example, when the first usage data includes a plurality of first application data for a plurality of applications, wherein each application corresponds to a first application data; in the aspect of comparing the first usage data with the second usage data to obtain a target comparison result, the program includes instructions for performing the following steps:

determining a plurality of second application data corresponding to the plurality of applications from the second usage data, wherein each application corresponds to one second application data;

comparing the plurality of first application data with the plurality of second application data to obtain a plurality of comparison values;

determining a weight value corresponding to each application in the plurality of applications to obtain a plurality of weight values;

and carrying out weighting operation on the comparison values and the weight values to obtain the target comparison result.

In one possible example, when the target comparison result is a similarity value, in the aspect of determining a reason for changing the machine according to the target comparison result, the program includes instructions for performing the following steps:

in the aspect of determining a reason for changing the target according to the target comparison result, the program includes instructions for performing the following steps:

selecting comparison data meeting preset requirements from the multiple comparison data to obtain at least one comparison data;

determining a switch reason corresponding to each item of comparison data in the at least one item of comparison data to obtain at least one switch reason;

determining the target change machine reason according to the at least one change machine reason.

In one possible example, when the target user ID is a natural person ID, the program further includes instructions for performing the steps of:

acquiring historical use data of the first electronic equipment;

constructing a multi-dimensional feature layer and an ID-mapping relation layer according to the historical use data;

and determining the ID of the natural person according to the multi-dimensional feature layer and the ID-mapping relation layer.

In one possible example, the program further comprises instructions for performing the steps of:

acquiring first time when the first electronic equipment uses the target user ID, wherein the first time is the time when the first electronic equipment is used for the first time;

acquiring current time;

and when the time difference between the current time and the first time is greater than a preset time, executing the step of acquiring first use data of the first electronic equipment.

obtaining last usage data of the second electronic device prior to the first time;

carrying out fault detection on the second electronic equipment according to the latest use data to obtain a detection result;

and when the detection result indicates that the second electronic device has no hardware fault, executing the step of determining the reason for changing the machine according to the target comparison result.

The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that the electronic device comprises corresponding hardware structures and/or software modules for performing the respective functions in order to realize the above-mentioned functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative elements and algorithm steps described in connection with the embodiments provided herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiment of the present application, the electronic device may be divided into the functional units according to the method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.

Referring to fig. 5A, fig. 5A is a schematic structural diagram of a data analysis apparatus provided in the present embodiment. The data analysis apparatus is applied to the electronic device or the server shown in fig. 1A, and includes a first obtaining unit 501, a second obtaining unit 502, a comparing unit 503 and a determining unit 504, wherein,

a first obtaining unit 501, configured to obtain first usage data of a first electronic device;

a second obtaining unit 502, configured to obtain second usage data of the second electronic device, where the first electronic device and the second electronic device correspond to a same target user ID, the first electronic device is a currently used electronic device, and the second electronic device is a previously used electronic device;

a comparing unit 503, configured to compare the first usage data with the second usage data to obtain a target comparison result;

a determining unit 504, configured to determine a reason for changing the target according to the target comparison result.

It can be seen that, the data analysis apparatus described in the embodiment of the present application obtains first usage data of a first electronic device, obtains second usage data of a second electronic device, where the first electronic device and the second electronic device correspond to a same target user ID, the first electronic device is a currently used electronic device, the second electronic device is a previously used electronic device, compares the first usage data with the second usage data to obtain a target comparison result, and determines a target reason for changing a machine according to the target comparison result.

In one possible example, in the aspect of acquiring the second usage data of the second electronic device, the second acquiring unit 502 is specifically configured to:

In a possible example, in the aspect of acquiring the second usage data of the second electronic device according to the at least one source identification information, the second acquiring unit 502 is specifically configured to:

In one possible example, when the first usage data includes a plurality of first application data for a plurality of applications, wherein each application corresponds to a first application data; in the aspect of comparing the first usage data with the second usage data to obtain a target comparison result, the comparing unit 503 is specifically configured to:

In a possible example, when the target comparison result is a similarity value, in terms of determining a reason for changing the target according to the target comparison result, the determining unit 504 is specifically configured to:

in the aspect of determining a reason for replacing the target according to the target comparison result, the determining unit 504 is specifically configured to:

In one possible example, as shown in fig. 5B, fig. 5B is a further apparatus of the data analysis method shown in fig. 5A, which may further include, compared with fig. 5A: the building unit 505 is specifically as follows:

the first obtaining unit 501 is further specifically configured to obtain historical usage data of the first electronic device;

the constructing unit 505 is configured to construct a multi-dimensional feature layer and an ID-mapping relationship layer according to the historical usage data;

the determining unit 504 is further specifically configured to determine the natural person ID according to the multi-dimensional feature layer and the ID-mapping relationship layer.

In a possible example, the first obtaining unit 501 is further specifically configured to obtain a first time when the first electronic device uses the target user ID, where the first time is a time when the first electronic device is used for the first time; and obtaining the current time;

the step of acquiring the first usage data of the first electronic device is performed by the first acquiring unit 501 when a time difference between the current time and the first time is greater than a preset time.

Further, in a possible example, when the target user ID is a natural human ID, as shown in fig. 5C, fig. 5C is still another apparatus of the data analysis method shown in fig. 5B, and compared with fig. 5B, the method may further include: the detecting unit 506 is specifically as follows:

the second obtaining unit 502 is further specifically configured to obtain last usage data of the second electronic device before the first time;

the detecting unit 506 is configured to perform fault detection on the second electronic device according to the latest usage data to obtain a detection result;

when the detection result indicates that the second electronic device has no hardware fault, the comparing unit 503 executes the step of determining a reason for replacing the target according to the target comparison result.

It can be understood that the functions of each program module of the data analysis apparatus in this embodiment may be specifically implemented according to the method in the foregoing method embodiment, and the specific implementation process may refer to the related description of the foregoing method embodiment, which is not described herein again.

Embodiments of the present application also provide a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the data transmission methods as described in the above method embodiments.

Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the data transmission methods as recited in the above method embodiments.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may be implemented in the form of a software program module.

The integrated units, if implemented in the form of software program modules and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned memory comprises: various media capable of storing program codes, such as a usb disk, a read-only memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and the like.

Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash disk, ROM, RAM, magnetic or optical disk, and the like.

The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

A method of data analysis, comprising:

acquiring first use data of first electronic equipment;

acquiring second use data of the second electronic device, wherein the first electronic device and the second electronic device correspond to the same target user ID, the first electronic device is a currently used electronic device, and the second electronic device is a previously used electronic device;

comparing the first usage data with the second usage data to obtain a target comparison result;

and determining the reason for changing the machine of the target according to the target comparison result.
The method of claim 1, wherein the obtaining second usage data of the second electronic device comprises:

obtaining source identification information of a data source corresponding to the first use data to obtain at least one source identification information;

and acquiring second use data of the second electronic equipment according to the at least one source identification information.
The method of claim 2, wherein the obtaining second usage data of the second electronic device according to the at least one source identification information comprises:

acquiring original use data of the second electronic equipment in a preset time period according to the at least one source identification information;

and screening out the use data corresponding to the target user ID from the original use data to obtain the second use data.
The method according to any of claims 1-3, wherein when the first usage data comprises a plurality of first application data for a plurality of applications, wherein each application corresponds to a first application data; the comparing the first usage data with the second usage data to obtain a target comparison result includes:

determining a plurality of second application data corresponding to the plurality of applications from the second usage data, wherein each application corresponds to one second application data;

comparing the plurality of first application data with the plurality of second application data to obtain a plurality of comparison values;

determining a weight value corresponding to each application in the plurality of applications to obtain a plurality of weight values;

and carrying out weighting operation on the comparison values and the weight values to obtain the target comparison result.
The method according to any one of claims 1 to 4, wherein when the target comparison result is a similarity value, the determining a reason for replacing the machine according to the target comparison result includes:

and determining the target change reason corresponding to the target comparison result according to a mapping relation between a preset similarity value and a change reason.
The method of any one of claims 1 to 4, wherein when the target alignment result is an alignment list, the alignment list comprises a plurality of alignment data;

the determining a reason for replacing the target according to the target comparison result includes:

selecting comparison data meeting preset requirements from the multiple comparison data to obtain at least one comparison data;

determining a switch reason corresponding to each item of comparison data in the at least one item of comparison data to obtain at least one switch reason;

determining the target change machine reason according to the at least one change machine reason.
The method according to any one of claims 1-6, wherein when the target user ID is a natural human ID, the method further comprises:

acquiring historical use data of the first electronic equipment;

constructing a multi-dimensional feature layer and an ID-mapping relation layer according to the historical use data;

and determining the ID of the natural person according to the multi-dimensional feature layer and the ID-mapping relation layer.
The method according to any one of claims 1-7, further comprising:

acquiring first time when the first electronic equipment uses the target user ID, wherein the first time is the time when the first electronic equipment is used for the first time;

acquiring current time;

and when the time difference between the current time and the first time is greater than a preset time, executing the step of acquiring first use data of the first electronic equipment.
The method of claim 8, wherein when the target user ID is a natural human ID, the method further comprises:

obtaining last usage data of the second electronic device prior to the first time;

carrying out fault detection on the second electronic equipment according to the latest use data to obtain a detection result;

and when the detection result indicates that the second electronic device has no hardware fault, executing the step of determining the reason for changing the machine according to the target comparison result.
A data analysis apparatus, characterized in that the apparatus comprises:

a first acquisition unit configured to acquire first usage data of a first electronic device;

a second obtaining unit, configured to obtain second usage data of the second electronic device, where the first electronic device and the second electronic device correspond to a same target user ID, the first electronic device is a currently used electronic device, and the second electronic device is a previously used electronic device;

the comparison unit is used for comparing the first use data with the second use data to obtain a target comparison result;

and the determining unit is used for determining the reason for changing the target according to the target comparison result.
The apparatus according to claim 10, wherein in said obtaining second usage data of the second electronic device, the second obtaining unit is specifically configured to:

obtaining source identification information of a data source corresponding to the first use data to obtain at least one source identification information;

and acquiring second use data of the second electronic equipment according to the at least one source identification information.
The apparatus according to claim 11, wherein, in said obtaining second usage data of the second electronic device according to the at least one source identification information, the second obtaining unit is specifically configured to:

acquiring original use data of the second electronic equipment in a preset time period according to the at least one source identification information;

and screening out the use data corresponding to the target user ID from the original use data to obtain the second use data.
The apparatus according to any of claims 10-12, wherein when the first usage data comprises a plurality of first application data for a plurality of applications, each application corresponds to a first application data; in the aspect of comparing the first usage data with the second usage data to obtain a target comparison result, the comparing unit is specifically configured to:

determining a plurality of second application data corresponding to the plurality of applications from the second usage data, wherein each application corresponds to one second application data;

comparing the plurality of first application data with the plurality of second application data to obtain a plurality of comparison values;

determining a weight value corresponding to each application in the plurality of applications to obtain a plurality of weight values;

and carrying out weighting operation on the comparison values and the weight values to obtain the target comparison result.
The apparatus according to any one of claims 10 to 13, wherein when the target comparison result is a similarity value, in the aspect of determining a reason for changing the machine according to the target comparison result, the determining unit is specifically configured to:

and determining the target change reason corresponding to the target comparison result according to a mapping relation between a preset similarity value and a change reason.
The apparatus according to any one of claims 10-13, wherein when the target alignment result is an alignment list, the alignment list comprises a plurality of alignment data;

in the aspect of determining a reason for replacing the target according to the target comparison result, the determining unit is specifically configured to:

selecting comparison data meeting preset requirements from the multiple comparison data to obtain at least one comparison data;

determining a switch reason corresponding to each item of comparison data in the at least one item of comparison data to obtain at least one switch reason;

determining the target change machine reason according to the at least one change machine reason.
The apparatus according to any of claims 10-15, wherein when the target user ID is a natural person ID, the apparatus further comprises: the construction unit specifically comprises the following components:

the first obtaining unit is further specifically configured to obtain historical usage data of the first electronic device;

the construction unit is used for constructing a multi-dimensional feature layer and an ID-mapping relation layer according to the historical use data;

the determining unit is further specifically configured to determine the ID of the natural person according to the multi-dimensional feature layer and the ID-mapping relationship layer.
The apparatus according to any one of claims 10 to 16,

the first obtaining unit is further specifically configured to obtain a first time when the first electronic device uses the target user ID, where the first time is a time when the first electronic device is used for the first time; and obtaining the current time;

and the first obtaining unit is used for obtaining first use data of the first electronic equipment when the time difference between the current time and the first time is longer than a preset time.
An electronic device comprising a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-9.
A computer-readable storage medium, characterized in that a computer program for electronic data exchange is stored, wherein the computer program causes a computer to perform the method according to any one of claims 1-9.
A computer program product, characterized in that the computer program product comprises a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform the method according to any one of claims 1-9.