CN114258662A

CN114258662A - User behavior data processing method and device, server and storage medium

Info

Publication number: CN114258662A
Application number: CN201980099450.1A
Authority: CN
Inventors: 庄立纯
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: 2019-11-04
Filing date: 2019-11-04
Publication date: 2022-03-29
Also published as: WO2021087684A1

Abstract

The embodiment of the application discloses a user behavior data processing method, a user behavior data processing device, a server and a storage medium. The method comprises the following steps: acquiring an identifier of a target device; acquiring a user account corresponding to the identifier of the target device; determining a plurality of target user accounts meeting characteristic conditions from the user accounts; and analyzing the user behavior data based on the specified dimensionality and outputting an analysis result. Therefore, by the above method, after the user behavior data is acquired, the identifier of the target device can be determined first, and then the comparison result of the behavior data corresponding to the plurality of target user accounts of the target device can be output subsequently, so that the difference of the behavior data of different target device users can be output.

Description

User behavior data processing method and device, server and storage medium

Technical Field

The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for processing user behavior data, a server, and a storage medium.

Background

With the development of internet services, data is also increasing explosively, and the operation requirements on data in various industries are more and more, for example, a related recommendation and retrieval system is to screen out a small part of data meeting the service requirements from a large amount of data. However, there are certain disadvantages in the related data request process.

Disclosure of Invention

In view of the foregoing problems, the present application provides a method, an apparatus, a server, and a storage medium for processing user behavior data to improve the foregoing problems.

In a first aspect, the present application provides a user behavior data processing method, where the method includes: acquiring an identifier of a target device; acquiring user behavior data corresponding to the target equipment; and analyzing the user behavior data based on the specified dimensionality and outputting an analysis result.

In a second aspect, the present application provides a user behavior data processing apparatus, including: a target device acquisition unit that acquires an identifier of a target device; a behavior data acquiring unit, configured to acquire user behavior data corresponding to the target device; and the data processing unit is used for analyzing the user behavior data based on the specified dimensionality and outputting an analysis result.

In a third aspect, the present application provides a server comprising a processor and a memory; one or more programs are stored in the memory and configured to be executed by the processor to implement the methods described above.

In a fourth aspect, the present application provides a computer readable storage medium having program code stored therein, wherein the method described above is performed when the program code is executed by a processor.

According to the user behavior data processing method, the user behavior data processing device, the server and the storage medium, the identification of the target device can be obtained firstly, then the user account corresponding to the identification of the target device is obtained, a plurality of target user accounts meeting characteristic conditions are determined from the user accounts, the user behavior data are analyzed based on the specified dimensionality, and the analysis result is output. Therefore, by the above method, after the user behavior data is obtained, the identifier of the target device can be determined first, and then the comparison result of the corresponding user behavior data of the target device can be output subsequently, so that the difference of the behavior data of different target device users can be output.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a flowchart illustrating a user behavior data processing method according to an embodiment of the present application

Fig. 2 is a schematic diagram illustrating an operation interface in a user behavior data processing method according to an embodiment of the present application;

fig. 3 is a flowchart illustrating a user behavior data processing method according to another embodiment of the present application;

fig. 4 is a schematic diagram illustrating analysis and comparison results in a user behavior data processing method according to another embodiment of the present application;

FIG. 5 is a flow chart illustrating a method for processing user behavior data according to yet another embodiment of the present application;

FIG. 6 is a diagram illustrating a machine-type selection interface in a method for processing user behavior data according to another embodiment of the present application;

FIG. 7 is a flow chart illustrating a method for processing user behavior data according to yet another embodiment of the present application;

fig. 8 is a block diagram illustrating a user behavior data processing apparatus according to an embodiment of the present application;

fig. 9 is a block diagram showing a user behavior data processing apparatus according to another embodiment of the present application;

fig. 10 is a block diagram showing another user behavior data processing apparatus according to still another embodiment of the present application;

fig. 11 is a block diagram showing a configuration of still another user behavior data processing apparatus according to still another embodiment of the present application;

fig. 12 is a block diagram illustrating a structure of another electronic device according to the present application for executing a user behavior data processing method according to an embodiment of the present application;

fig. 13 is a storage unit for storing or carrying program codes for implementing a user behavior data processing method according to an embodiment of the present application.

Detailed Description

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.

User portrayal is a very popular research direction in the related art. By processing, mining and depicting information such as active behaviors and consumption behaviors of users, user images (namely behavior data of the users) can be formed, and then user image labels of related users can be generated, so that user characteristics can be known more comprehensively. After the user portrait label is generated, the user can be pushed with proper content more pertinently, and the pushing operation cost can be reduced.

For example, upon generating a user representation tag for a user, the generated user representation tag may characterize that the user likes sports, that the user likes rice, and that the user likes to watch sports events. Then in this case, when the message is pushed to the user, a message matching the user profile may be pushed. For example, when the user is in the process of using an application program of the order type, more information about rice may be pushed. While more video content about the sports game may be pushed while the user is using the video-like application.

The inventor finds in research that after being generated, the related user portrait label is mainly developed for operation purposes, and comparison of analysis dimensions cannot be performed. The inventor has found that different user groups using the same application program have different distributions of the same tag, and it is necessary to perform comparative analysis on image tags of different user groups. And the related portrait generation platform can not compare the difference between portrait labels of users among different mobile phone brands according to different mobile phone brands and models, and can not realize the research on characteristics of user loyalty, inflow and outflow and the like. Therefore, the inventor provides the user behavior data processing method, the user behavior data processing device, the server and the storage medium, so that after the user behavior data are obtained, the identifier of the target device can be determined first, then the comparison result of the behavior data corresponding to the target user accounts of the target device can be output subsequently, and further the difference of the behavior data of different target device users can be output.

Embodiments of the present application will be described in detail below with reference to the accompanying drawings.

Referring to fig. 1, a method for processing user behavior data according to an embodiment of the present application includes:

step S410: the identification of the target device is obtained.

It should be noted that, in the embodiment of the present application, comparative analysis of user behavior data is performed based on a target device. Wherein the identification of the target device may be understood as information for uniquely characterizing the device. The identification may be the brand or specific model of the target device.

As one approach, the identity of the target device may be determined by way of a search.

In this manner, the information platform may provide a search interface. Keywords about the equipment can be input in the search interface, a search request is triggered, and then the information platform carries out searching based on the keywords. The information platform may use the searched device brand identity as the identity of the target device after responding to the search request.

Alternatively, there may be multiple models for some brands of equipment. In this way, in response to the search request, displaying a plurality of model identifiers corresponding to the searched device brand identifiers; and taking the selected model identifier in the plurality of model identifiers as the identifier of the target device.

As a mode, the data processing method provided in the embodiment of the present application may be executed on an information platform. The information platform can provide an operation interface for relevant personnel to operate so as to select the identification of the target equipment. For example, as shown in fig. 2, in the operation interface of the client provided by the information platform, an operation interface may be displayed, in which the identifiers of target devices such as a device brand a, a device brand B, a device brand C, a device brand D, a device brand E, and a device brand F are displayed, and one selection box 99 is arranged corresponding to each identifier of the target devices. In this case, obtaining the identification of the target device may be understood as obtaining the identification (device brand) of the target device selected by the user in the operation interface. In the process of operating the operation interface, the user may select only one device brand as the identifier of the target device, or may select multiple device brands as the identifiers of the target devices. Correspondingly, the information platform executing the user behavior data processing method provided in this embodiment may detect the number of identifiers of the target device carried in the data sent by the client, so as to determine the number of identifiers of the target device selected by the user. Alternatively, different comparison results may be output corresponding to the number of identifications of different target devices.

Step S420: and acquiring user behavior data corresponding to the target equipment.

Step S430: and analyzing the user behavior data based on the specified dimensionality and outputting an analysis result.

According to the user behavior data processing method, the identification of the target device can be obtained firstly, then the user account corresponding to the identification of the target device is obtained, a plurality of target user accounts meeting characteristic conditions are determined from the user accounts, the user behavior data are analyzed based on the specified dimensionality, and an analysis result is output. Therefore, by the above method, after the user behavior data is obtained, the identifier of the target device can be determined first, and then the comparison result of the corresponding user behavior data of the target device can be output subsequently, so that the difference of the behavior data of different target device users can be output.

Referring to fig. 3, a method for processing user behavior data according to an embodiment of the present application includes:

step S110: the identification of the target device is obtained.

Step S120: and acquiring a user account corresponding to the identifier of the target equipment.

In one embodiment, the generated user representation may include information uniquely identifying the user representation, such as a user account, in addition to the user representation tag. In this manner, each user account corresponds to at least one user representation tag and an identification of the electronic device used by the user to whom the user representation tag belongs. For example, information that may be included in a generated representation of a user is: a user account number, a user portrait label, and an identification of the electronic device used.

Among other things, the user account may be implemented in a number of ways. Optionally, the user account may be a phone number of the user, or may be a login account registered by the user in the platform for executing the method provided in this embodiment.

Step S130: and determining a plurality of target user accounts meeting characteristic conditions from the user accounts.

It should be noted that the users to which each user representation belongs are distinguished in some features. In order to accurately analyze the difference of the behavior data of the characteristic population, part of the user accounts can be screened from the user accounts corresponding to the identifier of the target device to serve as a plurality of target user accounts.

The characteristic condition may include a plurality of conditions, or may be determined in a plurality of ways.

As one way, the characteristic conditions include at least one of the following conditions: the sex meets the specified sex; the age meets the specified age interval; professions meet a specified profession category; regularly satisfying a designated area; and the family member category satisfies the specified category.

Optionally, in this embodiment of the present application, what specific contents the characteristic condition includes in each analysis and comparison process may be determined in a variety of ways.

As a way, a configuration file for storing the specific content of the characteristic condition may be generated in the present embodiment. The feature conditions included in the configuration files corresponding to different analysis and comparison environments may be different. It should be noted that the information platform for executing the data processing method provided in this embodiment may be operated by a relevant person, and the relevant person may log in by using an operation account of the relevant person before performing the operation. Different operators can configure different comparison requirements of the operators, and the comparison requirements can include characteristic conditions of comparison people. In this way, when the information platform detects that a login behavior occurs, the information platform acquires a login account corresponding to the login behavior, then acquires a comparison requirement corresponding to the login account based on the login account in which the login behavior occurs, and further acquires a characteristic condition required for comparison and analysis at the current time from the comparison requirement.

Illustratively, the information platform stores operation accounts including an operation account a and an operation account B. The configuration characteristic conditions corresponding to the operation account A comprise that the age meets a specified age section, the occupation meets a specified occupation category and the occupation meets a specified area. The configuration characteristic conditions corresponding to the operation account B comprise that occupation meets a specified occupation category, a place where the operation account B is frequently occupied meets a specified area and a family member category meets a specified category. Then, in the case that the information platform detects that the currently logged-in operation account is operation account a, the information platform may acquire characteristic conditions including that the age meets a specified age section, that the occupation meets a specified occupation category, and that the occupation meets a specified area in a daily life, and write the acquired characteristic conditions into the aforementioned configuration file. And generating corresponding information of the operation account A and the corresponding characteristic conditions in the configuration file.

Correspondingly, after the information platform acquires the user account corresponding to the identifier of the target device, the information platform can further read the configuration file to read the characteristic conditions (the age meets the specified age range, the occupation meets the specified occupation category and the occupation meets the specified area) corresponding to the currently logged-in account (the operation account a) from the configuration file, and then the information platform is favorable for acquiring a plurality of target user accounts according to the acquired characteristic conditions corresponding to the operation account a. Similarly, when the information platform executing the data processing method provided by the embodiment of the present application acquires that the logged-in operation account is the operation account B, the information platform may acquire the characteristic conditions corresponding to the operation account B from the configuration file in a similar process as described above (the job satisfies the specified job category, the frequent satisfaction of the specified area, and the family member category satisfies the specified category).

It should be noted that, as one way, in order to save the storage space of the information platform, after detecting that a certain operation account logs out, the feature condition corresponding to the logged-out operation account may be deleted from the configuration file.

Step S140: and analyzing the user behavior data based on the specified dimensionality and outputting an analysis result.

It should be noted that, in the embodiment of the present application, comparing the behavior data corresponding to the multiple target user accounts with each other may be understood as comparing the behavior data of the users to which the multiple target user accounts belong with each other. Then, in the embodiment of the present application, the information platform that executes the user behavior data processing method may obtain or generate the user behavior data in advance to be stored locally. And then after acquiring a plurality of target user accounts, comparing behavior data corresponding to the plurality of target user accounts based on the specified dimensionality.

The information platform can obtain the user behavior data in various ways. As one way, the information platform provides a platform for providing services to the end user, in this case, the end user can obtain the services required by the end user from the information platform, and in the process of obtaining the services each time by the end user, the operation behavior of the end user can be recorded under the permission of the end user. For example, it may record what types of information are browsed by the end user, what locations the end user frequently visits, and the like, and may generate behavior data for each end user.

Optionally, in this way, the information platform may periodically update the behavior data of the user that has been generated. It should be noted that, the terminal user may have different interests and hobbies at different times, and the user images generated at different times may also be different, so that the image update may be performed periodically by the information platform in order to make the user images to be compared be images representing the current time of the user. In this manner, an information platform implementing the data processing method provided by the present embodiment may be configured with a generated user representation storage area and a user representation storage area to be generated. The generated user portrait storage area stores a user portrait generated by the information platform after determining user preferences based on set criteria. Illustratively, after end user A accesses the information platform for the first time, information for sports is accessed. And the information platform is configured with the information that the same user accesses the same type of information for a specified number of times, and then the preference of the user is judged to be the type. Then when end user a accesses the information platform for the first time, and then accesses the sports-like information, the information platform stores the corresponding information of end user a and sports preferences in the aforementioned user representation storage area to be generated.

In the subsequent operation of the information platform, the access condition of the terminal user A can be continuously detected, if the terminal A is detected to access the information of the sports class again, the information platform adds 1 to the number of times of recording the information of the terminal user A accessing the sports class in the user portrait storage area to be generated, so that the preference of the terminal user A is judged as the sports class until the number of times of accessing the information of the sports class meets the specified number, a user portrait of the terminal user A preferring the sports class is generated in the generated user portrait storage area, and meanwhile, the relevant information of the terminal user A in the user portrait storage area to be generated is deleted. Alternatively, the generated user representation storage area may be understood as an area storing an already generated user representation, and the user representation storage area to be generated may be understood as an area storing a pseudo user representation.

In addition, in addition to the aforementioned generation of a user representation by the information platform itself executing the data processing method, a user representation provided by a third party may be directly acquired. Alternatively, in addition to the client corresponding to the information platform, another client may be installed in the terminal used by the user, and the other client may also detect some behavior data of the user under the authorization of the user. In this case, as a way, the information platform may configure an interface with a server corresponding to another client in order to obtain a more accurate user image, and obtain a user image provided by a third party from another server.

Furthermore, as another mode, the information platform can combine the user portrait generated by the information platform with the user portrait obtained from a third party, so as to obtain a more comprehensive user portrait, and further obtain a more comprehensive comparison result when subsequently performing user portrait comparison. Optionally, the information platform may delete a user representation tag included in the repeated user representation during merging of the self-generated user representation with a user representation obtained from a third party.

In the embodiment of the present application, in the comparison process, the comparison may be performed based on specified dimensions, and then as a way, the specified dimensions at least include at least one of the following dimensions: a preference dimension for a specified type of application; replacing the frequency dimension of the intelligent terminal; dietary preference dimension; and travel idiomatic dimension.

By one approach, the dimensions that different operating users desire to compare may be different for the relevant operators of the information platform. As a way, the operator may configure the dimension that needs to be compared in the information platform in advance, and bind the dimension that needs to be compared with the operation account of the operator. And after detecting that a certain operation account logs in, the information platform stores the dimension which is required to be compared and corresponds to the logged-in operation account into the configuration file.

Illustratively, the information platform stores operation accounts including an operation account a and an operation account B. The dimensions corresponding to the operation account A and needing comparison comprise a diet preference dimension, an intelligent terminal replacement frequency dimension and a preference dimension of an application program of a specified type. The configuration characteristic conditions corresponding to the operation account B comprise shopping type preference dimensions and travel vehicle preference dimensions. Then, when the information platform detects that the currently logged-in operation account is the operation account a, the information platform may acquire dimensions that need to be compared, including a diet preference dimension, an intelligent terminal replacement frequency dimension, and a preference dimension of a specific type of application program, and write the acquired dimensions into the aforementioned configuration file. And generating corresponding information of the operation account A and the corresponding dimension which needs to be compared in the configuration file.

Correspondingly, after the information platform acquires a plurality of target user accounts, the configuration file can be further read from the configuration file to read the dimension (diet preference dimension, intelligent terminal replacement frequency dimension and preference dimension of the application program of the specified type) required to be compared corresponding to the currently logged-in account (operation account A), and then the dimension required to be compared corresponding to the acquired operation account A is facilitated to be analyzed and compared, and the comparison result is output. Similarly, when the information platform executing the data processing method provided by the embodiment of the present application acquires that the logged-in operation account is the operation account B, the information platform may acquire the required comparison dimensions (the shopping type preference dimension and the travel vehicle preference dimension) corresponding to the operation account B from the configuration file in a similar process as described above.

For example, as shown in fig. 4, the information platform generates an exemplary comparison analysis result in the case where the identification of the target device is determined to include brand a and brand B, and in the case where the designated dimension is determined to be a preferred dimension of the travel vehicle.

According to the user behavior data processing method, the identification of the target device can be obtained firstly, then the user account corresponding to the identification of the target device is obtained, a plurality of target user accounts meeting characteristic conditions are determined from the user accounts, the user behavior data are analyzed based on the specified dimensionality, and an analysis result is output. Therefore, by the above method, after the user behavior data is acquired, the identifier of the target device can be determined first, and then the comparison result of the behavior data corresponding to the plurality of target user accounts of the target device can be output subsequently, so that the difference of the behavior data of different target device users can be output.

Referring to fig. 5, a method for processing user behavior data according to an embodiment of the present application includes:

step S210: and displaying a plurality of equipment brand identifications to be selected.

As one mode, when an analysis comparison instruction is received, the identifier of the target device is obtained from the multiple devices to be selected.

Step S220: and taking the brand identifier determined from the plurality of device brand identifiers to be selected as the identifier of the target device.

It should be noted that even for the same brand of equipment, there are many sub-categories, and one of the sub-categories is the model. Different models are different in price and function, and corresponding users are also different. Correspondingly, as a mode, an operator performing the data processing method provided in this embodiment correspondingly may also select a model on a client corresponding to the information platform. Referring to fig. 6, in the interface shown in fig. 6, when a touch operation acting on the device brand is detected, a model selection interface 97 may be further displayed, in which a device model corresponding to the device brand touched by the operator is displayed. And the device proceeds to the corresponding selection box 98.

As one mode, before the step of using the brand determined from the multiple device brand identities to be selected as the identity of the target device, the method further includes: displaying model information corresponding to the determined brand identifier in the multiple equipment brand identifiers to be selected; detecting whether the machine type information is selected or not; and if no model information is selected, executing the brand identification determined from the multiple equipment brand identifications to be selected as the identification of the target equipment.

Correspondingly, if the organic type information is selected, the selected type information is used as the identification of the target device.

Optionally, the information platform executing the data processing method provided by the embodiment of the present application may identify through the data sent by the corresponding client, and further identify whether the brand or the model is selected by the operating user, or select both the brand and the model as a basis for subsequent comparison.

As one mode, when generating data of the identifier of the target device, the client corresponding to the information platform may generate the data according to a specified private protocol. For example, it may be configured to include the first partial data and the second partial data in the generated data. Wherein the first part of data is used for data describing the overall data situation (i.e. whether the introducing operation user selects a brand or a model or selects a model while selecting the brand), and the second part of data comprises the data to be actually transmitted (i.e. the identification of the target device selected by the operation user). In this case, after receiving the data sent by the client, the information platform may identify, through the first part of data in the data, whether the identifier of the target device carried in the data transmitted by the client is a brand or a model, or both a brand and an organic model. And then acquiring the brand as an identifier of a target device according to the position of the brand carried in the first part of data in the second part of data, and acquiring the model as an identifier of the target device according to the position of the model carried in the first part of data in the second part of data. For example, the identifier of the target device selected by the user may be stored in the form of an array in the second part of data, and then specific arrays storing brands and models may be configured in the first part of data.

Step S230: and acquiring a user account corresponding to the identifier of the target equipment.

As one mode, the step of acquiring the user account corresponding to the identifier of the target device includes: acquiring first user behavior data stored by a user behavior data providing platform based on a network; and acquiring a user account corresponding to the identifier of the target device from the user account to which the first user behavior data belongs.

As another mode, the step of acquiring the user account corresponding to the identifier of the target device includes: acquiring a user data packet uploaded from a client; and acquiring a user account corresponding to the identifier of the target device from the user data packet.

It should be noted that, an operating user of the information platform may copy a user data packet carrying a user image from other terminal devices through the portable storage device, and in this manner, the operating user may upload the offline user data packet through the client of the information platform, so as to implement subsequent analysis and comparison of the user image acquired in the offline manner.

Step S240: and determining a plurality of target user accounts meeting characteristic conditions from the user accounts.

Step S250: and analyzing the user behavior data based on the specified dimensionality and outputting an analysis result.

It should be noted that the method provided by the embodiment of the present application may be executed on an information distribution platform. In this manner, as a manner, when an access request of a terminal is received, an identification of the accessed terminal is acquired; detecting whether the identification of the accessed terminal is stored or not; and if not, taking the identifier of the accessed terminal as a device to be selected.

In this manner, then, the step of obtaining the identification of the target device from the plurality of devices to be selected comprises: selecting the equipment to be selected, which meets the appointed sorting position in the plurality of equipment to be selected, as target equipment; and acquiring the determined identification of the target device.

According to the user behavior data processing method, the identification of the target device can be obtained firstly, then the user account corresponding to the identification of the target device is obtained, a plurality of target user accounts meeting characteristic conditions are determined from the user accounts, the user behavior data are analyzed based on the specified dimensionality, and an analysis result is output. Therefore, by the above method, after the user behavior data is acquired, the identifier of the target device can be determined first, and then the comparison result of the behavior data corresponding to the plurality of target user accounts of the target device can be output subsequently, so that the difference of the behavior data of different target device users can be output. In addition, in the embodiment of the application, two different reference factors, namely the brand or the model of the device, are used as a basis for subsequently comparing the user behavior data, so that a comparison result of behavior data corresponding to a plurality of target user accounts of the brand of the device can be output, a comparison result of behavior data corresponding to a plurality of target user accounts of the model of the device can also be output, and the comparison flexibility is improved.

Referring to fig. 7, a method for processing user behavior data according to an embodiment of the present application includes:

step S310: the identification of the target device is obtained.

Step S320: and acquiring a user account corresponding to the identifier of the target equipment.

Step S330: and determining a plurality of target user accounts meeting characteristic conditions from the user accounts.

Step S340: and detecting whether the identification of the target equipment is multiple.

Step S350: and if the target equipment is detected not to be provided with a plurality of identifiers, analyzing the user behavior data based on the specified dimensionality, and outputting an analysis result.

Step S360: and if the identifiers of the target devices are detected to be multiple, acquiring behavior data of specified dimensions corresponding to target user accounts corresponding to the identifiers of the multiple target devices, and obtaining multiple behavior parameters to be compared.

Step S370: and comparing the behavior parameters to be compared and outputting an analysis result.

As one way, the user behavior data is analyzed based on a specified dimension, and the step of outputting an analysis result includes: obtaining a dimension determined from a plurality of dimensions to be selected as a designated dimension; obtaining a chart display type; and comparing the behavior data corresponding to the plurality of target user accounts based on the specified dimensions, and generating a comparison analysis result displayed based on the chart display type.

Optionally, each dimension corresponds to a specified chart display type, and the step of obtaining the chart display type includes: and acquiring a chart display type corresponding to the specified dimension.

Optionally, the step of obtaining the chart display type includes: acquiring the terminal model of a receiving end of the comparison analysis result; and acquiring a chart display type corresponding to the terminal model.

As a mode, when an operator operates the information platform through a client of the information platform to compare behavior data corresponding to a plurality of target user accounts, a comparison analysis result output by the information platform may be directly fed back to the client of the operator or transmitted to other terminal devices. When the information platform outputs the analysis result, the analysis result is output in a charting mode, so that certain requirements are made on the image display function of the terminal for displaying.

For example, the information item platform outputs the comparative analysis result of the user behavior data of users of mobile phones of multiple brands based on different item platforms as the comparative analysis basis, and different colors may be used for distinguishing data of different dimensions (for example, data of different dimensions correspond to different colors), so that if the color gamut used by the information item platform is different from the color gamut of the terminal device which finally displays the analysis result, the display distortion of the analysis comparison result may be caused, and even the corresponding colors of part of different data are the same.

For another example, when the designated dimension is large, the data that needs to be contrastively analyzed is also large, and then in order to be able to display more comprehensive data in one page, the information platform may display more contrastively analyzed results in the same page when outputting the contrastively analyzed results. However, the screen of the terminal device for subsequent display may be relatively small, and data display cannot be performed within a screen range, so that a user needs to continuously slide the interface to browse data outside the screen range.

Therefore, in order to improve the above problem, when the information platform outputs the contrastive analysis result, the information platform may first obtain the display characteristics of the terminal device to be output, and then determine the contrastive analysis effect according to the display characteristics of the terminal device to be output. For example, when the screen color gamut of the terminal device to be output is detected to be sRGB, the colors in the output contrastive analysis result are determined in the sRGB color gamut. If the size of the screen of the terminal device to be output is detected to be small, the comparison and analysis result is output in a paging mode, and then different display effects of the same comparison result can be achieved according to the display characteristics of the terminal device to be output, so that the analysis and comparison effect can be better displayed, and the display adaptability is improved.

According to the user behavior data processing method, the identification of the target device can be obtained firstly, then the user account corresponding to the identification of the target device is obtained, a plurality of target user accounts meeting characteristic conditions are determined from the user accounts, the user behavior data are analyzed based on the specified dimensionality, and an analysis result is output. Therefore, by the above method, after the user behavior data is acquired, the identifier of the target device can be determined first, and then the comparison result of the behavior data corresponding to the plurality of target user accounts of the target device can be output subsequently, so that the difference of the behavior data of different target device users can be output. In addition, in this embodiment of the application, the number of identifiers of the target device may also be obtained, when the number of identifiers of the target device is not multiple, the user behavior data is analyzed based on the specified dimension, and an analysis result is output, and if the number of identifiers of the target device is not multiple, behavior data of the specified dimension corresponding to the target user account corresponding to each identifier of the target device is obtained, so as to obtain multiple behavior parameters to be compared, the multiple behavior parameters to be compared are compared, and the analysis result is output, so that the flexibility of user portrait analysis and comparison is improved.

Referring to fig. 8, according to an embodiment of the present invention, an apparatus 400 for processing user behavior data includes:

a target device obtaining unit 410, configured to obtain an identifier of the target device.

As one mode, the target device obtaining unit 410 is specifically configured to obtain an identifier of a target device from a plurality of devices to be selected when receiving an analysis comparison instruction.

A behavior data obtaining unit 420, configured to obtain user behavior data corresponding to the target device.

As one mode, as shown in fig. 9, the behavior data acquiring unit 420 includes: a candidate user acquiring unit 421 and a target user acquiring unit 422.

The unit 421 is configured to obtain a user account corresponding to the identifier of the target device.

As one mode, the candidate user obtaining unit 421 is specifically configured to obtain, based on a network, first user behavior data stored by the user behavior data providing platform; and acquiring a user account corresponding to the identifier of the target device from the user account to which the first user behavior data belongs.

As another mode, the to-be-selected user obtaining unit 421 is specifically configured to obtain a user data packet uploaded from the client; and acquiring a user account corresponding to the identifier of the target device from the user data packet.

A target user obtaining unit 422, configured to determine, from the user accounts, a plurality of target user accounts that satisfy the characteristic condition.

And the data processing unit 440 is configured to analyze the user behavior data based on the specified dimension, and output an analysis result.

As one mode, as shown in fig. 10, the target device acquisition unit 410 includes:

and an identifier display subunit 411, configured to display a plurality of device brand identifiers to be selected.

An identifier determining subunit 412, configured to use a brand identifier determined from the multiple device brand identifiers to be selected as the identifier of the target device.

In this way, the identifier displaying subunit 411 is specifically configured to display model information corresponding to a brand identifier determined in the multiple to-be-selected device brand identifiers; an identifier determining subunit 412, configured to detect whether the model information is selected as the organic type information; and if no model information is selected, executing the brand identification determined from the multiple equipment brand identifications to be selected as the identification of the target equipment. The identifier determining subunit 412 is further specifically configured to, if the organic type information is selected, use the selected type information as an identifier of the target device.

As one manner, the data processing unit 440 is specifically configured to determine whether the number of identifiers of the target device is multiple based on the detection; and if the number of the identifiers of the target equipment is not multiple, analyzing the user behavior data based on the specified dimensionality and outputting an analysis result. The data processing unit 440 is further specifically configured to, if it is detected that there are multiple identifiers of the target device, obtain behavior data of a specified dimension corresponding to a target user account corresponding to each identifier of the multiple target devices, and obtain multiple behavior parameters to be compared; and comparing the behavior parameters to be compared and outputting an analysis result.

As one mode, as shown in fig. 11, the apparatus 400 further includes: the device to be selected acquisition unit 450 is configured to acquire an identifier of an accessed terminal when receiving an access request of the terminal; detecting whether the identification of the accessed terminal is stored or not; and if not, taking the identifier of the accessed terminal as a device to be selected. As a mode, the to-be-selected device acquisition unit 450 is specifically configured to use, as the target device, a device to be selected, which is ranked to meet a specified ranking position among the multiple devices to be selected; and acquiring the determined identification of the target device.

As one mode, the data processing unit 440 is specifically configured to obtain a dimension determined from a plurality of dimensions to be selected as a designated dimension; obtaining a chart display type; and comparing the behavior data corresponding to the plurality of target user accounts based on the specified dimensions, and generating a comparison analysis result displayed based on the chart display type. In this manner, each dimension corresponds to a specified chart presentation type. Correspondingly, the data processing unit 440 is specifically configured to obtain a chart display type corresponding to the specified dimension. Optionally, the data processing unit 440 is specifically configured to obtain a terminal model of the receiving end of the comparison analysis result; and acquiring a chart display type corresponding to the terminal model.

By one approach, the specified dimensions include at least one of the following dimensions: a preference dimension for a specified type of application; replacing the frequency dimension of the intelligent terminal; dietary preference dimension; and travel idiomatic dimension.

As one way, the characteristic conditions include at least one of the following conditions: the sex meets the specified sex; the age meets the specified age interval; professions meet a specified profession category;

regularly satisfying a designated area; and the family member category satisfies the specified category.

It should be noted that the device embodiment and the method embodiment in the present application correspond to each other, and specific principles in the device embodiment may refer to the contents in the method embodiment, which is not described herein again.

An electronic device provided by the present application will be described below with reference to fig. 12.

Referring to fig. 12, based on the user behavior data processing method, another electronic device 200 including a processor 104 capable of executing the user behavior data processing method is further provided in the embodiment of the present application. The electronic device 200 also includes a memory 104, and a network module 106. The memory 104 stores programs that can execute the content of the foregoing embodiments, and the processor 102 can execute the programs stored in the memory 104. The internal structure of the processor 102 may be as shown in fig. 1.

Processor 102 may include, among other things, one or more cores for processing data and a message matrix unit. The processor 102 interfaces with various components throughout the electronic device 200 using various interfaces and circuitry to perform various functions of the electronic device 200 and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 104 and invoking data stored in the memory 104. Alternatively, the processor 102 may be implemented in hardware using at least one of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 102 may integrate one or more of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a modem, and the like. Wherein, the CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing display content; the modem is used to handle wireless communications. It is understood that the modem may not be integrated into the processor 102, but may be implemented by a communication chip.

The Memory 104 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). The memory 104 may be used to store instructions, programs, code sets, or instruction sets. The memory 104 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing various method embodiments described below, and the like. The storage data area may also store data created by the terminal 100 in use, such as a phonebook, audio-video data, chat log data, and the like.

The network module 106 is configured to receive and transmit electromagnetic waves, and implement interconversion between the electromagnetic waves and electrical signals, so as to communicate with a communication network or other devices, for example, an audio playing device. The network module 106 may include various existing circuit elements for performing these functions, such as an antenna, a radio frequency transceiver, a digital signal processor, an encryption/decryption chip, a Subscriber Identity Module (SIM) card, memory, and so forth. The network module 106 may communicate with various networks, such as the internet, an intranet, a wireless network, or with other devices via a wireless network. The wireless network may comprise a cellular telephone network, a wireless local area network, or a metropolitan area network. For example, the network module 106 may interact with a base station.

Referring to fig. 13, a block diagram of a computer-readable storage medium according to an embodiment of the present application is shown. The computer-readable medium 1100 has stored therein program code that can be called by a processor to perform the method described in the above-described method embodiments.

The computer-readable storage medium 1100 may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. Alternatively, the computer-readable storage medium 1100 includes a non-volatile computer-readable storage medium. The computer readable storage medium 1100 has storage space for program code 810 to perform any of the method steps of the method described above. The program code can be read from or written to one or more computer program products. The program code 1110 may be compressed, for example, in a suitable form.

In summary, according to the user behavior data processing method, device, server and storage medium provided by the present application, the identifier of the target device may be obtained first, then the user account corresponding to the identifier of the target device is obtained, a plurality of target user accounts satisfying the characteristic conditions are determined from the user accounts, the user behavior data is analyzed based on the specified dimension, and the analysis result is output. Therefore, by the above method, after the user behavior data is acquired, the identifier of the target device can be determined first, and then the comparison result of the behavior data corresponding to the plurality of target user accounts of the target device can be output subsequently, so that the difference of the behavior data of different target device users can be output.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not necessarily depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.

Claims

A method for processing user behavior data, the method comprising:

acquiring an identifier of a target device;

acquiring user behavior data corresponding to the target equipment;

and analyzing the user behavior data based on the specified dimensionality and outputting an analysis result.
The method of claim 1, wherein the step of obtaining user behavior data corresponding to the target device comprises:

acquiring a user account corresponding to the identifier of the target device;

determining a plurality of target user accounts meeting characteristic conditions from the user accounts;

and acquiring user behavior data corresponding to the target user accounts.
The method according to claim 1 or 2, wherein the step of obtaining the identity of the target device comprises:

and responding to the search request, and taking the searched brand identification of the equipment as the identification of the target equipment.
The method of claim 3, wherein the step of using the searched device brand identity as the identity of the target device in response to the search request comprises:

responding to the search request, and displaying a plurality of searched device brand identifications to be selected;

and taking the brand identifier determined from the plurality of device brand identifiers to be selected as the identifier of the target device.
The method of claim 3, wherein the step of using the searched device brand identity as the identity of the target device in response to the search request comprises:

responding to the search request, and displaying a plurality of model identifications corresponding to the searched equipment brand identifications;

and taking the selected model identifier in the plurality of model identifiers as the identifier of the target device.
The method according to any of claims 2-5, wherein the step of obtaining the user account corresponding to the identity of the target device comprises:

acquiring first user behavior data stored by a user behavior data providing platform based on a network;

and acquiring a user account corresponding to the identifier of the target device from the user account to which the first user behavior data belongs.
The method according to any of claims 2-5, wherein the step of obtaining the user account corresponding to the identity of the target device comprises:

acquiring a user data packet uploaded from a client;

and acquiring a user account corresponding to the identifier of the target device from the user data packet.
The method of any of claims 1-7, wherein the user behavior data is analyzed based on a specified dimension, and the step of outputting the analysis result comprises:

detecting whether the identification of the target equipment is multiple;

and if the number of the identifiers of the target equipment is not multiple, analyzing the user behavior data based on the specified dimensionality and outputting an analysis result.
The method of claim 8, further comprising:

if the number of the identifiers of the target devices is detected to be multiple,

acquiring behavior data of a designated dimension corresponding to a target user account corresponding to each identifier of the target equipment to obtain a plurality of behavior parameters to be compared;

and comparing the behavior parameters to be compared and outputting an analysis result.
The method according to any of claims 1-9, wherein the step of obtaining the identity of the target device comprises:

and when an analysis and comparison instruction is received, acquiring the identification of the target equipment from the multiple equipment to be selected.
The method of claim 10, wherein the method comprises:

when receiving an access request of a terminal, acquiring an identifier of the accessed terminal;

detecting whether the identification of the accessed terminal is stored or not;

and if not, taking the identifier of the accessed terminal as a device to be selected.
The method of claim 10, wherein the step of obtaining the identity of the target device from the plurality of devices to be selected comprises:

selecting the equipment to be selected, which meets the appointed sorting position in the plurality of equipment to be selected, as target equipment;

and acquiring the determined identification of the target device.
The method of claim 1, wherein the user behavior data is analyzed based on a specified dimension, and the step of outputting the analysis result comprises:

obtaining a dimension determined from a plurality of dimensions to be selected as a designated dimension;

obtaining a chart display type;

and comparing the behavior data corresponding to the plurality of target user accounts based on the specified dimensions, and generating a comparison analysis result displayed based on the chart display type.
The method of claim 13, wherein each dimension corresponds to a specified chart presentation type, and wherein the step of obtaining the chart presentation type comprises:

and acquiring a chart display type corresponding to the specified dimension.
The method of claim 13, wherein the step of obtaining the chart presentation type comprises:

acquiring the terminal model of a receiving end of the comparison analysis result;

and acquiring a chart display type corresponding to the terminal model.
The method according to any of claims 1-15, wherein the specified dimensions comprise at least one of the following dimensions:

a preference dimension for a specified type of application;

replacing the frequency dimension of the intelligent terminal;

dietary preference dimension; and

travel habitual way dimension.
The method according to any of claims 1-16, wherein the characteristic conditions comprise at least one of the following conditions:

the sex meets the specified sex;

the age meets the specified age interval;

professions meet a specified profession category;

regularly satisfying a designated area; and

the family member category satisfies the specified category.
A user behavior data processing apparatus, characterized in that the apparatus comprises:

a target device acquisition unit that acquires an identifier of a target device;

a behavior data acquiring unit, configured to acquire user behavior data corresponding to the target device;

and the data processing unit is used for analyzing the user behavior data based on the specified dimensionality and outputting an analysis result.
A server, comprising a processor and a memory; one or more programs are stored in the memory and configured to be executed by the processor to implement the methods of claims 1-17.
A computer-readable storage medium, having program code stored therein, wherein the program code when executed by a processor performs the method of any of claims 1-17.