CN113094582A

CN113094582A - Processing method and device and electronic equipment

Info

Publication number: CN113094582A
Application number: CN202110350175.5A
Authority: CN
Inventors: 罗蒙; 田翰华; 李振宁
Original assignee: Lenovo Beijing Ltd
Current assignee: Lenovo Beijing Ltd
Priority date: 2021-03-31
Filing date: 2021-03-31
Publication date: 2021-07-09

Abstract

The embodiment of the application discloses a processing method, a processing device and electronic equipment, wherein the processing method comprises the following steps: if the recommended content is determined to be output to the target user, obtaining usage data of at least two electronic devices associated with the target user; determining user profile information of the target user at least according to the usage data, and outputting target recommended content at a target electronic device at least according to the user profile information; the at least two electronic devices can establish an association relationship through different association modes. The portrait of the target user is more accurate, and the recommended content is more in line with the interests and hobbies of the user, so that the user experience is improved.

Description

Processing method and device and electronic equipment

Technical Field

The present application relates to a user identification technology based on an electronic device, and in particular, to a processing method and apparatus for implementing user portrait determination based on device identification, and an electronic device.

Background

The prior user portrait recommendation system identifies users by using Device Identifiers (DIDs), and performs related content recommendation according to the user portrait corresponding to the DIDs, but because the DIDs are obtained by performing hash operation on hardware Serial Numbers (SNs) and belong to unique identifiers of hardware devices, the method can only perform portrait recommendation and content recommendation on a single device, and because of different use habits of users, user portraits which can be obtained by two devices of the same user are incomplete, so that the consistency of recommendation results on different devices of the same user is poor.

Disclosure of Invention

The technical scheme of the embodiment of the application is realized as follows:

according to a first aspect of embodiments of the present application, there is provided a processing method, including:

if the recommended content is determined to be output to the target user, obtaining usage data of at least two electronic devices associated with the target user;

determining user profile information of the target user at least according to the usage data, and outputting target recommended content at a target electronic device at least according to the user profile information;

the at least two electronic devices can establish an association relationship through different association modes.

As one implementation, the obtaining usage data of at least two electronic devices associated with the target user includes:

determining a first electronic device which has an affiliated relationship with the target user, determining electronic devices associated with the first electronic device according to at least association parameters between the first electronic device and second electronic devices in a target scene environment, and taking obtained usage data of the first electronic device and the electronic devices associated with the first electronic device as usage data of at least two electronic devices associated with the target user.

As an implementation manner, determining, according to at least an association parameter between the first electronic device and each second electronic device in a target scene environment, an electronic device associated therewith includes:

determining an electronic device associated with the first electronic device according to at least a first association parameter between the first electronic device and a second electronic device accessed and/or accessed in a network environment; or the like, or, alternatively,

determining electronic equipment associated with the first electronic equipment at least according to a second association parameter between the first electronic equipment and second electronic equipment, wherein the first electronic equipment and the second electronic equipment are both connected and/or connected with peripherals; or the like, or, alternatively,

and determining the electronic equipment associated with the first electronic equipment according to at least a third association parameter between the first electronic equipment and a second electronic equipment which shares and/or shares the account information of the target user with the first electronic equipment.

As an implementation manner, determining an electronic device associated with the first electronic device according to at least a first association parameter between the first electronic device and a second electronic device within a network environment accessed and/or accessed by the first electronic device includes:

acquiring first attribute information of a network accessed and/or accessed by first electronic equipment;

obtaining second attribute information of a second electronic device accessed and/or accessed to the network;

and determining the electronic equipment associated with the first electronic equipment according to the association parameter obtained by processing the first attribute information and the second attribute information according to the determined association algorithm.

As an implementation manner, determining an electronic device associated with the first electronic device according to at least a second association parameter between the first electronic device and a second electronic device includes:

obtaining first equipment information of a first peripheral connected with the first electronic equipment and/or established with the first electronic equipment;

obtaining second equipment information of a second peripheral connected with the second electronic equipment and/or established with the second electronic equipment;

and determining the electronic equipment associated with the first electronic equipment according to the matching parameter between the first equipment information and the second equipment information.

As an implementation manner, determining an electronic device associated with the first electronic device according to at least a third association parameter between the first electronic device and a second electronic device with which the first electronic device shares and/or shares account information of the target user, includes:

obtaining first account information logged in or logged in by the first electronic device;

obtaining second account information logged in or logged in by the second electronic device;

and determining the electronic equipment associated with the first electronic equipment according to the matching parameter between the first account information and the second account information.

As one implementation, determining user representation information for the target user based at least on the usage data includes:

and determining user portrait information of the target user according to the determined processing strategy according to the usage data and the association coefficient between the at least two electronic devices associated with the target user.

As an implementation manner, outputting target recommended content at a target electronic device according to at least the user portrait information includes:

determining electronic equipment having a target association relation with a target user as target electronic equipment from the current environment of the target user; and/or the presence of a gas in the atmosphere,

and determining target recommended content according to the user portrait information and the attribute information of the target electronic equipment, and outputting the target recommended content to the target user through the target electronic equipment.

According to a second aspect of embodiments of the present application, there is provided a processing apparatus including:

an obtaining unit configured to obtain usage data of at least two electronic devices associated with a target user if it is determined that recommended content is output to the target user;

a determination unit for determining user portrait information of the target user based at least on the usage data;

the output unit is used for outputting target recommended content on target electronic equipment at least according to the user portrait information;

According to a third aspect of embodiments of the present application, there is provided an electronic device comprising at least one processor and a memory for storing a computer program capable of running on the processor, the computer program being capable of performing the processing method when executed by the processor.

According to a fourth aspect of embodiments of the present application, there is provided a storage medium having stored thereon an executable program, the executable program being executed by a processor to perform the steps of the processing method.

The processing method and device and the electronic equipment determine the association degrees of the plurality of electronic equipment, determine the use data of at least two pieces of electronic equipment associated with a target user, image the target user according to the use data, determine the user portrait information of the target user, determine recommended content for the target user based on the user portrait information, and recommend the corresponding recommended content to the target user through the corresponding electronic equipment. The embodiment of the application determines the relevant parameters of the association degree more accurately, the portrait of the target user is more accurate, and the recommended content more conforms to the interests and hobbies of the user, so that the user experience is improved.

Drawings

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

FIG. 1 is a schematic flow chart of a processing method according to an embodiment of the present application;

FIG. 2 is a schematic flow chart of a processing method according to an embodiment of the present application;

FIG. 3 is a schematic diagram of a data collection and processing method according to an embodiment of the present application;

FIG. 4 is a schematic diagram of a structure of a processing apparatus according to an embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the accompanying 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 the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given in the present application without any inventive step, shall fall within the scope of protection of the present application. In the present application, the embodiments and features of the embodiments may be arbitrarily combined with each other without conflict. The steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions. Also, while a logical order is shown in the flow diagrams, in some cases, the steps shown or described may be performed in an order different than here.

The present application will be described in further detail with reference to the following drawings and specific embodiments.

Fig. 1 is a schematic flow chart of a processing method according to an embodiment of the present application, and as shown in fig. 1, the processing method according to the embodiment of the present application includes the following processing steps:

step 101, if it is determined that recommended content is output to a target user, usage data of at least two electronic devices associated with the target user is obtained.

In the embodiment of the application, when it is determined that the corresponding recommended content needs to be output to the target user, the usage data of at least two electronic devices related to the target user needs to be determined. Specifically, the obtaining of the usage data of at least two electronic devices associated with the target user includes:

determining a first electronic device having an affiliated relationship with the target user, determining electronic devices associated with the first electronic device according to at least association parameters between the first electronic device and second electronic devices in a target scene environment, and taking obtained usage data of the first electronic device and the electronic devices associated with the first electronic device as usage data of at least two electronic devices associated with the target user.

In the embodiment of the application, the target scene environment includes a communication environment including a WIFI communication connection, a bluetooth connection and other communication environments. The associated parameters include account number or connected network equipment parameters and the like.

In an embodiment of the present application, determining, according to at least an association parameter between the first electronic device and each second electronic device in a target scene environment, an electronic device associated with the first electronic device includes:

determining an electronic device associated with the first electronic device according to at least a first association parameter between the first electronic device and a second electronic device accessed and/or accessed in a network environment; here, the first correlation parameter may be identification information of a WIFI network or a set local area network, and when it is determined that network parameters in a network environment to which the plurality of electronic devices access are the same or that the plurality of electronic devices access the same local area network or a private wireless network, it is determined that a probability that the plurality of electronic devices belong to the same user is very high.

Determining electronic equipment associated with the first electronic equipment at least according to a second association parameter between the first electronic equipment and second electronic equipment, wherein the first electronic equipment and the second electronic equipment are both connected and/or connected with peripherals; the second association parameter here includes a device identifier, and when the peripheral device is a bluetooth headset and multiple electronic devices are all connected to the bluetooth headset, the multiple electronic devices are more likely to belong to the same user.

And determining the electronic equipment associated with the first electronic equipment according to at least a third association parameter between the first electronic equipment and a second electronic equipment which shares and/or shares the account information of the target user with the first electronic equipment. The third association parameter includes the association degree of the logged account information, and when the accounts logged in by the user on different electronic devices are similar or the same, the possibility that different electronic devices belong to the same user is high.

Specifically, when at least two electronic devices access the same electronic device, the probability of the electronic devices belonging to the same target user is relatively high. In a practical application scenario, if two devices are found to be connected to the same mobile phone or bluetooth headset at the same time, the probability that the two devices belong to the same user is high. The method comprises the steps of collecting device hardware information of a plurality of electronic devices connected with a mobile phone or a Bluetooth headset, and carrying out related analysis based on the hardware information.

In the embodiment of the application, the probability that the multiple devices belong to the target user is assisted and judged through the user name similarity of the user login system.

In the embodiment of the application, for determining that a plurality of electronic devices belong to the same user, whether the plurality of electronic devices belong to the same user can be determined according to the attributes of the access network, the private connection of the electronic devices to the plurality of electronic devices, the login of the same or similar account numbers on the plurality of electronic devices, and the like, so that the accuracy of the plurality of electronic devices of the same user is improved. Specifically, when the network accessed by the electronic device is a public network, a lower weighted value is set for the electronic device accessed to the same network; when the network accessed by the electronic equipment is a home network, setting a higher weighted value for the network accessed by the plurality of electronic equipment; for some special public SSIDs, the weight value is set to 0, that is, such electronic devices accessing to the network are directly filtered out, and the electronic devices are not considered to belong to the same user. For example, the access hotspot identifications accessed by a plurality of electronic devices are correlated, the identifications of the electronic devices with the same access hotspot are found, and the correlation degree of the electronic devices with the same access hotspot identification of the home network is set to α, where α may be 0.45.

And inquiring according to the client list corresponding to the identifier of each electronic device, finding out a plurality of electronic devices related to the client, and setting the degree of association as beta. That is, by searching for a user account, such as a communication account, a mail account, a web portal login account, etc., logged in to the electronic device, when the same account logs in to multiple electronic devices, it is highly likely that multiple electronic devices belong to the same user. β may be 0.7.

When the data related to a plurality of electronic devices accessed by a private electronic device such as a bluetooth headset is used, the possibility that the plurality of electronic devices belong to the same user is high. Therefore, the associated weights for a plurality of electronic devices accessed by the same electronic device, such as a bluetooth headset, may also be set to be larger. The degree of association is set to δ. δ may be 0.8.

And calculating a plurality of association degrees and respective weighting coefficients of the plurality of electronic devices accessed to the network, or the plurality of electronic devices of the same or similar login accounts, and the specific electronic device such as a Bluetooth headset, to obtain a final association coefficient relationship ═ α × weight _ alpha + β × weight _ beta + δ weight _ delta. Here, the weighting coefficient of each degree of association may be set empirically, such as may be set to 1, or to 0.2, 0.3, 0.5, and so on. And when the association coefficient is larger than the set threshold value, determining that the plurality of electronic devices belong to the same user.

And 102, determining user portrait information of the target user at least according to the use data, and outputting target recommended content on target electronic equipment at least according to the user portrait information.

In an embodiment of the present application, determining user image information of the target user at least according to the usage data includes:

After determining a plurality of associated electronic devices according to the association coefficient of the currently associated electronic device, integrating the user usage data reported by the plurality of devices, and generating a user image and a label based on the complete user device data, which are exemplified as follows:

for the accumulated digital data, such as the use time, the sum is generated by direct accumulation; for coefficient type data such as probability, a correlation degree weighting correction coefficient is used; for non-digital data, the confidence attribute is modified using the correlation coefficient.

In this embodiment, outputting the target recommendation content at the target electronic device at least according to the user profile information includes:

determining electronic equipment having a target association relation with a target user as target electronic equipment from the current environment of the target user; and determining target recommendation content according to the user portrait information and the attribute information of the target electronic equipment so as to output the target recommendation content to the target user through the target electronic equipment. The target recommended content includes that when the maximum number of times that a user logs in an APP is determined and the accumulated residence time on the APP is longest, the APP or related content with the maximum login number and the longest residence time is preferentially recommended to the target user.

Fig. 2 is a schematic flow chart of a processing method according to an embodiment of the present application, and as shown in fig. 2, the processing method according to the embodiment of the present application includes the following processing steps:

step 201, if it is determined that the recommended content is output to the target user, obtaining usage data of at least two electronic devices associated with the target user.

In the embodiment of the application, the target scene environment comprises a communication environment, including a WIFI communication connection, a Bluetooth connection and other communication environments. The associated parameters include account number or connected network equipment parameters and the like.

In the embodiment of the present application, at least two electronic devices associated with a target user are determined, and specifically, a plurality of associated electronic devices may be determined in the following manner.

Obtaining identifiers of networks accessed by the first equipment and the electronic equipment; determining the type of a network accessed by the first equipment and the number of electronic equipment which have the same network with the first equipment according to the identification; and obtaining a correlation parameter between the first equipment and each electronic equipment according to the network type and the number.

Or, obtaining identifiers of access devices connected to the first device and the electronic devices respectively; according to the identification of the access equipment, analyzing the similarity of the first equipment and the access equipment connected with each electronic equipment; and obtaining a correlation parameter between the first equipment and each electronic equipment according to the analysis result.

Or, performing similarity analysis on access information adopted between the first device and each electronic device; here, the access information includes account information and the like. And obtaining a correlation parameter between the first equipment and each electronic equipment according to the analysis result.

Step 202, determining user portrait information of the target user at least according to the usage data, and outputting target recommended content on the target electronic equipment at least according to the user portrait information.

In an embodiment of the present application, determining user portrait information includes: and determining user portrait information of the target user according to the use data and the association degree parameter between the first device and each electronic device associated with the target user. Specifically, obtaining a plurality of usage data with the same attribute in the first device and the electronic devices associated with the target user; analyzing each of the usage data having the same attribute; and integrating the analysis result and the association degree parameter to obtain the user portrait information of the target user.

Determining the target electronic device includes: obtaining the use information of the first device and each electronic device associated with the target user on each use data with the same attribute; and determining the target electronic equipment from the electronic equipment associated with the target user based on the use information.

The essence of the technical solution of the embodiments of the present application is further clarified below by specific examples.

Firstly, the embodiment of the application acquires user data through a data acquisition end, and records the MAC address and service set identification (ssid) of the current access hotspot (AP); specifically, the device list of the MAC Address information included in each electronic device in the current network may be obtained through an Address Resolution Protocol (ARP) and a port scanning manner.

After acquiring the information, sending the data to a data processing end (LUDP), and after receiving the acquired data, the data processing end performing user portrait and simultaneously performing the following calculation:

after the collected data is received, simple data cleaning and processing are performed, for example, the weighting value is set to be low for a public network, the weighting value can be set to be high for a home network, and some special public SSIDs can be directly filtered out. That is, for all the collected data, all the electronic devices accessing the same network are directly determined, for example, the electronic devices accessing the same network may be determined according to the network identifier, and the electronic devices accessing the same network may not access the network for one period. For the public network, even if a plurality of electronic devices are accessed simultaneously, the probability of belonging to the same user is low, and therefore, for the public network, a lower weighted value is set for the public network, that is, when whether the electronic devices belong to the same target user is determined by using the access network identifier, when the same network is accessed as the public network, the weighted value of the association parameter is low, and when the same network accessed by a plurality of electronic devices is a home network, the probability that a plurality of electronic devices accessed into the home network belong to the same user is high, and therefore, the probability that a plurality of electronic devices accessed into the home network belong to the same user is high compared with the public network.

And after the related data is acquired, correlating access hotspot fields in the acquired data, finding out the identifiers of the electronic devices with the same access hotspot, and setting the correlation degree of the same access hotspot as alpha.

And inquiring according to the client list corresponding to the identifier of each electronic device, finding out a plurality of electronic devices related to the client, and setting the degree of association as beta. That is, by searching for a user account, such as a communication account, a mail account, a web portal login account, etc., logged in to the electronic device, when the same account logs in to multiple electronic devices, it is highly likely that multiple electronic devices belong to the same user.

Specifically, it may be determined that a certain electronic device is connected to multiple electronic devices according to the identification information of the electronic device, for example, when the certain electronic device is a bluetooth headset, when the bluetooth headset is connected to multiple electronic devices, the multiple electronic devices may also have a higher possibility of belonging to the same user. Therefore, the associated weights for a plurality of electronic devices accessed by the same electronic device, such as a bluetooth headset, may also be set to be larger. Its degree of correlation is set to δ.

In the embodiment of the present application, when calculating the user portrait and the tag, according to the association coefficient of the other device associated with the current electronic device identifier, each item of data reported by the multiple devices of the user is integrated, and the user portrait and the tag based on the complete user device data are generated, for example: for the accumulated digital data, such as the use time, the sum is generated by direct accumulation; for coefficient type data such as probability, etc., a correlation-weighted correction coefficient is used; for non-digital data, the confidence attribute is modified using the correlation coefficient. The embodiment of the present application is only described as an example, and there may be other determination manners for determining the association degree of the related parameters of the electronic devices belonging to the same user, and the corresponding weighting coefficients may also be set as needed.

After the calculation is completed, the data is sent to a recommendation system for further processing, and after the steps are completed, the system should be basically consistent for the images generated by the same user on different devices due to the calculation of the correlation coefficient. And after the recommending system receives the recommending request, recommending the content according to the user portrait generated by the big data. The recommended content may be determined based on the habit of scheduling applications by users in a plurality of electronic devices, frequently scheduled applications, and the like, and the electronic device currently used or recently used by the user is taken as a target electronic device, and the corresponding recommended content is output to the user through the target electronic device. For example, when it is determined that the user opens the game more and uses the game for a longer time, the game-related content is preferentially recommended to the user. Or determining that the user logs in the shopping application website more times and stays for a longer time, preferentially recommending the shopping related information to the user, and specifically recommending the related content to the user according to the image of the user.

Fig. 4 is a schematic structural diagram of a processing apparatus according to an embodiment of the present application, and as shown in fig. 4, the processing apparatus according to the embodiment of the present application includes:

an obtaining unit 40 configured to obtain usage data of at least two electronic devices associated with a target user if it is determined that recommended content is output to the target user;

a determining unit 41 for determining user representation information of the target user at least from the usage data;

an output unit 42, configured to output a target recommendation content at a target electronic device at least according to the user profile information;

As an implementation manner, the obtaining unit 40 is further configured to:

As an implementation manner, the determining unit 41 is further configured to:

As an implementation, the output unit 42 is further configured to:

In the Processing apparatus of the embodiment of the application, the obtaining Unit 40, the determining Unit 41, the output Unit 42, and the like may be implemented by a Central Processing Unit (CPU), a Digital Signal Processor (DSP), a Micro Control Unit (MCU), or a Programmable Gate Array (FPGA) in the terminal in practical application.

It should be noted that, in the electronic device according to the embodiment of the present application, because the principle of solving the problem of the electronic device is similar to that of the control method, the implementation process and the implementation principle of the electronic device can be described by referring to the implementation process and the implementation principle of the method, and repeated details are not repeated.

An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is configured to, when executed by a processor, perform at least the steps of the foregoing processing method. The computer readable storage medium may be specifically a memory.

The embodiment of the application also provides the electronic equipment. Fig. 5 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application, and as shown in fig. 5, the electronic device according to the embodiment of the present application includes: a communication component 63 for data transmission, at least one processor 61 and a memory 62 for storing computer programs capable of running on the processor 61. The various components in the terminal are coupled together by a bus system 64. It will be appreciated that the bus system 64 is used to enable communications among the components. The bus system 64 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 64 in fig. 5.

Wherein the processor 61 executes at least the steps of the aforementioned processing method when executing the computer program.

It will be appreciated that the memory 62 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Enhanced Synchronous Dynamic Random Access Memory (Enhanced Synchronous Random Access Memory), Synchronous linked Dynamic Random Access Memory (DRAM), Direct Random Access Memory (DRDRDRD). The memory 62 described in the embodiments of the present application is intended to comprise, without being limited to, these and any other suitable types of memory.

The method disclosed in the above embodiments of the present application may be applied to the processor 61, or implemented by the processor 61. The processor 61 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 61. The processor 61 described above may be a general purpose processor, a DSP, or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. Processor 61 may implement or perform the methods, steps, and logic blocks disclosed in the embodiments of the present application. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed in the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in the memory 62, and the processor 61 reads the information in the memory 62 and performs the steps of the aforementioned processing method in conjunction with its hardware.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple 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 coupling, direct coupling or communication between the components shown or discussed may be through some interfaces, indirect coupling or communication between devices or units, and may be electrical, mechanical or other.

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, that is, 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, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a hardware form, and can also be realized in a form of hardware and a software functional unit.

Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

Alternatively, the integrated units described above in the present application may be stored in a computer-readable storage medium if they are implemented in the form of software functional modules and sold or used as independent products. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially implemented or portions thereof contributing to the prior art may be embodied in the form of a software product stored in a storage medium and including 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 methods described in the embodiments of the present application. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.

The methods disclosed in the several method embodiments provided in the present application may be combined arbitrarily without conflict to obtain new method embodiments.

Features disclosed in several of the product embodiments provided in the present application may be combined in any combination to yield new product embodiments without conflict.

The features disclosed in the several method or apparatus embodiments provided in this application may be combined in any combination to arrive at a new method or apparatus embodiment without conflict.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of processing, comprising:

2. The method of claim 1, the obtaining usage data for at least two electronic devices associated with the target user, comprising:

determining a first electronic device having an affiliated relationship with the target user, determining an electronic device associated with the first electronic device according to at least association parameters between the first electronic device and second electronic devices in a target scene environment, and taking obtained usage data of the first electronic device and the electronic device associated with the first electronic device as usage data of at least two electronic devices associated with the target user.

3. The method of claim 2, wherein determining the electronic device associated with the first electronic device according to at least an association parameter between the first electronic device and each second electronic device in the target scene environment comprises:

determining an electronic device associated with the first electronic device at least according to a first association parameter between the first electronic device and a second electronic device accessed and/or accessed in a network environment; or the like, or, alternatively,

4. The method of claim 3, wherein determining the electronic device associated therewith based at least on a first association parameter between the first electronic device and a second electronic device within a network environment to which the first electronic device is coupled and/or coupled comprises:

5. The method of claim 3, wherein determining an electronic device associated therewith based at least on a second association parameter between the first electronic device and a second electronic device comprises:

6. The method of claim 3, wherein determining the electronic device associated therewith based at least on a third association parameter between the first electronic device and a second electronic device with which the account information of the target user is shared and/or shared comprises:

7. The method of claim 1, wherein determining user representation information of the target user based at least on the usage data comprises:

8. The method of any of claims 1-7, wherein outputting target recommended content at a target electronic device based at least on the user representation information comprises:

9. A processing apparatus, comprising:

10. An electronic device comprising at least one processor and a memory for storing a computer program operable on the processor, the computer program being operable when executed by the processor to perform the processing method of any of claims 1 to 8.