Message recommendation method, device, equipment and medium

Abstract

The present application discloses a message recommendation method, apparatus, device and medium, which belongs to the field of artificial intelligence technology. The message recommendation method includes: obtaining at least two user tags of a target user, wherein the at least two user tags are tags generated based on at least two user features of the target user, and the at least two user features are user features of the target user relative to at least two target objects; generating a user portrait corresponding to the target user based on the at least two user tags; when the target user interacts with a first object, generating first information based on the user portrait, wherein the first information is used to instruct the first object to recommend a message to the target user; sending the first information to the first object so that the first object recommends a message to the target user based on the first information. Using the scheme disclosed in the present application, the first object can recommend messages based on the user tags generated by the user relative to the user features of at least two objects.

Description

Technical Field

[0001] The present application belongs to the field of artificial intelligence technology, and specifically relates to a message recommendation method, apparatus, device, and medium. Background Art

[0002] User profiling, or the labeling of user information, is achieved by collecting and analyzing key information about users, including their social attributes, lifestyle habits, consumption behaviors, and preferences. This information is then abstracted into tags, which are then used to visualize the user and provide targeted services. User profiling is comprised of numerous tags, each defining a perspective for observing, understanding, and describing the user.

[0003] In related technologies, electronic devices or applications recommend messages based on user tags included in user profiles. However, the user profiles generated by different objects (electronic devices or applications) for users are not universal across all objects. Any one of the different objects can only recommend messages based on the user tags included in its generated user profile, and cannot recommend messages based on the user tags included in the user profiles generated by other objects. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a message recommendation method, apparatus, device and medium that can solve the problem that any object cannot recommend messages based on user tags included in user portraits generated by other objects.

[0005] In a first aspect, an embodiment of the present application provides a message recommendation method, comprising:

[0006] Obtaining at least two user tags of the target user, wherein the at least two user tags are tags generated based on at least two user features of the target user, and the at least two user features are user features of the target user relative to at least two target objects;

[0007] Generate a user profile corresponding to the target user based on the at least two user tags, wherein the user profile includes the at least two user tags;

[0008] When a target user interacts with a first object, first information is generated according to the user portrait, wherein the first information is used to instruct the first object to recommend a message to the target user, and the first object is any one of the at least two target objects;

[0009] The first information is sent to the first object, so that the first object recommends a message to a target user according to the first information.

[0010] In some possible implementations of the first aspect of the embodiments of the present application, obtaining at least two user tags of the target user includes:

[0011] At least two user tags sent by at least two target objects are received, wherein the user tags are generated according to historical operations of the target users on the target objects.

[0012] In some possible implementations of the first aspect of the embodiments of the present application, obtaining at least two user tags of the target user includes:

[0013] receiving at least two user features sent by at least two target objects, wherein the user features are extracted based on historical operations of the target users on the target objects;

[0014] At least two user tags are generated according to the at least two user features.

[0015] In some possible implementations of the first aspect of the embodiment of the present application, before generating the first information based on the user portrait, the message recommendation method provided in the embodiment of the present application further includes:

[0016] Obtain the target user's identity information;

[0017] The user profile that matches the identity information among multiple user profiles is determined as the user profile corresponding to the target user.

[0018] In some possible implementations of the first aspect of the embodiments of the present application, obtaining the identity information of the target user includes:

[0019] Receive identity information sent by the first object, wherein the identity information is information obtained by the first object through identity recognition based on biometric information of the target user.

[0020] In some possible implementations of the first aspect of the embodiments of the present application, obtaining the identity information of the target user includes:

[0021] receiving biometric information of a target user sent by a first object;

[0022] The target user is identified based on the biometric information to obtain identity information.

[0023] In some possible implementations of the first aspect of the embodiment of the present application, the first information includes:

[0024] At least two user tags, and / or a target message of the first object to be recommended to the target user.

[0025] In a second aspect, an embodiment of the present application provides a message recommendation device, including:

[0026] A first acquisition module is configured to acquire at least two user tags of a target user, wherein the at least two user tags are tags generated based on at least two user features of the target user, and the at least two user features are user features of the target user relative to at least two target objects;

[0027] A first generating module is configured to generate a user profile corresponding to a target user based on at least two user tags, wherein the user profile includes at least two user tags;

[0028] A second generating module is configured to generate first information based on the user portrait when the target user interacts with the first object, wherein the first information is used to instruct the first object to recommend a message to the target user, and the first object is any one of the at least two target objects;

[0029] The sending module is used to send the first information to the first object, so that the first object recommends a message to the target user according to the first information.

[0030] In some possible implementations of the second aspect of the embodiment of the present application, the first acquisition module is specifically configured to:

[0031] At least two user tags sent by at least two target objects are received, wherein the user tags are generated according to historical operations of the target users on the target objects.

[0032] In some possible implementations of the second aspect of the embodiment of the present application, the first acquisition module includes:

[0033] A first receiving submodule is configured to receive at least two user features sent by at least two target objects, wherein the user features are extracted based on the target user's historical operations on the target objects;

[0034] The generating submodule is used to generate at least two user tags according to at least two user features.

[0035] In some possible implementations of the second aspect of the embodiments of the present application, the message recommendation device provided in the embodiments of the present application further includes:

[0036] The second acquisition module is used to obtain the identity information of the target user;

[0037] The determination module is used to determine the user profile that matches the identity information among multiple user profiles as the user profile corresponding to the target user.

[0038] In some possible implementations of the second aspect of the embodiment of the present application, the second acquisition module is specifically configured to:

[0039] Receive identity information sent by the first object, wherein the identity information is information obtained by the first object through identity recognition based on biometric information of the target user.

[0040] In some possible implementations of the second aspect of the embodiment of the present application, the second acquisition module includes:

[0041] A second receiving submodule is configured to receive the biometric information of the target user sent by the first object;

[0042] The identification submodule is used to identify the target user based on the biometric information and obtain identity information.

[0043] In some possible implementations of the second aspect of the embodiment of the present application, the first information includes:

[0044] At least two user tags, and / or a target message of the first object to be recommended to the target user.

[0045] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the method described in the first aspect are implemented.

[0046] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0047] In a fifth aspect, an embodiment of the present application provides a chip comprising a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the steps of the method described in the first aspect.

[0048] In a sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the method described in the first aspect.

[0049] In an embodiment of the present application, since at least two user features are user features of the target user relative to at least two target objects, and at least two user tags are tags generated based on the at least two user features of the target user, the user profile corresponding to the target user generated based on the at least two user tags includes at least two user tags. In other words, the user profile corresponding to the target user is a user profile generated based on at least two user tags generated based on the at least two user features of the target user relative to at least two target objects, and the user profile can be used by the at least two target objects. Therefore, when the target user interacts with the first object of the at least two target objects, the first object can make message recommendations based on the user tags corresponding to other objects other than the first object of the at least two target objects. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0051] Figure 1 This is a flowchart of a message recommendation method provided by an embodiment of the present application;

[0052] Figure 2 This is a schematic diagram of the process of generating a user portrait provided by an embodiment of the present application;

[0053] Figure 3 This is a structural diagram of a message recommendation device provided in an embodiment of the present application;

[0054] Figure 4 is a structural diagram of an electronic device provided in an embodiment of the present application;

[0055] Figure 5 It is a schematic diagram of the hardware structure of the electronic device implementing the embodiment of the present application. DETAILED DESCRIPTION

[0056] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0057] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0058] The message recommendation method, apparatus, device, and medium provided in the embodiments of the present application are described in detail below with reference to specific embodiments and their application scenarios in conjunction with the accompanying drawings.

[0059] Figure 1 This is a flow chart of the message recommendation method provided by the embodiment of the present application. Figure 1 As shown, the message recommendation method may include:

[0060] S101: Acquire at least two user tags of a target user, wherein the at least two user tags are tags generated based on at least two user features of the target user, and the at least two user features are user features of the target user relative to at least two target objects;

[0061] S102: Generate a user profile corresponding to the target user based on the at least two user tags, wherein the user profile includes the at least two user tags;

[0062] S103: When the target user interacts with the first object, first information is generated according to the user portrait, wherein the first information is used to instruct the first object to recommend a message to the target user, and the first object is any one of the at least two target objects;

[0063] S104: Sending first information to the first object, so that the first object recommends a message to the target user according to the first information.

[0064] The specific implementation of each of the above steps will be described in detail below.

[0065] In an embodiment of the present application, since at least two user features are user features of the target user relative to at least two target objects, and at least two user tags are tags generated based on the at least two user features of the target user, the user profile corresponding to the target user generated based on the at least two user tags includes at least two user tags. In other words, the user profile corresponding to the target user is a user profile generated based on at least two user tags generated based on the at least two user features of the target user relative to at least two target objects, and the user profile can be used by the at least two target objects. Therefore, when the target user interacts with the first object of the at least two target objects, the first object can make message recommendations based on the user tags corresponding to other objects other than the first object of the at least two target objects.

[0066] In some possible implementations of the embodiments of the present application, the object in the embodiments of the present application may be an electronic device or an application.

[0067] In some possible implementations of the embodiment of the present application, at least two target objects in the embodiment of the present application may be objects that have historically interacted with the target user.

[0068] In some possible implementations of the embodiments of the present application, when the object is an electronic device, at least two electronic devices in the embodiments of the present application belong to the same management platform, and the information of at least two electronic devices can be collected by the same message recommendation device to form a user portrait, and there is no cross-platform information leakage.

[0069] In some possible implementations of the embodiments of the present application, when the object is an electronic device, at least two electronic devices in the embodiments of the present application may also belong to different management platforms, but these management platforms are allowed to share the message recommendation device provided by the embodiments of the present application.

[0070] In some possible implementations of the embodiments of the present application, when the object is an application, at least two applications in the embodiments of the present application may be applications installed on the same electronic device, and the message recommendation device provided by the embodiments of the present application may be shared between the applications.

[0071] In some possible implementations of the embodiments of the present application, an object may correspond to one or more user features of a user. A user tag may be generated based on one or more user features. In other words, one or more user features of a user may be extracted from an object.

[0072] In some possible implementations of the embodiments of the present application, user characteristics include but are not limited to: user basic attribute characteristics, user behavior attribute characteristics, user preference attribute characteristics, user consumption attribute characteristics, user social attribute characteristics, etc.

[0073] Among them, basic user attribute characteristics include but are not limited to: gender, age, occupation, etc. User behavior attribute characteristics include but are not limited to: time periods for listening to music, commuting time, recently used applications, recently visited places, etc. User preference attribute characteristics include but are not limited to: music that users like to listen to, singers that users like, types of movies that users like, products that users like, etc. User consumption attribute characteristics include but are not limited to: the amount of goods purchased in a certain period of time, the frequency of purchases in a certain period of time, the categories of goods purchased in a certain period of time, the products purchased in a certain period of time, etc. User social attribute characteristics include but are not limited to: time periods and places where users are active, etc.

[0074] In some possible implementations of the embodiments of the present application, at least two user tags may correspond one-to-one with at least two user features, and at least two user features may correspond one-to-one with at least two objects. That is, one object corresponds to one user feature, and one user tag is generated based on one user feature. In other words, a user feature extracted from an object is one user feature, and a user tag is a user tag generated based on a user feature extracted from an object.

[0075] For example, taking N electronic devices as an example, N is a positive integer greater than or equal to 2. Figure 2 As shown, Figure 2 This is a schematic diagram of the process of generating a user portrait provided by an embodiment of the present application. Figure 2In the example, N electronic devices are UE1 through UEN. User feature F1 of user A is extracted from UE1, user feature F2 of user A is extracted from UE2, etc., user features Fi of user A are extracted from electronic device UEi, etc., and user features FN of user A are extracted from electronic device UEN. User tag T1 is generated based on user feature F1, user tag T2 is generated based on user feature F2, etc., user tags Ti are generated based on user feature Fi, etc., and user tag TN is generated based on user feature FN, where i is a positive integer greater than or equal to 1 and less than or equal to N.

[0076] A user portrait of user A including the user tags F1, F2, ..., FN is generated according to the user tags F1, F2, ..., FN.

[0077] When user A interacts with electronic device UE2, first information for instructing electronic device UE2 to recommend messages to user A is generated based on the user portrait of user A including user tags F1, F2, ..., FN. After receiving the first information, electronic device UE2 recommends messages to user A based on the first information.

[0078] In some possible implementations of the embodiments of the present application, S101 may include: receiving at least two user tags sent by at least two target objects, wherein the user tags are generated according to the target user's historical operations on the target objects.

[0079] In an embodiment of the present application, user features can be extracted based on the target user's historical operations on the target object. Then, a user tag is generated based on the user features, and the generated user tag is sent to an electronic device capable of implementing the message recommendation method provided in an embodiment of the present application. It will be understood that in an embodiment of the present application, the user tag can be generated by at least two target objects that the user has historically interacted with.

[0080] The embodiment of the present application does not limit the method used to extract user features based on the target user's history of operations on the target object. Any available feature extraction method can be applied to the embodiment of the present application.

[0081] In some possible implementations of the embodiments of the present application, S101 may include: receiving at least two user features sent by at least two target objects, wherein the user features are extracted based on the target user's historical operations on the target object; and generating at least two user tags based on the at least two user features.

[0082] In an embodiment of the present application, user features can be extracted based on the target user's historical operations on the target object. The extracted user features are then sent to an electronic device capable of implementing the message recommendation method provided in an embodiment of the present application. The electronic device capable of implementing the message recommendation method provided in an embodiment of the present application generates a user tag based on the received user features. It is understood that in an embodiment of the present application, the user tag can be generated by the electronic device capable of implementing the message recommendation method provided in an embodiment of the present application.

[0083] In some possible implementations of the embodiments of the present application, before S103, the message recommendation method provided by the embodiments of the present application may also include: obtaining the identity information of the target user; and determining the user portrait that matches the identity information among multiple user portraits as the user portrait corresponding to the target user.

[0084] In some possible implementations of the embodiments of the present application, there are situations where multiple user portraits are stored. Therefore, when a user interacts with the above-mentioned first object, first, the identity of the user is determined, and then, from the multiple stored user portraits, according to the user's identity information, the user portrait corresponding to the user is determined to make message recommendations.

[0085] In some possible implementations of the embodiments of the present application, the identity information may include the account information of the user login object, and then the user portrait corresponding to the acquired account information among multiple user portraits may be determined as the user portrait corresponding to the target user.

[0086] Exemplarily, it is assumed that M user portraits are pre-stored, and the M user portraits are respectively the user portrait Persona-1 corresponding to user Use1, the user portrait Persona-2 corresponding to user Use2, ..., the user portrait Persona-M corresponding to user UseM.

[0087] When user Use2 interacts with the first electronic device, it is determined that the user interacting with the first electronic device is Use2, and message recommendations are then performed based on the user portrait Persona-2 corresponding to user Use2.

[0088] For another example, M user profiles are pre-stored, and the M user profiles are respectively user profile Persona-1 corresponding to account information ID1, user profile Persona-2 corresponding to account information ID2, ..., and user profile Persona-M corresponding to account information ID M. Account information ID1 to IDM are the account information of users Use1 to UseM for logging into the first application.

[0089] When user Use2 interacts with the first application, the account information ID2 of user Use2 logging into the first application is obtained, and then message recommendations are made based on the user portrait Persona-2 corresponding to the account information ID2.

[0090] In an embodiment of the present application, by determining the user portrait that matches the identity information among multiple user portraits as the user portrait corresponding to the target user, and then performing message recommendations based on the determined user portrait, the accuracy of the message recommendation can be guaranteed.

[0091] In some possible implementations of the embodiments of the present application, obtaining the identity information of the target user may include: receiving identity information sent by a first object, wherein the identity information is information obtained by the first object through identity recognition based on biometric information of the target user.

[0092] In some possible implementations of the embodiments of this application, biometric information includes, but is not limited to, fingerprint information, voiceprint information, facial information, iris information, etc. The embodiments of this application do not limit the method used for identity recognition based on biometric information, and any available identity recognition method can be applied to the embodiments of this application.

[0093] In the embodiment of the present application, during the user's interaction with the first object, the first object can obtain the user's biometric information and then perform identity recognition based on the biometric information. It is understandable that in the embodiment of the present application, user identity recognition is completed by the first object.

[0094] In some possible implementations of the embodiments of the present application, obtaining the identity information of the target user may include: receiving biometric information of the target user sent by the first object; and performing identity identification on the target user based on the biometric information to obtain the identity information.

[0095] In an embodiment of the present application, the first object may obtain biometric information of the user interacting with it, and then send the user's biometric information to an electronic device capable of implementing the message recommendation method provided in an embodiment of the present application. The electronic device capable of implementing the message recommendation method provided in an embodiment of the present application performs identity recognition based on the received biometric information of the user. It is understood that in an embodiment of the present application, user identity recognition is performed by the electronic device capable of implementing the message recommendation method provided in an embodiment of the present application.

[0096] In some possible implementations of the embodiments of the present application, the first information may include at least two user tags, and / or a target message to be recommended by the first electronic device to the target user.

[0097] In an embodiment of the present application, when the first information includes at least two user tags, that is, the first information includes the user portrait itself, when the first object receives the first information including at least two user tags, it can generate target information to be recommended to the target user based on the at least two user tags included in the first information, and then recommend the target information to the target user.

[0098] The embodiment of the present application does not limit the method used to generate target information to be recommended to the target user based on at least two user tags. Any available method can be applied to the embodiment of the present application.

[0099] When the first information includes a target message to be recommended to the target user by the first object, the first object may directly recommend the target information to the target user upon receiving the first information including the target message to be recommended to the target user by the first object.

[0100] It should be noted that the acquisition, storage, use and processing of data in all implementation methods of this application comply with the relevant provisions of national laws and regulations.

[0101] The message recommendation method provided in the embodiment of the present application is described below in conjunction with specific application scenarios.

[0102] For example, if a smart playback device detects that a user prefers to listen to songs by singer A, a preference tag for singer A is generated. If a Bluetooth attendance device detects that the user's clock-in time falls between T1 and T2, and their clock-out time falls between T3 and T4, a work behavior tag is generated. When the user interacts with the smart playback device at time T4, a recommendation message, such as "You've been working hard, relax with song X by singer A!", can be sent to the user.

[0103] As another example, suppose a medical registration app obtains a user's registration information and generates a registration tag for the user. A news app then detects an epidemic situation near the hospital corresponding to the user's registration information and generates an epidemic prevention tag for the user. When the user interacts with the medical registration app again, for example, to view their appointment time, a recommendation message such as "There is an epidemic situation. Please take precautions when visiting the doctor!" may be provided to the user.

[0104] As another example, suppose a travel app obtains a user's ticket purchase information and generates a travel tag for the user. A news app also obtains information about an epidemic at the destination corresponding to the user's travel information, requiring nucleic acid testing to travel there, generating a user's epidemic prevention tag. When the user interacts with the travel app again, for example, to view their travel time, a recommendation message such as "Nucleic acid testing is required to travel to your destination. Please get tested promptly" can be provided to the user.

[0105] For example, suppose a food delivery app obtains a user's food order information and generates a food order tag for the user. Furthermore, a health checkup app obtains the user's health checkup information and generates a health checkup tag for the user. When the user interacts with the food delivery app again, a recommendation message, such as "You purchased a lot of junk food. Please get a health checkup done." may be provided to the user.

[0106] It should be noted that the message recommendation method provided in the embodiment of the present application can be executed by a message recommendation device. In the embodiment of the present application, the message recommendation device executing the message recommendation method is taken as an example to illustrate the message recommendation device provided in the embodiment of the present application.

[0107] Figure 3 : is a schematic diagram of the structure of a message recommendation device provided in an embodiment of the present application. The message recommendation device 300 may include:

[0108] A first acquisition module 301 is configured to acquire at least two user tags of a target user, wherein the at least two user tags are tags generated based on at least two user features of the target user, and the at least two user features are user features of the target user relative to at least two target objects;

[0109] A first generating module 302 is configured to generate a user profile corresponding to a target user based on at least two user tags, wherein the user profile includes at least two user tags;

[0110] A second generating module 303 is configured to generate first information based on the user portrait when the target user interacts with the first object, wherein the first information is used to instruct the first object to recommend a message to the target user, where the first object is any one of the at least two target objects;

[0111] The sending module 304 is configured to send first information to the first object, so that the first object recommends a message to a target user according to the first information.

[0112] In an embodiment of the present application, since at least two user features are user features of the target user relative to at least two target objects, and at least two user tags are tags generated based on the at least two user features of the target user, the user profile corresponding to the target user generated based on the at least two user tags includes at least two user tags. In other words, the user profile corresponding to the target user is a user profile generated based on at least two user tags generated based on the at least two user features of the target user relative to at least two target objects, and the user profile can be used by the at least two target objects. Therefore, when the target user interacts with the first object of the at least two target objects, the first object can make message recommendations based on the user tags corresponding to other objects other than the first object of the at least two target objects.

[0113] In some possible implementations of the embodiment of the present application, the first acquisition module 301 is specifically configured to:

[0114] At least two user tags sent by at least two target objects are received, wherein the user tags are generated according to historical operations of the target users on the target objects.

[0115] In an embodiment of the present application, a user tag may be generated based on the target user's historical operations on the target object.

[0116] In some possible implementations of the embodiment of the present application, the first acquisition module 301 includes:

[0117] A first receiving submodule is configured to receive at least two user features sent by at least two target objects, wherein the user features are extracted based on the target user's historical operations on the target objects;

[0118] The generating submodule is used to generate at least two user tags according to at least two user features.

[0119] In the embodiment of the present application, the user tag may be generated by a message recommendation device.

[0120] In some possible implementations of the embodiment of the present application, the message recommendation apparatus 300 provided in the embodiment of the present application further includes:

[0121] The second acquisition module is used to obtain the identity information of the target user;

[0122] The determination module is used to determine the user profile that matches the identity information among multiple user profiles as the user profile corresponding to the target user.

[0123] In an embodiment of the present application, by determining the user portrait that matches the identity information among multiple user portraits as the user portrait corresponding to the target user, and then performing message recommendations based on the determined user portrait, the accuracy of the message recommendation can be guaranteed.

[0124] In some possible implementations of the embodiments of the present application, the second acquisition module is specifically configured to:

[0125] Receive identity information sent by the first object, wherein the identity information is information obtained by the first object through identity recognition based on biometric information of the target user.

[0126] In the embodiment of the present application, the user identity information can be obtained by the first object through identity recognition based on the biometric information of the target user.

[0127] In some possible implementations of the embodiments of the present application, the second acquisition module includes:

[0128] A second receiving submodule is configured to receive the biometric information of the target user sent by the first object;

[0129] The identification submodule is used to identify the target user based on the biometric information and obtain identity information.

[0130] In the embodiment of the present application, the user identity information can be obtained by the message recommendation device through identity recognition based on the biometric information of the target user.

[0131] In some possible implementations of the embodiments of the present application, the first information includes:

[0132] At least two user tags, and / or a target message of the first object to be recommended to the target user.

[0133] The message recommendation device in the embodiments of the present application can be an electronic device or a component of an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other device other than a terminal. For example, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a mobile internet device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc. It can also be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine, or a self-service machine, etc., and the embodiments of the present application do not specifically limit this.

[0134] The message recommendation device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0135] The message recommendation device provided in the embodiment of the present application can achieve Figures 1 to 2 To avoid repetition, each process in the message recommendation method embodiment will not be described here.

[0136] Optional, such as Figure 4As shown, an embodiment of the present application also provides an electronic device 400, including a processor 401 and a memory 402, wherein the memory 402 stores a program or instruction that can be run on the processor 401. When the program or instruction is executed by the processor 401, the various steps of the above-mentioned message recommendation method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0137] In some possible implementations of the embodiments of the present application, the processor 401 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0138] In some possible implementations of the embodiments of the present application, the memory 402 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Therefore, typically, the memory 402 includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the message recommendation method according to the embodiments of the present application.

[0139] Figure 5 It is a schematic diagram of the hardware structure of the electronic device implementing the embodiment of the present application.

[0140] The electronic device 500 includes but is not limited to components such as a radio frequency unit 501 , a network module 502 , an audio output unit 503 , an input unit 504 , a sensor 505 , a display unit 506 , a user input unit 507 , an interface unit 508 , a memory 509 , and a processor 510 .

[0141] Those skilled in the art will understand that the electronic device 500 may also include a power source (such as a battery) to power each component, and the power source may be logically connected to the processor 510 through a power management system, thereby implementing functions such as charging, discharging, and power consumption management through the power management system. Figure 5 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be repeated here.

[0142] Processor 510 is configured to obtain at least two user tags of a target user, where the at least two user tags are tags generated based on at least two user features of the target user, and the at least two user features are user features of the target user relative to at least two target objects; generate a user profile corresponding to the target user based on the at least two user tags, where the user profile includes at least two user tags; and generate first information based on the user profile when the target user interacts with a first object, where the first information is used to instruct the first object to recommend a message to the target user, where the first object is any one of the at least two target objects;

[0143] The network module 502 is configured to send first information to the first object, so that the first object recommends a message to a target user according to the first information.

[0144] In an embodiment of the present application, since at least two user features are user features of the target user relative to at least two target objects, and at least two user tags are tags generated based on the at least two user features of the target user, the user profile corresponding to the target user generated based on the at least two user tags includes at least two user tags. In other words, the user profile corresponding to the target user is a user profile generated based on at least two user tags generated based on the at least two user features of the target user relative to at least two target objects, and the user profile can be used by the at least two target objects. Therefore, when the target user interacts with the first object of the at least two target objects, the first object can make message recommendations based on the user tags corresponding to other objects other than the first object of the at least two target objects.

[0145] In some possible implementations of the embodiments of the present application, the processor 510 is specifically configured to:

[0146] At least two user tags sent by at least two target objects are received, wherein the user tags are generated according to historical operations of the target users on the target objects.

[0147] In an embodiment of the present application, a user tag may be generated based on the target user's historical operations on the target object.

[0148] In some possible implementations of the embodiments of the present application, the processor 510 is specifically configured to:

[0149] At least two user features sent by at least two target objects are received, wherein the user features are extracted based on target users' historical operations on the target objects; and at least two user tags are generated based on the at least two user features.

[0150] In an embodiment of the present application, the user tag can be generated by the electronic device 500.

[0151] In some possible implementations of the embodiments of the present application, the processor 510 is further configured to:

[0152] Obtain the target user's identity information;

[0153] The user profile that matches the identity information among multiple user profiles is determined as the user profile corresponding to the target user.

[0154] In an embodiment of the present application, by determining the user portrait that matches the identity information among multiple user portraits as the user portrait corresponding to the target user, and then performing message recommendations based on the determined user portrait, the accuracy of the message recommendation can be guaranteed.

[0155] In some possible implementations of the embodiments of the present application, the network module 502 is specifically configured to:

[0156] Receive identity information sent by the first object, wherein the identity information is information obtained by the first object through identity recognition based on biometric information of the target user.

[0157] In the embodiment of the present application, the user identity information can be obtained by the first object through identity recognition based on the biometric information of the target user.

[0158] In some possible implementations of the embodiment of the present application, the network module 502 is further configured to:

[0159] receiving biometric information of a target user sent by a first object;

[0160] Correspondingly, the processor 510 is further configured to: perform identity recognition on the target user according to the biometric information to obtain identity information.

[0161] In the embodiment of the present application, the user identity information can be obtained by the electronic device 500 through identity recognition based on the biometric information of the target user.

[0162] In some possible implementations of the embodiments of the present application, the first information includes:

[0163] At least two user tags, and / or a target message of the first object to be recommended to the target user.

[0164] It should be understood that in an embodiment of the present application, the input unit 504 may include a graphics processing unit (GPU) 5041 and a microphone 5042, and the graphics processor 5041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 506 may include a display panel 5061, and the display panel 5061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 507 includes a touch panel 5071 and at least one of other input devices 5072. The touch panel 5071 is also called a touch screen. The touch panel 5071 may include two parts: a touch detection device and a touch controller. Other input devices 5072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and an operating stick, which will not be repeated here.

[0165] The memory 509 can be used to store software programs and various data. The memory 509 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, applications or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 509 may include a volatile memory or a non-volatile memory, or the memory 509 may include both volatile and non-volatile memories. Among them, the non-volatile 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), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM), and a direct memory bus random access memory (DRRAM). The memory 509 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0166] Processor 510 may include one or more processing units. Optionally, processor 510 integrates an application processor and a modem processor. The application processor primarily handles operations related to the operating system, user interface, and application programs, while the modem processor primarily processes wireless communication signals, such as a baseband processor. It is understood that the modem processor may not be integrated into processor 510.

[0167] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned message recommendation method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0168] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer-readable storage medium, and examples of the computer-readable storage medium include non-transitory computer-readable storage media, such as ROM, RAM, magnetic disk or optical disk.

[0169] An embodiment of the present application further provides a chip including a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned message recommendation method embodiment and achieve the same technical effect. To avoid repetition, they will not be described here.

[0170] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0171] An embodiment of the present application provides a computer program product, which is stored in a storage medium. The program product is executed by at least one processor to implement the various processes of the above-mentioned message recommendation method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0172] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be noted that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0173] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the relevant technology, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0174] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. A message recommendation method, characterized in that: The method comprises: Acquire at least two user tags of a target user, wherein the at least two user tags are tags generated based on at least two user features of the target user, and the at least two user features are user features of the target user relative to at least two target objects; Generating a user profile corresponding to the target user based on the at least two user tags, wherein the user profile includes the at least two user tags, wherein one object corresponds to one or more user features of the user, and one user tag is generated based on the one or more user features; When the target user interacts with a first object, first information is generated based on the user profile, wherein the first information is used to instruct the first object to recommend a message to the target user, the first object is any one of the at least two target objects, the at least two target objects are objects that have had a history of interaction with the target user, and when the at least two target objects are electronic devices, information of the at least two electronic devices is collected by the same message recommendation device to form a user profile; sending the first information to the first object, so that the first object recommends a message to the target user according to the first information; Before generating the first information according to the user portrait, the method further includes: Obtaining identity information of the target user; A user portrait that matches the identity information among multiple user portraits is determined as the user portrait corresponding to the target user.

2. The method according to claim 1, characterized in that The acquiring of at least two user tags of the target user includes: The at least two user tags sent by the at least two target objects are received, wherein the user tags are generated according to the target user's historical operations on the target objects.

3. The method according to claim 1, characterized in that The acquiring of at least two user tags of the target user includes: Receiving the at least two user features sent by the at least two target objects, wherein the user features are extracted based on the target user's historical operations on the target objects; The at least two user tags are generated according to the at least two user features.

4. The method according to claim 1, wherein The obtaining of the identity information of the target user includes: The identity information sent by the first object is received, wherein the identity information is information obtained by the first object through identity recognition based on the biometric information of the target user.

5. The method according to claim 1, wherein The obtaining of the identity information of the target user includes: receiving biometric information of the target user sent by the first object; The target user is identified according to the biometric information to obtain the identity information.

6. The method according to claim 1, characterized in that The first information includes: The at least two user tags, and / or the target message to be recommended to the target user by the first object.

7. A message recommendation device, characterized in that: The device comprises: A first acquisition module is configured to acquire at least two user tags of a target user, wherein the at least two user tags are tags generated based on at least two user features of the target user, and the at least two user features are user features of the target user relative to at least two target objects; A first generating module is configured to generate a user profile corresponding to the target user based on the at least two user tags, wherein the user profile includes the at least two user tags, wherein one object corresponds to one or more user features of the user, and one user tag is generated based on the one or more user features; a second generating module configured to generate first information based on the user profile when the target user interacts with a first object, wherein the first information is used to instruct the first object to recommend a message to the target user, the first object being any one of the at least two target objects, the at least two target objects being objects with which the target user has historically interacted, and when the at least two target objects are electronic devices, information of the at least two electronic devices is collected by the same message recommendation device to form the user profile; a sending module, configured to send the first information to the first object, so that the first object recommends a message to the target user according to the first information; The second generation module is further specifically used for: Obtaining identity information of the target user; A user portrait that matches the identity information among multiple user portraits is determined as the user portrait corresponding to the target user.

8. An electronic device, characterized in that: The electronic device includes: a processor and a memory, the memory storing a program or instruction that can be run on the processor, and the program or instruction, when executed by the processor, implements the steps of the message recommendation method according to any one of claims 1 to 6.

9. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by a processor, the steps of the message recommendation method according to any one of claims 1 to 6 are implemented.

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