Resource recommendation method and device, electronic equipment and computer readable storage medium

Abstract

The embodiment of the invention discloses a resource recommendation method and device, electronic equipment and a computer readable storage medium. The method comprises the following steps: determining a plurality of face recognition results of a plurality of users; according to the multiple face recognition results, multiple groups of interested resources are determined, and each face recognition result in the multiple face recognition results corresponds to one group of interested resources; and determining a target recommendation resource according to the multiple groups of interested resources. According to the resource recommendation method provided by the embodiment of the invention, related resources which are commonly interested by a plurality of users can be recommended according to the face recognition results of the plurality of users.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of smart home technology, and specifically to a resource recommendation method, device, electronic device, and computer-readable storage medium. Background Art

[0002] With the continuous development of smart home devices, various smart home devices can adjust their own properties or parameters in real time according to user conditions. For example, smart TVs can obtain users' historical viewing records or pre-set preferred content based on their facial images, and recommend resources that users are interested in to enhance their viewing experience.

[0003] In the prior art, resource recommendations of smart TVs mainly rely on the user's historical viewing records and preference settings. However, this resource recommendation method is only applicable to a single user using a smart TV, and requires the user to manually set preferences and search in advance. When there are multiple users in front of the smart TV, the smart TV cannot recommend corresponding resources based on the preferences of multiple users.

[0004] Therefore, existing resource recommendation methods cannot perform resource recommendation when there are multiple users. Even if resource recommendation is performed, it is impossible to provide recommendation content that satisfies multiple users. Summary of the invention

[0005] Embodiments of the present application provide a resource recommendation method, device, electronic device, and computer-readable storage medium, which can recommend related resources of common interest to multiple users based on facial recognition results of multiple users.

[0006] In a first aspect, an embodiment of the present application provides a resource recommendation method, which is applied to a smart device, and the method includes:

[0007] determining multiple facial recognition results for multiple users;

[0008] Determine a plurality of groups of resources of interest according to the plurality of facial recognition results, each facial recognition result in the plurality of facial recognition results corresponding to a group of resources of interest;

[0009] According to the multiple groups of interesting resources, target recommended resources are determined.

[0010] Optionally, in some embodiments of the present application, determining target recommended resources according to the multiple groups of interesting resources includes:

[0011] Determine a resource category corresponding to each group of interesting resources in the multiple groups of interesting resources;

[0012] The target recommended resources are determined according to multiple groups of resource categories.

[0013] Optionally, in some embodiments of the present application, when the same resource category exists in the multiple groups of resource categories, determining the target recommended resource according to the multiple groups of resource categories includes:

[0014] Determine that the target recommended resource is a resource of interest corresponding to the same resource category.

[0015] Optionally, in some embodiments of the present application, when there is no identical resource category in the multiple groups of resource categories, determining the target recommended resource according to the multiple groups of resource categories includes:

[0016] Determine the intersection category of every two different groups of resource categories in the multiple groups of resource categories;

[0017] The target recommended resource is determined according to the cross-category.

[0018] Optionally, in some embodiments of the present application, when there are resources to be recommended in the cross-category, determining the target recommended resource according to the cross-category includes:

[0019] The target recommended resource is determined to be the resource to be recommended.

[0020] Optionally, in some embodiments of the present application, when there is no resource to be recommended in the cross-category, determining the target recommended resource according to the cross-category includes:

[0021] Determine a first resource category and a second resource category corresponding to the cross-category;

[0022] determining a first recommended resource according to the first resource category, and determining a second recommended resource according to the second resource category;

[0023] The target recommended resource is determined to be the first recommended resource and the second recommended resource.

[0024] Optionally, in some embodiments of the present application, determining multiple groups of interesting resources according to the multiple facial recognition results includes:

[0025] Determining multiple identity information of the multiple users according to the multiple facial recognition results;

[0026] Obtain a resource record corresponding to each piece of identity information in the plurality of identity information;

[0027] The multiple groups of interesting resources are determined according to the resource records.

[0028] In a second aspect, an embodiment of the present application further provides a resource recommendation device, which is applied to a smart device, and the device includes:

[0029] A processing module, configured to determine a plurality of facial recognition results for a plurality of users;

[0030] The processing module is further used to determine multiple groups of interesting resources based on the multiple facial recognition results, each facial recognition result in the multiple facial recognition results corresponds to a group of interesting resources;

[0031] The processing module is further configured to determine target recommended resources based on the multiple groups of interesting resources.

[0032] Optionally, in some embodiments of the present application, the processing module is further used to:

[0033] Determine a resource category corresponding to each group of interesting resources in the multiple groups of interesting resources;

[0034] The target recommended resources are determined according to multiple groups of resource categories.

[0035] Optionally, in some embodiments of the present application, the processing module is further used to:

[0036] Determine that the target recommended resource is a resource of interest corresponding to the same resource category.

[0037] Optionally, in some embodiments of the present application, the processing module is further used to:

[0038] Determine the intersection category of every two different groups of resource categories in the multiple groups of resource categories;

[0039] The target recommended resource is determined according to the cross-category.

[0040] Optionally, in some embodiments of the present application, the processing module is further used to:

[0041] The target recommended resource is determined to be the resource to be recommended.

[0042] Optionally, in some embodiments of the present application, the processing module is further used to:

[0043] Determine a first resource category and a second resource category corresponding to the cross-category;

[0044] determining a first recommended resource according to the first resource category, and determining a second recommended resource according to the second resource category;

[0045] The target recommended resource is determined to be the first recommended resource and the second recommended resource.

[0046] Optionally, in some embodiments of the present application, the processing module is further used to:

[0047] Determining multiple identity information of the multiple users according to the multiple facial recognition results;

[0048] Obtain a resource record corresponding to each piece of identity information in the plurality of identity information;

[0049] The multiple groups of interesting resources are determined according to the resource records.

[0050] In a third aspect, an embodiment of the present application further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps in the above-mentioned resource recommendation method when executed by the processor.

[0051] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps in the above-mentioned resource recommendation method are implemented.

[0052] In a fifth aspect, the embodiments of the present application further provide a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. The processor of the computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the method provided in various optional implementations described in the embodiments of the present application.

[0053] In summary, the embodiments of the present application determine multiple facial recognition results for multiple users; determine multiple groups of resources of interest based on the multiple facial recognition results, each facial recognition result in the multiple facial recognition results corresponds to a group of resources of interest; and determine a technical solution for target recommended resources based on the multiple groups of resources of interest. It is possible to recommend related resources of common interest to multiple users based on the facial recognition results of multiple users, thereby achieving the technical effect of accurately recommending resources of common interest to multiple users based on the content of interest to multiple users, thereby improving the user viewing experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0055] Figure 1 is a scenario diagram of a resource recommendation method provided in an embodiment of the present application;

[0056] Figure 2is a schematic diagram of a scenario in which a smart device according to an embodiment of the present application executes the resource recommendation method;

[0057] Figure 3 It is a schematic diagram of the overall process of the resource recommendation method corresponding to the resource recommendation method provided in the embodiment of the present application;

[0058] Figure 4 is a schematic diagram of the structure of a resource recommendation device provided in an embodiment of the present application;

[0059] Figure 5 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in this application to clearly and completely describe the technical solutions in this application. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments in the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0061] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the above features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0062] In this application, the word "exemplary" is used to mean "serving as an example, illustration, or illustration." Any embodiment described in this application as "exemplary" is not necessarily to be construed as being preferred or advantageous over other embodiments. The following description is given to enable any person skilled in the art to implement and use the invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the invention can be implemented without using these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in this application.

[0063] First, the terms involved in this application are explained:

[0064] Eye tracking: Eye Tracking is a technology that tracks the user's eye movements to determine their gaze point. This technology uses specialized hardware (such as infrared cameras) and software algorithms to capture and analyze eye movement trajectories.

[0065] Pose Recognition: Pose Recognition is a technology that detects and interprets human body postures through computer vision technology. It usually uses cameras and machine learning algorithms to identify user body parts and determine their relative positions and movement trajectories.

[0066] Smart Gimbal Connectivity: Smart Gimbal Connectivity refers to the technology of interconnecting the smart gimbal with other devices (such as cameras, smart phones, tablets, etc.) to achieve remote control, data transmission and device collaboration through the network.

[0067] Face recognition: The process of identifying and verifying a person's face through computer technology. It uses image processing and pattern recognition algorithms to analyze the features of a person's face and compare it with pre-stored face templates. Face recognition technology can be applied in many fields, including security monitoring, identity authentication, human-computer interaction, etc.

[0068] The embodiment of the present application provides a resource recommendation method, device, electronic device and computer-readable storage medium. Specifically, the embodiment of the present application provides a resource recommendation device applicable to the resource recommendation method, the resource recommendation device includes a smart device and a processor of the smart device, and the smart device can be a TV, a mobile phone, a tablet, a computer, etc.

[0069] In the prior art, resource recommendation strategies for smart devices are becoming more and more diverse. Many smart device manufacturers have improved traditional resource recommendation strategies. The improved resource recommendation strategies can more accurately recommend relevant resources to users based on their viewing history and preference settings.

[0070] For example, most existing resource recommendation methods determine the user identity based on the acquired user image, and recommend resources based on the viewing history, search history, and pre-set preferences or likes of the identity.

[0071] However, existing resource recommendation methods are unable to recommend resources of possible common interest to multiple users when there are multiple users in front of the screen of a smart device.

[0072] Therefore, the resource recommendation method in the prior art has the problem that the intelligent level of multi-user mode recommendation is low and it is impossible to recommend mutually satisfactory resources to multiple viewing users at the same time.

[0073] The embodiment of the present application provides a resource recommendation method, device, electronic device and computer-readable storage medium. The method adopts a technical solution of determining multiple facial recognition results of multiple users; determining multiple groups of interesting resources based on the multiple facial recognition results, each facial recognition result in the multiple facial recognition results corresponds to a group of interesting resources; and determining target recommended resources based on the multiple groups of interesting resources.

[0074] In summary, the resource recommendation method in the embodiment of the present application can recommend related resources of common interest to multiple users based on the facial recognition results of multiple users, thereby achieving the technical effect of accurately recommending resources of common interest to multiple users based on the content of interest to multiple users, thereby improving the user viewing experience.

[0075] It should be noted that the order of description of the following embodiments is not intended to limit the priority order of the embodiments.

[0076] See also Figure 1 , Figure 1The scene diagram of the resource recommendation method provided in the embodiment of the present application is as follows. The resource recommendation system may include a smart device 100, a shooting module 200 and a processor 501. The smart device 100, the shooting module 200 and the processor 501 may be connected to each other in any manner, including but not limited to signal communication through electronic circuits, communication through wireless signals, and the wireless signals may be computer network communications of the TCP / IP protocol suite (TCP / IP Protocol Suite, TCP / IP) and the User Datagram Protocol (UDP). The smart device 100 may receive control signals from a remote controller or a control panel, and the smart device 100 may also receive instruction information sent by the processor 501. The smart device 100 may perform corresponding operations according to the corresponding instruction information. Accordingly, the shooting module 200 may also receive control signals from a remote controller or a control panel, and the shooting module 200 may also receive instruction information sent by the processor 501. The shooting module 200 may perform corresponding operations according to the corresponding instruction information, such as the resource recommendation method in the present application.

[0077] In the embodiment of the present application, the smart device 100 includes but is not limited to a television, a mobile phone, a tablet, a computer, etc.

[0078] Those skilled in the art will understand that Figure 1 The application environment shown in the figure is only one application scenario of the present application solution and does not constitute a limitation on the application scenario of the present application solution. Other application environments may also include Figure 1 More or fewer smart devices as shown in Figure 1 Only one smart device is shown, and no specific limitation is given here.

[0079] In addition, if Figure 1 As shown, the processor 501 may include any hardware device capable of performing data processing and instruction sending, such as a CPU or a single-chip microcomputer embedded in the smart device, and the specific details are not limited here.

[0080] In addition, if Figure 1 As shown, the shooting module 200 may include any hardware device capable of acquiring images, such as a camera embedded in a smart device, and the specifics are not limited here.

[0081] It should be noted that Figure 1The scenario diagram of the resource recommendation system shown is only an example. The resource recommendation system and scenario described in the embodiment of the present application are intended to more clearly illustrate the technical solution of the embodiment of the present application, and do not constitute a limitation on the technical solution provided in the embodiment of the present application. Ordinary technicians in this field can know that with the evolution of the resource recommendation system and the emergence of new business scenarios, the technical solution provided in the embodiment of the present application is also applicable to similar technical problems.

[0082] For details, please refer to Figure 2 , Figure 2 : is a schematic diagram of a scenario in which a smart device according to an embodiment of the present application executes the resource recommendation method, wherein the specific execution process of the smart device executing the resource recommendation method is as follows:

[0083] S201: Determine multiple facial recognition results of multiple users.

[0084] In the embodiment of the present application, a visual algorithm can be used to recognize faces and automatically enter a preset user mode. For example, when a single user is recognized, a single-person recommendation mode is entered, and when two or more users are recognized, a multiple recommendation mode is entered.

[0085] As an optional embodiment, the user image in front of the smart device can be obtained in a variety of ways. For example, the smart TV uses a shooting module (camera) to capture the facial images of all users within a preset range in front of the TV screen, and uses a processor to recognize the facial images of all users to obtain multiple facial recognition results for multiple users.

[0086] Alternatively, if Figure 3 As shown in the overall flow diagram of the resource recommendation method, the user of the smart device can pre-enter facial images of different users and resources of interest to each user (or automatically enter the resources of interest corresponding to each user based on the viewing history of each user). After the smart device is started, in the resource recommendation mode, the face image can be captured by the shooting module and face recognition can be performed. According to the face recognition result, it is determined whether there are multiple users. If there is only a single user, the single-person recommendation mode can be entered. If there are multiple users, the multi-person recommendation mode can be entered.

[0087] Alternatively, Figure 3 As shown, after performing face recognition, the smart device can also combine eye and gesture recognition to determine whether there are other users who want to watch the smart device (or whether there are users who are not watching the smart device), and combine the recognition results of gesture recognition and eye tracking recognition to determine whether there are multiple users, and then enter single-person recommendation mode or multi-person recommendation mode (family sharing mode).

[0088] Alternatively, Figure 3As shown, the smart device can also combine eyeball and gesture recognition to determine whether there is no user watching the smart device. If the recognition result is that there is no user watching the smart device, the processor can control itself to enter the sleep mode, and collect facial images of all users within a preset range in front of the smart device screen in real time or periodically through the shooting module. If there is a user who wants to watch the smart device in the subsequently collected images, the processor can control itself to resume the resource being played before the sleep mode (resume broadcast), or enter other modes.

[0089] As an optional embodiment, it is possible to determine whether the user is looking directly at the TV screen by estimating the head posture, thereby determining whether the user is watching TV. It is also possible to determine whether the user is watching the TV screen by the degree of completeness and tilt angle of the face, thereby determining whether the user is watching TV. It is also possible to detect the position of the white of the eye and the pupil by eye tracking technology, determine the direction of the eyes, and determine whether the user is watching the screen.

[0090] S202: Determine multiple groups of interested data based on multiple facial recognition results.

[0091] In an embodiment of the present application, each facial recognition result among the multiple facial recognition results corresponds to a group of interesting resources; the interesting resources can be the preferences corresponding to the faces entered in advance by the user, or can be the interesting content obtained based on the viewing history corresponding to the faces entered in advance.

[0092] Optionally, the resource recommendation method provided in the embodiment of the present application also includes: determining multiple identity information of multiple users based on multiple facial recognition results; obtaining resource records corresponding to each identity information in the multiple identity information; and determining multiple groups of resources of interest based on the resource records.

[0093] In an embodiment of the present application, after the smart device is started, facial recognition results of multiple users are obtained through the shooting module and the processor, and then the identity information of the multiple users is determined based on the facial recognition results, and the resource records pre-stored for each identity information are obtained; and then multiple groups of interesting resources that can be recommended are determined based on the resource records of each user.

[0094] As an optional embodiment, if there is a new user (a user with no storage record) in the facial recognition results, the user's resources of interest can be temporarily ignored, or the resources of interest of other users can be obtained by combining smart cloud platform interconnection and other methods to determine the new user's resources of interest.

[0095] S203: Determine target recommended resources based on multiple groups of interesting resources.

[0096] In the embodiment of the present application, after it is determined that there are multiple users and the resources of interest to each user have been determined, the resources of interest to each user are analyzed to determine the target recommended resources for recommendation.

[0097] Optionally, the resource recommendation method provided in the embodiment of the present application further includes: determining a resource category corresponding to each group of interested resources in the multiple groups of interested resources; and determining a target recommended resource based on the multiple groups of resource categories.

[0098] In an embodiment of the present application, the resource category of each resource in the resources of interest to each user is first determined. For example, the categories included in the resources of interest to user one include comedy and emotion, and the categories included in the resources of interest to user two include drama and horror. Then, the target recommended resources can be determined based on the comedy, emotion, drama, and horror categories.

[0099] In the case that the same resource category exists in multiple groups of resource categories, optionally, the resource recommendation method provided in the embodiment of the present application further includes: determining that the target recommended resource is a resource of interest corresponding to the same resource category.

[0100] In the embodiment of the present application, if the categories included in the resources that user one is interested in are comedy and emotion, and the categories included in the resources that user two is interested in are drama and comedy, then the target recommended resource can be directly determined to be a comedy resource.

[0101] In the case where there are no identical resource categories in the multiple groups of resource categories, optionally, the resource recommendation method provided in the embodiment of the present application also includes: determining the intersection category of every two different groups of resource categories in the multiple groups of resource categories; and determining the target recommended resource based on the intersection category.

[0102] In the embodiment of the present application, if the categories included in the resources that user 1 is interested in are comedy and emotion, and the categories included in the resources that user 2 is interested in are drama and horror, then the cross-category of comedy and drama can be determined as comedy and drama, the cross-category of comedy and horror can be determined as comedy and horror, the cross-category of emotion and drama can be determined as emotion and drama, and the cross-category of emotion and horror can be determined as emotion and horror. Then, target resources are recommended according to the determined cross-categories.

[0103] In the case where there are resources to be recommended in the cross-category, optionally, the resource recommendation method provided in the embodiment of the present application further includes: determining that the target recommended resource is the resource to be recommended.

[0104] In the embodiment of the present application, if there are resources that can be recommended in the comedy drama category, then the resource can be recommended as a target recommendation resource.

[0105] Correspondingly, if there are resources in the romance category that can be recommended, then the resource can be recommended as a target recommendation resource.

[0106] In the case where there are no resources to be recommended in the cross-category, optionally, the resource recommendation method provided in the embodiment of the present application also includes: determining a first resource category and a second resource category corresponding to the cross-category; determining a first recommended resource based on the first resource category, and determining a second recommended resource based on the second resource category; and determining the target recommended resources as the first recommended resource and the second recommended resource.

[0107] In the embodiment of the present application, if there are no resources in the comedy and horror categories that can be recommended, comedy resources and horror resources can be recommended as target recommendation resources respectively.

[0108] Correspondingly, if there are no resources in the emotion horror category that can be recommended, emotion resources and horror resources can be recommended as target recommended resources respectively.

[0109] As an optional embodiment, if there is a conflict in cross-categories, the categories that each user watches the most are recommended, and categories that may be commonly liked are intelligently recommended. For example, if one person likes to watch comedy and the other likes to watch horror, comedy and horror categories are recommended at the same time. The smart device can intelligently recommend similar or commonly liked movies by identifying certain specific movies that they have watched or rated highly.

[0110] As an optional embodiment, the general preferences of multiple user groups can also be pre-added, for example, recommendations for parent-child programs can be added for fathers, mothers and children; recommendations for animation programs can also be added based on the age of the children.

[0111] Optionally, assuming that a family consists of parents and a preschooler, when it is recognized that family members are watching together, it can intelligently recommend parent-child programs that are suitable for both adults and children, such as "Peppa Pig", while retaining content recommendations preferred by adults, such as comedy or drama movies, to ensure that every family member can find content they like.

[0112] The embodiments of the present application significantly improve the family viewing experience and enhance user satisfaction and interactivity by introducing key innovations such as personalized cross-recommendations in the family sharing mode, multimodal user status recognition, dynamic learning and adaptability, family combination preference considerations, and user feedback mechanism.

[0113] The embodiment of the present application determines multiple facial recognition results for multiple users; determines multiple groups of resources of interest based on the multiple facial recognition results, each facial recognition result in the multiple facial recognition results corresponds to a group of resources of interest; and determines a technical solution of target recommended resources based on the multiple groups of resources of interest. It can recommend related resources of common interest to multiple users based on the facial recognition results of multiple users, thereby achieving the technical effect of accurately recommending resources of common interest to multiple users based on the content of interest to multiple users, thereby improving the user viewing experience.

[0114] In order to better implement the resource recommendation method of the present application, the present application also provides a resource recommendation device based on the resource recommendation method. The meanings of the terms are the same as those in the resource recommendation method, and the specific implementation details can refer to the description in the method embodiment.

[0115] See also Figure 4 , Figure 4 4 is a schematic diagram of the structure of a resource recommendation device provided in an embodiment of the present application, wherein the resource recommendation device 400 is applied to a smart device, and specifically can be as follows:

[0116] Processing module 401, used to determine multiple facial recognition results of multiple users;

[0117] The processing module 401 is further used to determine multiple groups of interesting resources according to the multiple facial recognition results, each facial recognition result in the multiple facial recognition results corresponds to a group of interesting resources;

[0118] The processing module 401 is further configured to determine target recommended resources according to the multiple groups of interesting resources.

[0119] Optionally, in some embodiments of the present application, the processing module 401 is further configured to:

[0120] Determine a resource category corresponding to each group of interesting resources in a plurality of groups of interesting resources;

[0121] Determine target recommended resources based on multiple groups of resource categories.

[0122] Optionally, in some embodiments of the present application, the processing module 401 is further configured to:

[0123] Determine that the target recommended resource is the resource of interest corresponding to the same resource category.

[0124] Optionally, in some embodiments of the present application, the processing module 401 is further configured to:

[0125] determining the intersection category of every two different groups of resource categories in the plurality of groups of resource categories;

[0126] Based on the cross-categories, target recommended resources are determined.

[0127] Optionally, in some embodiments of the present application, the processing module 401 is further configured to:

[0128] The target recommended resource is determined as the resource to be recommended.

[0129] Optionally, in some embodiments of the present application, the processing module 401 is further configured to:

[0130] Determine a first resource category and a second resource category corresponding to the cross-category;

[0131] Determining a first recommended resource according to the first resource category, and determining a second recommended resource according to the second resource category;

[0132] The target recommended resource is determined to be the first recommended resource and the second recommended resource.

[0133] Optionally, in some embodiments of the present application, the processing module 401 is further configured to:

[0134] Determining multiple identity information of multiple users based on multiple facial recognition results;

[0135] Obtain resource records corresponding to each of the multiple identity information;

[0136] Groups of resources of interest are determined based on resource records.

[0137] In the embodiment of the present application, the processing module 401 first determines multiple facial recognition results of multiple users. Then, the processing module 401 determines multiple groups of interesting resources based on the multiple facial recognition results, each facial recognition result in the multiple facial recognition results corresponds to a group of interesting resources. Subsequently, the processing module 401 determines target recommended resources based on the multiple groups of interesting resources.

[0138] Among them, the embodiment of the present application determines multiple facial recognition results of multiple users; determines multiple groups of interested resources based on the multiple facial recognition results, each facial recognition result in the multiple facial recognition results corresponds to a group of interested resources; and determines a technical solution of target recommended resources based on the multiple groups of interested resources. It can recommend related resources of common interest to multiple users based on the facial recognition results of multiple users, thereby achieving the technical effect of accurately recommending resources of common interest to multiple users based on the content of interest to multiple users, thereby improving the user viewing experience.

[0139] In addition, the present application also provides an electronic device, such as Figure 5 As shown, it shows a schematic diagram of the structure of the electronic device involved in this application, specifically:

[0140] The electronic device may include components such as a processor 501 with one or more processing cores, a memory 502 with one or more computer-readable storage media, a power supply 503, and an input unit 504. Those skilled in the art will appreciate that Figure 5 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0141] The processor 501 is the control center of the electronic device, and uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 502, and calling data stored in the memory 502, the processor 501 performs various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 501 may include one or more processing cores; preferably, the processor 501 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 501.

[0142] The memory 502 can be used to store software programs and modules. The processor 501 executes various functional applications and data processing by running the software programs and modules stored in the memory 502. The memory 502 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 502 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 502 may also include a memory controller to provide the processor 501 with access to the memory 502.

[0143] The electronic device also includes a power supply 503 for supplying power to various components. Preferably, the power supply 503 can be logically connected to the processor 501 through a power management system, so as to manage charging, discharging, power consumption and other functions through the power management system. The power supply 503 can also include one or more DC or AC power supplies, recharging systems, power supply device debugging circuits, power converters or inverters, power status indicators and other arbitrary components.

[0144] The electronic device may further include an input unit 504, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0145] Although not shown, the electronic device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 501 in the electronic device will load the executable file corresponding to the process of one or more application programs into the memory 502 according to the following instructions, and the processor 501 will run the application program stored in the memory 502, thereby implementing the steps in any resource recommendation method provided in the embodiments of the present application.

[0146] The embodiment of the present application determines multiple facial recognition results for multiple users; determines multiple groups of resources of interest based on the multiple facial recognition results, each facial recognition result in the multiple facial recognition results corresponds to a group of resources of interest; and determines a technical solution of target recommended resources based on the multiple groups of resources of interest. It can recommend related resources of common interest to multiple users based on the facial recognition results of multiple users, thereby achieving the technical effect of accurately recommending resources of common interest to multiple users based on the content of interest to multiple users, thereby improving the user viewing experience.

[0147] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0148] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0149] To this end, the present application provides a computer-readable storage medium, on which a computer program is stored. The computer program can be loaded by a processor to execute the steps in any resource recommendation method provided in the present application.

[0150] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0151] The computer-readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0152] Since the instructions stored in the computer-readable storage medium can execute the steps in any resource recommendation method provided in the present application, the beneficial effects that can be achieved by any resource recommendation method provided in the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0153] The above is a detailed introduction to a resource recommendation method, device, electronic device and computer-readable storage medium provided by the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A resource recommendation method, characterized in that: Applied to a smart device, the method comprises: determining multiple facial recognition results for multiple users; Determine a plurality of groups of resources of interest according to the plurality of facial recognition results, each facial recognition result in the plurality of facial recognition results corresponding to a group of resources of interest; According to the multiple groups of interesting resources, target recommended resources are determined.

2. The method according to claim 1, characterized in that The step of determining target recommended resources according to the multiple groups of interesting resources includes: Determine a resource category corresponding to each group of interesting resources in the multiple groups of interesting resources; The target recommended resources are determined according to multiple groups of resource categories.

3. The method according to claim 2, characterized in that In the case that the same resource category exists in the multiple groups of resource categories, determining the target recommended resource according to the multiple groups of resource categories includes: Determine that the target recommended resource is a resource of interest corresponding to the same resource category.

4. The method according to claim 2, characterized in that: In the case that there is no identical resource category in the multiple groups of resource categories, determining the target recommended resource according to the multiple groups of resource categories includes: Determine the intersection category of every two different groups of resource categories in the multiple groups of resource categories; The target recommended resource is determined according to the cross-category.

5. The method according to claim 4, characterized in that In the case that there are resources to be recommended in the cross-category, determining the target recommended resource according to the cross-category includes: The target recommended resource is determined to be the resource to be recommended.

6. The method according to claim 4, characterized in that In the case that there is no resource to be recommended in the cross-category, determining the target recommended resource according to the cross-category includes: Determine a first resource category and a second resource category corresponding to the cross-category; determining a first recommended resource according to the first resource category, and determining a second recommended resource according to the second resource category; The target recommended resource is determined to be the first recommended resource and the second recommended resource.

7. The method according to claim 1, characterized in that The step of determining multiple groups of resources of interest based on the multiple facial recognition results includes: Determining multiple identity information of the multiple users according to the multiple facial recognition results; Obtain a resource record corresponding to each piece of identity information in the plurality of identity information; The multiple groups of interesting resources are determined according to the resource records.

8. A resource recommendation device, characterized in that: Applied to a smart device, the device comprises: A processing module, configured to determine a plurality of facial recognition results for a plurality of users; The processing module is further used to determine multiple groups of interesting resources based on the multiple facial recognition results, each facial recognition result in the multiple facial recognition results corresponds to a group of interesting resources; The processing module is further configured to determine target recommended resources based on the multiple groups of interesting resources.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps in the resource recommendation method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the resource recommendation method according to any one of claims 1 to 7 are implemented.

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