Content recommendation method and apparatus, electronic device, and storage medium

Abstract

This application discloses a content recommendation method, apparatus, electronic device, and storage medium. The method includes: an electronic device acquiring the number of users within a target range, as well as the gender and age of each user; then determining the target number range to which the number of users belongs; further, determining a target combination method based on the target number range, and determining a target audience based on the target combination method, the number of users, and the gender and age of each user; finally, recommending corresponding content to the target audience. By identifying the number of users, their age, and gender, the main target audience is selected, and suitable content is recommended to the main target audience, thus improving the accuracy of content recommendation.

Description

Technical Field

[0001] This application relates to the field of data processing technology, specifically to a content recommendation method, apparatus, electronic device, and storage medium. Background Technology

[0002] In related technologies, with the rapid growth of online content, when users browse and watch content on electronic devices, the devices record the users' browsing and viewing history, thereby recommending corresponding content to the users.

[0003] However, when multiple users are using the electronic device, the device cannot recommend suitable content. Summary of the Invention

[0004] This application provides a content recommendation method, apparatus, electronic device, and storage medium. The content recommendation method improves the accuracy of content recommendations.

[0005] In a first aspect, embodiments of this application provide a content recommendation method, including:

[0006] Obtain the number of users within the target range, as well as the gender and age of each user;

[0007] Determine the target number range to which the number of users belongs;

[0008] The target combination method is determined based on the target quantity range, and the target population is determined based on the target combination method, the number of users, and the gender and age corresponding to each user;

[0009] Recommend relevant content to the target audience.

[0010] Secondly, embodiments of this application provide a content recommendation device, including:

[0011] The acquisition module is used to acquire the number of users within the target range, as well as the gender and age of each user;

[0012] The first determining module is used to determine the target quantity range to which the number of users belongs;

[0013] The second determining module is used to determine the target combination method based on the target quantity range, and to determine the target population based on the target combination method, the number of users, and the gender and age corresponding to each user;

[0014] The recommendation module is used to recommend corresponding content to the target audience.

[0015] Thirdly, embodiments of this application provide an electronic device, a memory storing executable program code, and a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the steps in the content recommendation method provided in embodiments of this application.

[0016] Fourthly, embodiments of this application provide a computer-readable storage medium storing a plurality of instructions adapted for loading by a processor to execute the steps in the content recommendation method provided in embodiments of this application.

[0017] In this embodiment, the electronic device acquires the number of users within a target range, as well as the gender and age of each user; then it determines the target number range to which the number of users belongs; next, it determines the target combination method based on the target number range, and determines the target audience based on the target combination method, the number of users, and the gender and age of each user; finally, it recommends corresponding content to the target audience. By identifying the number of users, their age, and their gender, the main target audience is selected, and suitable content is recommended to the main target audience, thus improving the accuracy of content recommendation. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a first flowchart illustrating the content recommendation method provided in the embodiments of this application.

[0020] Figure 2 This is a schematic diagram of the second process of the content recommendation method provided in the embodiments of this application.

[0021] Figure 3 This is a schematic diagram of the content recommendation device provided in the embodiments of this application.

[0022] Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] In related technologies, with the rapid growth of online content, when users browse and watch content on electronic devices, the devices record the users' browsing and viewing history, thereby recommending corresponding content to the users.

[0025] However, when multiple users are using the electronic device, the device cannot recommend suitable content.

[0026] To address this technical problem, embodiments of this application provide a content recommendation method, apparatus, electronic device, and storage medium. This content recommendation method can improve the accuracy of content recommendations.

[0027] It should be noted that this content recommendation method applies to electronic devices such as televisions, smartphones, computers, tablets, and head-mounted devices.

[0028] Please see Figure 1 , Figure 1 This is a first flowchart illustrating the content recommendation method provided in this application embodiment. The content recommendation method may include the following steps:

[0029] 110. Obtain the number of users within the target range, as well as the gender and age of each user.

[0030] In some implementations, the electronic device can acquire the number of users within a target range, such as within a range of 40 to 140 degrees in front of the electronic device.

[0031] After determining the number of users, the electronic device can use its camera to acquire facial images of each user, then generate facial key points for each user's face, and determine the user's age and gender based on the distribution of these key points. For example, men often have larger jawbones, so the gender of the user can be identified by using facial key points corresponding to the positions of the upper and lower jawbones in the facial image.

[0032] Since children's faces are smaller than adults', the user's facial features can be identified by the area of ​​the facial key points. For example, if the area of ​​the facial key points is larger than a preset area, the user is an adult; if the area of ​​the facial key points is smaller than the preset area, the user is a child.

[0033] In some implementations, the user's age can also be identified based on facial key points. For example, elderly users have droopy eyelids, while young users have firm eyelids. The user's age can be determined based on the facial key points corresponding to the eyelid area.

[0034] In some implementations, after obtaining the user's image, the user's age and gender can be determined based on relatively straightforward user characteristics. For example, users with hair longer than a preset length are female, and users with hair shorter than a preset length are male. The user's age can also be determined based on their clothing and appearance. These will not be listed exhaustively here.

[0035] In some implementations, the electronic device may also locally store the ages and genders of multiple preset users, and store the facial images, ages, and genders of these users in a user database. When there are multiple users within the target range of the electronic device, the facial images of these users can be input into the user database for matching, thereby obtaining the age and gender corresponding to each user.

[0036] 120. Determine the target number range to which the number of users belongs.

[0037] In some implementations, multiple quantity ranges can be preset, for example, each quantity range includes a different number of users.

[0038] Once the number of users is determined, the range of users can be determined, and this range can be set as the target range.

[0039] For example, if the number of users is 4, and the number of users corresponds to a range of 4-6, then the range of 4-6 is the target number range.

[0040] 130. Determine the target combination method based on the target quantity range, and determine the target audience based on the target combination method, the number of users, and the gender and age of each user.

[0041] In some implementations, if the target quantity range is a second preset quantity range, then the matrix arrangement is determined as the target combination method. Then, a target matrix is ​​generated based on the matrix arrangement, the number of users, and the gender and age of each user. Finally, the target population is determined based on the target matrix.

[0042] For example, electronic devices determine the first user in the same age range and the second user who does not have the same age range based on the target matrix. Then, multiple combinations of second user groups are generated based on the first user and the second user. Finally, the target user group is determined based on the multiple combinations of second user groups.

[0043] In some implementations, if the target quantity range is a first preset quantity range, the permutation and combination method is determined to be the target combination method.

[0044] Then, multiple primary user groups are generated based on the number of users and their permutations. Finally, the target audience is determined based on these primary user groups and the gender and age of each user.

[0045] 140. Recommend relevant content to the target audience.

[0046] In some implementations, after identifying the target audience, the age and gender of each target user within the target audience can be determined. Then, based on the age and gender, content that each target user likes can be identified, and then the content that each target user likes can be recommended to the target audience.

[0047] In some implementations, after recommending content to the target audience, the mapping between the target audience and their preferred content can be stored locally on the electronic device. The next time the electronic device determines that a user group is similar to the target audience, it can recommend that content to similar users.

[0048] In this embodiment, the electronic device acquires the number of users within a target range, as well as the gender and age of each user; then it determines the target number range to which the number of users belongs; next, it determines the target combination method based on the target number range, and determines the target audience based on the target combination method, the number of users, and the gender and age of each user; finally, it recommends corresponding content to the target audience. By identifying the number of users, their age, and their gender, the main target audience is selected, and suitable content is recommended to the main target audience, thus improving the accuracy of content recommendation.

[0049] For a more detailed understanding of the content recommendation method provided in the embodiments of this application, please refer to [link / reference]. Figure 2 , Figure 2 This is a schematic diagram of the second process of the content recommendation method provided in this application embodiment. The content recommendation method may include:

[0050] 201. Obtain the number of users within the target range, as well as the gender and age of each user.

[0051] In some implementations, the electronic device can acquire the number of users within a target range, such as within a range of 40 to 140 degrees in front of the electronic device.

[0052] After determining the number of users, the electronic device can use its camera to acquire facial images of each user, then generate facial key points for each user's face, and determine the user's age and gender based on the distribution of these key points. For example, men often have larger jawbones, so the gender of the user can be identified by using facial key points corresponding to the positions of the upper and lower jawbones in the facial image.

[0053] Since children's faces are smaller than adults', the user's facial features can be identified by the area of ​​the facial key points. For example, if the area of ​​the facial key points is larger than a preset area, the user is an adult; if the area of ​​the facial key points is smaller than the preset area, the user is a child.

[0054] In some implementations, the user's age can also be identified based on facial key points. For example, elderly users have droopy eyelids, while young users have firm eyelids. The user's age can be determined based on the facial key points corresponding to the eyelid area.

[0055] In some implementations, after obtaining the user's image, the user's age and gender can be determined based on relatively straightforward user characteristics. For example, users with hair longer than a preset length are female, and users with hair shorter than a preset length are male. The user's age can also be determined based on their clothing and appearance. These will not be listed exhaustively here.

[0056] In some implementations, the electronic device may also locally store the ages and genders of multiple preset users, and store the facial images, ages, and genders of these users in a user database. When there are multiple users within the target range of the electronic device, the facial images of these users can be input into the user database for matching, thereby obtaining the age and gender corresponding to each user.

[0057] 202. If the target quantity range is the first preset quantity range, generate multiple first group combinations based on the number of users and the permutation and combination method.

[0058] For example, if the first preset quantity range is 1-3, then the corresponding first group combination is: S=2 n -1, where S is the number of first-group combinations and n is the number of users. When the number of users is 3, the corresponding number of first-group combinations is 7. For example, if there are users A, B, and C, then there are a total of 7 first-group combinations: {A, B, C, AB, AC, BC, ABC}.

[0059] 203. Determine the target audience based on multiple first-person group combinations and the gender and age of each user.

[0060] Once multiple initial user groups are identified, the electronic device can determine the target audience based on each user's gender and age. For example, if there is only one user in the initial user group, a weight value can be determined for that user by defining their age and gender. If there are multiple users in the initial user group, such as user A and user C, a first weight value can be determined for user A based on their age and gender, and a second weight value can be determined for user C based on their age and gender. Then, a first coefficient corresponding to the first weight value and a second coefficient corresponding to the second weight value are determined.

[0061] Multiply the first coefficient by the first weight value, and then add the second coefficient multiplied by the second weight value to obtain the weight value of the first population combination AC.

[0062] This method allows us to determine the weight values ​​of multiple first-group combinations and identify the first-group combination with the highest weight value as the target group.

[0063] 204. If the target quantity range is the second preset quantity range, generate a target matrix based on the matrix arrangement, the number of users, and the gender and age of each user.

[0064] If the target quantity range is the second preset quantity range, for example, the second preset quantity range is 4-10, then the target matrix can be generated by matrix method, the number of users and the gender and age of each user.

[0065] The details are shown in Table 1:

[0066] A(male) B (female) C (Male) D (Female) E(male) 1-10 1 1 11-20 1 21-30 31-40 1 1 41-50 ＞51

[0067] Table 1

[0068] The horizontal arrangement of the matrix represents different users and their corresponding genders, while the vertical arrangement represents the age range of the users.

[0069] 205. Based on the target matrix, identify the first user within the same age range and the second user without a user within the same age range.

[0070] In some implementations, as shown in Table 1, A and B are first users in the same age range, C and D are first users in the same age range, and E is a second user who does not have users in the same age range.

[0071] This method can then be used to determine the first and second users among multiple users.

[0072] 206. Generate multiple second-person group combinations based on the first user and the second user.

[0073] After identifying the first user and the second user, multiple second user groups can be generated based on the first user and the second user.

[0074] For example, users within the same age range are identified as a second group, and users without a corresponding age range are identified as another second group. As shown in Table 1, the identified second group combinations are: AB, CD, and E.

[0075] Multiple first users can also be permuted and combined to obtain multiple second user groups. For example, the known second user group combinations are: AB, AC, AD, BC, BD.

[0076] 207. Determine the target population based on multiple combinations of secondary population groups.

[0077] In some implementations, the historical viewing time for multiple users can be determined, thereby determining the total historical viewing time for each user. Then, the weight of each user's historical viewing time in the total viewing time can be determined.

[0078] For example, if C watches for a total of 2 hours, D watches for a total of 3 hours, E watches for a total of 1 hour, and A and B watch for a total of 1 hour, then C's weight is 2 / 8, D's weight is 3 / 8, and E, A, and B's weight is 1 / 8.

[0079] Then, obtain the weight value corresponding to each second group combination, and select the second group combination with the largest weight value as the target group. For example, calculate the weight value corresponding to each second group combination. If the weight value corresponding to combination CD is 5 / 8, and combination CD has the largest weight value, then the second group combination CD is determined to be the target group.

[0080] 208. Recommend relevant content to the target audience.

[0081] In some implementations, after identifying the target audience, the age and gender of each target user within the target audience can be determined. Then, based on the age and gender, content that each target user likes can be identified, and then the content that each target user likes can be recommended to the target audience.

[0082] In some implementations, after recommending content to the target audience, the mapping between the target audience and their preferred content can be stored locally on the electronic device. The next time the electronic device determines that a user group is similar to the target audience, it can recommend that content to similar users.

[0083] In this embodiment, by obtaining the number of users within a target range, as well as the gender and age of each user, if the target range is a first preset range, multiple first group combinations are generated based on the number of users and their permutation and combination. The target group is then determined based on the multiple first group combinations and the gender and age of each user.

[0084] If the target number range is a second preset number range, a target matrix is ​​generated based on the matrix arrangement, the number of users, and the gender and age of each user. The first group of users within the same age range is identified based on the target matrix, and the second group of users without a corresponding age range is identified. Multiple second-group combinations are generated based on the first and second users. The target group is then determined based on these multiple second-group combinations.

[0085] Finally, relevant content is recommended to the target audience. This achieves accurate content recommendation for the target audience.

[0086] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of the content recommendation device provided in an embodiment of this application. The content recommendation device includes:

[0087] The acquisition module 310 is used to acquire the number of users within the target range, as well as the gender and age of each user.

[0088] The first determining module 320 is used to determine the target quantity range to which the number of users belongs.

[0089] The second determining module 330 is used to determine the target combination method according to the target quantity range, and to determine the target population according to the target combination method, the number of users, and the gender and age corresponding to each user.

[0090] The second determining module 330 is further configured to determine the matrix arrangement as the target combination method if the target quantity range is a second preset quantity range.

[0091] The second determining module 330 is further configured to generate a target matrix based on the matrix arrangement, the number of users, and the gender and age of each user.

[0092] The target population is determined based on the target matrix.

[0093] The second determining module 330 is further configured to determine, based on the target matrix, a first user within the same age range and a second user without users within the same age range;

[0094] Multiple second user group combinations are generated based on the first user and the second user;

[0095] The target population is determined based on the combination of the multiple second population groups.

[0096] The second determining module 330 is further configured to determine the permutation and combination method as the target combination method if the target quantity range is a first preset quantity range.

[0097] The second determining module 330 is also used to generate multiple first group combinations based on the number of users and the permutation and combination method;

[0098] The target population is determined based on the multiple first-group combinations and the gender and age of each user.

[0099] The recommendation module 340 is used to recommend corresponding content to the target audience.

[0100] In this embodiment, the electronic device acquires the number of users within a target range, as well as the gender and age of each user; then it determines the target number range to which the number of users belongs; next, it determines the target combination method based on the target number range, and determines the target audience based on the target combination method, the number of users, and the gender and age of each user; finally, it recommends corresponding content to the target audience. By identifying the number of users, their age, and their gender, the main target audience is selected, and suitable content is recommended to the main target audience, thus improving the accuracy of content recommendation.

[0101] Accordingly, embodiments of this application also provide an electronic device, such as... Figure 4 As shown, the electronic device may include components such as an input unit 401, a display unit 402, a memory 403 including one or more computer-readable storage media, a sensor 405, a processor 404 including one or more processing cores, and a power supply 406. Those skilled in the art will understand that... Figure 4 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:

[0102] Input unit 401 can be used to receive input digital or character information, and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control. Specifically, in one embodiment, input unit 401 may include a touch-sensitive surface and other input devices. A touch-sensitive surface, also known as a touch display or touchpad, can collect user touch operations on or near it (e.g., user operations using fingers, styluses, or any suitable object or accessory on or near the touch-sensitive surface) and drive corresponding connection devices according to a pre-set program. Optionally, the touch-sensitive surface may include a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, transmitting the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, sends it to the processor 404, and can receive and execute commands from the processor 404. Furthermore, various types of touch-sensitive surfaces, such as resistive, capacitive, infrared, and surface acoustic wave, can be used. In addition to the touch-sensitive surface, input unit 401 may also include other input devices. Specifically, other input devices may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc.

[0103] Display unit 402 can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces of electronic devices. These graphical user interfaces can be composed of graphics, text, icons, video, and any combination thereof. Display unit 402 may include a display panel, optionally configured as a liquid crystal display (LCD), organic light-emitting diode (OLED), or similar form. Furthermore, a touch-sensitive surface may cover the display panel. When the touch-sensitive surface detects a touch operation on or near it, it transmits the information to processor 404 to determine the type of touch event. Subsequently, processor 404 provides corresponding visual output on the display panel according to the type of touch event. Although in Figure 4 In this context, the touch-sensitive surface and the display panel are two separate components for implementing input and output functions. However, in some embodiments, the touch-sensitive surface and the display panel can be integrated to achieve both input and output functions.

[0104] The memory 403 can be used to store software programs and modules. The processor 404 executes various functional applications and data processing by running the software programs and modules stored in the memory 403. The memory 403 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device (such as audio data, telephone directory, etc.). In addition, the memory 403 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 403 may also include a memory controller to provide access to the memory 403 by the processor 404 and the input unit 401.

[0105] The electronic device may also include at least one sensor 405, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display panel according to the ambient light level, and the proximity sensor can turn off the display panel and / or backlight when the electronic device is moved to the ear. As a type of motion sensor, a gravity acceleration sensor can detect the magnitude of acceleration in various directions (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that identify the posture of the electronic device (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometers, taps), etc. Other sensors that may be configured in the electronic device, such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, will not be described in detail here.

[0106] The processor 404 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 403, and by calling data stored in the memory 403, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. Optionally, the processor 404 may include one or more processing cores; preferably, the processor 404 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 404.

[0107] The electronic device also includes a power supply 406 (such as a battery) that supplies power to various components. Preferably, the power supply can be logically connected to the processor 404 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 406 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0108] Although not shown, the electronic device may also include a camera, Bluetooth module, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 404 in the electronic device loads the executable files corresponding to the processes of one or more applications into the memory 403 according to the following instructions, and the processor 404 runs the applications stored in the memory 403 to realize various functions:

[0109] Obtain the number of users within the target range, as well as the gender and age of each user;

[0110] Determine the target number range to which the number of users belongs;

[0111] The target combination method is determined based on the target quantity range, and the target population is determined based on the target combination method, the number of users, and the gender and age corresponding to each user;

[0112] Recommend relevant content to the target audience.

[0113] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0114] Therefore, embodiments of this application provide a computer-readable storage medium storing a plurality of instructions that can be loaded by a processor to execute steps in any of the content recommendation methods provided in embodiments of this application. For example, the instructions can execute the following steps:

[0115] Obtain the number of users within the target range, as well as the gender and age of each user;

[0116] Determine the target number range to which the number of users belongs;

[0117] The target combination method is determined based on the target quantity range, and the target population is determined based on the target combination method, the number of users, and the gender and age corresponding to each user;

[0118] Recommend relevant content to the target audience.

[0119] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0120] The computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0121] Since the instructions stored in the storage medium can execute the steps of any of the content recommendation methods provided in the embodiments of this application, the beneficial effects that any of the content recommendation methods provided in the embodiments of this application can achieve can be realized, as detailed in the preceding embodiments, and will not be repeated here.

[0122] The foregoing has provided a detailed description of a content recommendation method, apparatus, electronic device, and storage medium provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A content recommendation method, characterized in that, include: The number of users within the target range, as well as the gender and age of each user, are obtained; the target range is the range within a preset angle in front of the electronic device. Determine the target number range to which the number of users belongs; The target combination method is determined based on the target quantity range, and the target population is determined based on the target combination method, the number of users, and the gender and age corresponding to each user; Recommend corresponding content to the target audience; The step of determining the target combination method based on the target quantity range includes: If the target quantity range is within the second preset quantity range, then the matrix arrangement is determined to be the target combination method; If the target quantity range is within the first preset quantity range, then the permutation and combination method is determined to be the target combination method; the first preset quantity range is less than the second preset quantity range; The step of determining the target population based on the target combination method, the number of users, and the gender and age of each user includes: A target matrix is ​​generated based on the matrix arrangement, the number of users, and the gender and age of each user. Based on the target matrix, identify the first user within the same age range and the second user who does not have a user within the same age range; Multiple second user group combinations are generated based on the first user and the second user; The target population is determined based on the multiple combinations of second population groups; The step of generating multiple second user groups based on the first user and the second user includes: The first users within the same age range are identified as a second group, and the second users without the same age range are identified as a second group, or multiple first users are arranged and combined to obtain multiple second group combinations.

2. The content recommendation method according to claim 1, characterized in that, Determining the target population based on the multiple combinations of second population groups includes: Obtain the weight value corresponding to each of the second group of people; The second group of people with the largest weight value is selected as the target group.

3. The content recommendation method according to claim 1, characterized in that, The step of determining the target population based on the target combination method, the number of users, and the gender and age of each user includes: Multiple first-group combinations are generated based on the number of users and the permutation and combination method; The target population is determined based on the multiple first-group combinations and the gender and age of each user.

4. A content recommendation device, characterized in that, include: The acquisition module is used to acquire the number of users within a target range, as well as the gender and age of each user; the target range is a range within a preset angle in front of the electronic device; The first determining module is used to determine the target quantity range to which the number of users belongs; The second determining module is used to determine the target combination method based on the target quantity range, and to determine the target population based on the target combination method, the number of users, and the gender and age corresponding to each user; The recommendation module is used to recommend corresponding content to the target audience; The second determining module is also used for: If the target quantity range is within the second preset quantity range, then the matrix arrangement is determined to be the target combination method; If the target quantity range is within the first preset quantity range, then the permutation and combination method is determined to be the target combination method; the first preset quantity range is less than the second preset quantity range; The second determining module is also used for: A target matrix is ​​generated based on the matrix arrangement, the number of users, and the gender and age of each user. Based on the target matrix, identify the first user within the same age range and the second user who does not have a user within the same age range; Multiple second user group combinations are generated based on the first user and the second user; The target population is determined based on the multiple combinations of second population groups; The second determining module is also used for: The first users within the same age range are identified as a second group, and the second users without the same age range are identified as a second group, or multiple first users are arranged and combined to obtain multiple second group combinations.

5. An electronic device, characterized in that, include: A memory storing executable program code, and a processor coupled to the memory; The processor invokes the executable program code stored in the memory to perform the steps in the content recommendation method as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The storage medium stores a plurality of instructions adapted for loading by a processor to execute the steps of the content recommendation method according to any one of claims 1 to 3.

Images