CN112799514A - Information recommendation method and device, electronic equipment and medium - Google Patents
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Abstract
The disclosure provides an information recommendation method, and belongs to the technical field of digital people. The method comprises the following steps: displaying an action skeleton diagram; capturing the action of the user imitating the action skeleton diagram to obtain user action skeleton data; determining the action matching degree of the user action bone data and the action bone graph; and recommending product marketing information corresponding to the action skeleton map to the user when the action matching degree reaches a preset threshold value. The disclosure also provides an information recommendation device, an electronic device, and a computer-readable storage medium.
Description
Technical Field
The present disclosure may be applied to the field of digital people technologies, and more particularly, to an information recommendation method and apparatus, an electronic device, and a medium.
Background
At present, enterprises have single means in aspects of popularizing products, popularizing product applications or recommending related knowledge to users. If the relevant information can be suggested to the user in a subtler way through more interesting and attractive ways, not only the interaction with the user can be increased, but also the conversion rate of the product can be improved.
Disclosure of Invention
In view of this, the disclosed embodiments provide a method and apparatus for recommending information based on digital people, an electronic device, and a medium.
In one aspect of the present disclosure, an information recommendation method is provided. The method comprises the following steps: displaying an action skeleton diagram; capturing the action of the user imitating the action skeleton diagram to obtain user action skeleton data; determining the action matching degree of the user action bone data and the action bone graph; and recommending product marketing information corresponding to the action skeleton map to the user when the action matching degree reaches a preset threshold value.
According to an embodiment of the present disclosure, after recommending product marketing information corresponding to the action skeleton map to the user when the action matching degree reaches a predetermined threshold, the method further includes updating the action skeleton map if the user selects a continuation challenge, and repeatedly performing the operations of capturing, determining the action matching degree, and recommending information when the action matching degree reaches a predetermined threshold. Wherein the updated action skeleton map is more complex than the action skeleton map before updating.
According to an embodiment of the present disclosure, the method further comprises presenting an image of the motion made by the user while capturing the motion of the user.
According to an embodiment of the present disclosure, the displaying the image of the action made by the user includes: replacing the user's avatar in the presentation based on the user-selected image object; and displaying the image of the action made by the image object.
According to an embodiment of the present disclosure, recommending, to the user, product marketing information corresponding to the action skeleton map when the action matching degree reaches a predetermined threshold includes: and recommending the product marketing information to the user through the demonstration or broadcast of the image object.
According to an embodiment of the present disclosure, the determining the action matching degree of the user action bone data and the action bone map includes: and calculating the action matching degree based on the matching number of the user action skeleton data and the human skeleton points and the skeletons in the action skeleton map.
According to an embodiment of the present disclosure, wherein the content of the action skeleton map is associated with the product marketing information. Wherein the content of the action skeleton map is associated with the product marketing information including at least one of: the action content of the action skeleton diagram is the action made by the service personnel or the user of the product related to the product marketing information; setting business knowledge related to the product marketing information in the background of the action skeleton diagram; setting multimedia data of a business scene related to the product marketing information in the background of the action skeleton diagram; or the action content of the action skeleton map is set for the guide based on one or more questions related to the product marketing information.
In another aspect of the disclosed embodiments, an information recommendation apparatus is provided. The device comprises a display module, a capturing module, a matching degree determining module and a reward module. The display module is used for displaying the action skeleton map. The capturing module is used for capturing the motion of the user imitating the motion skeleton map to obtain the motion skeleton data of the user. And the matching degree determination module is used for determining the action matching degree of the user action bone data and the action bone graph. And the reward module is used for recommending product marketing information corresponding to the action skeleton map to the user when the action matching degree reaches a preset threshold value.
According to an embodiment of the present disclosure, the apparatus further comprises an update module. The updating module is used for updating the action skeleton map under the condition that the user selects to continue the challenge. Wherein the updated action skeleton map is more complex than the action skeleton map before updating.
According to an embodiment of the present disclosure, the presentation module is further configured to present an image of the motion made by the user while capturing the motion of the user.
In another aspect of the disclosed embodiments, an electronic device is provided. The electronic device includes one or more memories, and one or more processors. The memory stores executable instructions. The processor executes the executable instructions to implement the method as described above.
Another aspect of the embodiments of the present disclosure provides a computer-readable storage medium storing computer-executable instructions for implementing the method as described above when executed.
Another aspect of embodiments of the present disclosure provides a computer program comprising computer executable instructions for implementing the method as described above when executed.
One or more of the above-described embodiments may provide the following advantages or benefits: the problem that the mode of recommending the product marketing information to the user is single and boring can be solved at least partially, the user is guided to do various actions through digital human technology, the product marketing information is recommended to the user in a reward feedback mode, interestingness of an information recommendation process can be improved, the product marketing mode is richer, attractive, and product rate is improved.
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The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:
FIG. 1 schematically illustrates an information recommendation method and apparatus system architecture according to an embodiment of the present disclosure;
FIG. 2 schematically shows a flow chart of an information recommendation method according to an embodiment of the present disclosure;
FIG. 3 schematically shows a schematic of an image of a motion made by a user according to an embodiment of the present disclosure;
FIG. 4 schematically shows a schematic of an image of a motion made by a user according to another embodiment of the present disclosure;
FIG. 5 schematically shows a flow chart of an information recommendation method according to another embodiment of the present disclosure;
FIG. 6 schematically illustrates a flow chart of an information recommendation method according to yet another embodiment of the present disclosure;
FIG. 7 schematically shows a block diagram of an information recommendation device according to an embodiment of the present disclosure; and
fig. 8 schematically shows a block diagram of an electronic device adapted to implement an information recommendation method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.
Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). Where a convention analogous to "A, B or at least one of C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B or C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
With the rapid development and application of technologies such as artificial intelligence, big data, biological recognition, 5G communication and the like, people are more and more eager for a more natural man-machine interaction mode, the development of digital people technology enables digital people to broadcast, and the digital people guide users to do various actions.
The embodiment of the disclosure provides an information recommendation method and device based on digital people, electronic equipment and a medium. The method comprises the steps of firstly displaying an action skeleton diagram, then capturing actions of a user imitating the action skeleton diagram to obtain user action skeleton data, then determining action matching degree of the user action skeleton data and the action skeleton diagram, and recommending product marketing information corresponding to the action skeleton diagram to the user when the action matching degree reaches a preset threshold value. In this way, the user is guided to complete various actions through the digital human technology, product marketing information is recommended to the user in a reward feedback mode, interactivity and interestingness of the information recommendation process can be improved, the product marketing mode is richer, attractive, and product rate is improved.
It should be noted that the method and apparatus determined by the embodiments of the present disclosure may be used in the financial field, and may also be used in any field other than the financial field, which is not limited by the present disclosure.
Fig. 1 schematically shows a system architecture 100 of an information recommendation method and apparatus according to an embodiment of the present disclosure. It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.
As shown in fig. 1, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (for example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to the user request) to the terminal device.
According to the embodiment of the disclosure, an action skeleton map may be provided in a user interface of a client application of the terminal device 101, 102, 103, and then the terminal device 101, 102, 103 captures an action performed by the user according to the action skeleton map, and the degree of action matching of the action performed by the user and the given action skeleton map is determined by the terminal device 101, 102, 103 or the server 105, and when the degree of action matching reaches a predetermined threshold (for example, 80%), related product marketing information is recommended to the user through the terminal device 101, 102, 103.
It should be noted that the information recommendation method provided by the embodiments of the present disclosure may be generally executed by the terminal devices 101, 102, and 103. Accordingly, the information recommendation device provided by the embodiment of the present disclosure may be generally disposed in the terminal devices 101, 102, 103. The information recommendation method provided by the embodiment of the present disclosure may also be executed by the terminal devices 101, 102, and 103 in part and the server 105 in part. Accordingly, the information recommendation device provided by the embodiment of the present disclosure may also be partially disposed in the terminal devices 101, 102, and 103, and partially disposed in the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Fig. 2 schematically shows a flow chart of an information recommendation method according to an embodiment of the present disclosure.
As shown in fig. 2, the information recommendation method according to the embodiment may include operations S210 to S240.
In operation S210, an action skeleton map is presented. For example, an action skeleton map is provided in the user interaction interface of the terminal devices 101, 102, 103. The action skeleton diagram can be a simple action such as finger stroke, and the expansion can be a complex action such as whole body movement. Alternatively, the action skeleton map may also be a continuously varying series of actions. In some embodiments, a corresponding action skeleton map may be presented according to the action difficulty selected by the user.
In operation S220, the motion of the user imitating the motion skeleton diagram is captured, and the user motion skeleton data is obtained. For example, the terminal devices 101, 102, and 103 capture images of the users, and perform data processing (for example, human body posture detection, gesture recognition, or the like) through the terminal devices 101, 102, and 103 or the server 105 to obtain the user action skeleton data.
According to an embodiment of the present disclosure, the user' S motion may be captured in operation S220, and an image of the motion performed by the user may be displayed on the user interface, so that the user may see a picture of the motion performed by the user, thereby improving interestingness. Wherein the image of the action made by the user may be a virtual simulated image based on digital human technology synthesis.
FIG. 3 schematically shows an illustration of an image of a motion made by a user according to an embodiment of the disclosure. Fig. 3 shows a screen of the user interface in which the user performs a finger stroke motion. Wherein, the user opens the palm according to the skeleton distribution of the fingers, the positions of the skeleton points and the skeleton intervals, and performs finger stroke.
Fig. 4 schematically shows an illustration of an image of a motion made by a user according to another embodiment of the present disclosure. The image in the user interface when the user is doing a full body motion is shown in fig. 4. Wherein, the user does the actions of bifurcating arms, bifurcating waist and separating legs according to the action skeleton layout of the whole body action, the positions of the skeleton points and the like.
In operation S230, a degree of motion matching of the user motion skeleton data with the motion skeleton map is determined. According to the embodiment of the disclosure, the action matching degree can be calculated based on the matching number of the human skeleton points and the skeletons in the action skeleton map and the action skeleton data of the user.
In operation S240, product marketing information corresponding to the action skeleton map is recommended to the user when the action matching degree reaches a predetermined threshold value. Therefore, the participation degree of the user can be improved and the interestingness is increased in the process of recommending the product marketing information to the user.
The product marketing information corresponding to the action skeleton map is, for example, product marketing information set in advance for the action skeleton map. For example, the action skeleton map can be classified according to difficulty, and then action skeleton maps of different difficulty classes correspond to product marketing information of different levels or contents.
As another example, the product marketing information corresponding to the action skeletal graph may be product marketing information associated with content of the action skeletal graph. Wherein the content design of the action skeleton diagram is associated with the content of product marketing.
According to an embodiment of the present disclosure, the content of the action skeleton map is associated with product marketing information. Wherein the association of the content of the action skeleton diagram with the product marketing information may include any one or more of the following; for example, the action content of the action skeleton diagram is the action made by a business person or a user of a product related to product marketing information, for example, for a financial product, the action content of the action skeleton diagram may be the action of a bank teller for paying money, and the like; or, for example, business knowledge related to product marketing information can be set in the background of the action skeleton diagram, so that the business knowledge can be learnt in a latent way in the process that the user acts according to the action skeleton diagram; or for example, multimedia data of a business scene related to product marketing information is set in the background of the action skeleton diagram, for example, the background of the action skeleton diagram can be set as a transaction hall for bank financing products; or the action content of the action skeleton graph is set for the guide based on one or more questions related to the product marketing information.
The product marketing message may be, for example, a product function introduction, a product use introduction, or various coupons, etc. For example, for a bank financing product, the product marketing information may be, for example, financing-related knowledge points, mall points, or coupons.
According to other embodiments of the present disclosure, after operation S240, if the user selects to continue the challenge, the action skeleton map is updated, and operations S210 to S240 are repeatedly performed. Wherein the updated action skeleton map has a higher complexity than the action skeleton map before the update.
Fig. 5 schematically shows a flowchart of an information recommendation method according to another embodiment of the present disclosure.
As shown in fig. 5, the information recommendation method according to the embodiment may include operations S210 to S341.
First, in operation S210, an action skeleton map is presented.
Then, in operation S311, the avatar of the user is replaced in the presentation screen based on the image object selected by the user. For example, a two-dimensional or three-dimensional image model based on digital human technology synthesis may be selected to replace the user's own image.
Next, in operation S220, the motion of the user imitating the motion skeleton diagram is captured, and the user motion skeleton data is obtained.
And presenting an image of the action made by the image object in operation S322.
According to the embodiment of the disclosure, the image of the image object selected by the user can replace the image of the user while or after the action of the user imitating the action skeleton diagram is captured, the action of the user is displayed in the user interface, and the visual interest can be improved. For example, in the example of fig. 4, if the user selects a cartoon character to replace the user's own image, a picture showing the cartoon character with both hands crossing the waist and both legs separated is shown in fig. 4, so that the user can see various actions of the image object of his mood.
Next, in operation S230, a motion matching degree of the user motion bone data with the motion bone map is determined.
Thereafter, in operation S341, when the action matching degree reaches a predetermined threshold value, product marketing information may be recommended to the user through demonstration or broadcast of the image object. Specifically, the picture of the image object demonstration or broadcast can be synthesized based on digital human technology to recommend the product marketing information to the user, so that the interestingness of information recommendation is increased, and the information conversion rate is improved.
Fig. 6 schematically shows a flowchart of an information recommendation method according to still another embodiment of the present disclosure. It is to be understood that fig. 6 is an illustration of an application of the embodiments of the disclosure, and does not constitute any limitation to the disclosure.
As shown in fig. 6, the information recommendation method of this embodiment may include steps S601 to S610.
In step S601, the user enters a digital person guidance portal to guide the user operation.
In step S602, a game entry is entered.
In step S603, an action difficulty level is selected, and the user is guided to select an action difficulty level.
In step S604, user motion capture. For example, the user may be guided to replace his/her avatar with a two-dimensional illustration model synthesized, for example, by digital human technology, and a picture of the action made by the two-dimensional illustration model of the user's mind may be presented in the user interface.
In step S605, the motion matching degree is determined.
In step S606, it is determined whether or not the motion matching degree exceeds 80%. If not, step S607 is executed. If so, go to step S608,
in step S607, when the action matching degree is less than 80%, the process returns to step S602 to repeat the game.
In step S608, when the action matching degree exceeds 80%, the bonus system is entered to obtain bonus. The reward system can give various links, or various business knowledge (such as financial knowledge), or coupons, or interfaces of various client application programs related to product business, so that users can be guided to quickly know the functions, information and the like of various application programs.
The user is then asked whether to continue the challenge at step S609. If yes, returning to step S603 to continue the game; if not, the game is exited at step S610.
The disclosed embodiments can be based on digital human question answering and guide the user to complete actions using the pictorial model and get rewards. For example, when the method is applied to banking, each time an action or a set of actions is performed, a banking-related knowledge point or other reward, such as a financial precious metal, may be played to the user and asked if the user continues to challenge the complexity of the action, which is increasing. Therefore, the activity of user participation can be improved, the user can acquire more financing knowledge, the financing knowledge becomes a potential customer of a financing purchasing user, and more other consumption interests of the user are mined.
Fig. 7 schematically shows a block diagram of an information recommendation device 700 according to an embodiment of the present disclosure.
As shown in fig. 7, the information recommendation apparatus 700 according to an embodiment of the present disclosure may include a presentation module 710, a capture module 720, a matching degree determination module 730, and a reward module 740. The apparatus 700 may be used to implement the information recommendation method described with reference to fig. 2 to 6.
The display module 710 is used for displaying an action skeleton map.
The capturing module 720 is used for capturing the motion of the user imitating the motion skeleton map to obtain the user motion skeleton data. According to another embodiment of the present disclosure, the presentation module 710 is further configured to present an image of the motion made by the user while capturing the motion of the user.
The matching degree determination module 730 is used for determining the action matching degree of the user action bone data and the action bone map.
The reward module 740 is configured to recommend product marketing information corresponding to the action skeleton map to the user when the action matching degree reaches a predetermined threshold.
According to another embodiment of the present disclosure, the apparatus 700 further comprises an update module 750. The update module 750 is configured to update the action skeleton map if the user chooses to continue the challenge. Wherein the updated action skeleton map has a higher complexity than the action skeleton map before the update.
Any number of modules, sub-modules, units, sub-units, or at least part of the functionality of any number thereof according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in any other reasonable manner of hardware or firmware by integrating or packaging a circuit, or in any one of or a suitable combination of software, hardware, and firmware implementations. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the disclosure may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.
For example, any of the presentation module 710, the capture module 720, the matching degree determination module 730, the reward module 740, and the update module 750 may be combined into one module to be implemented, or any one of them may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the presentation module 710, the capture module 720, the matching degree determination module 730, the reward module 740, and the update module 750 may be implemented at least partially as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or in any one of three implementations of software, hardware, and firmware, or in a suitable combination of any of them. Alternatively, at least one of the presentation module 710, the capture module 720, the matching degree determination module 730, the reward module 740, and the update module 750 may be implemented at least in part as a computer program module that, when executed, may perform a corresponding function.
Fig. 8 schematically shows a block diagram of an electronic device 800 adapted to implement an information recommendation method according to an embodiment of the present disclosure. The electronic device 800 illustrated in fig. 8 is only an example and should not bring any limitations to the functionality or scope of use of the embodiments of the present disclosure.
As shown in fig. 8, an electronic device 800 according to an embodiment of the present disclosure includes a processor 801 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)802 or a program loaded from a storage section 808 into a Random Access Memory (RAM) 803. The processor 801 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 801 may also include onboard memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing different actions of the method flows according to embodiments of the present disclosure.
In the RAM 803, various programs and data necessary for the operation of the electronic apparatus 800 are stored. The processor 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. The processor 801 performs various operations of the method flows according to the embodiments of the present disclosure by executing programs in the ROM 802 and/or RAM 803. Note that the programs may also be stored in one or more memories other than the ROM 802 and RAM 803. The processor 801 may also perform various operations of method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.
According to embodiments of the present disclosure, method flows according to embodiments of the present disclosure may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable storage medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 809 and/or installed from the removable medium 811. The computer program, when executed by the processor 801, performs the above-described functions defined in the system of the embodiments of the present disclosure. The systems, devices, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the present disclosure, a computer-readable storage medium may include the ROM 802 and/or RAM 803 described above and/or one or more memories other than the ROM 802 and RAM 803.
Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the method provided by the embodiments of the present disclosure, when the computer program product is run on an electronic device, the program code being adapted to cause the electronic device to carry out the image recognition method provided by the embodiments of the present disclosure.
The computer program, when executed by the processor 801, performs the above-described functions defined in the system/apparatus of the embodiments of the present disclosure. The systems, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
In one embodiment, the computer program may be hosted on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted in the form of a signal on a network medium, distributed, downloaded and installed via communication section 809, and/or installed from removable media 811. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In accordance with embodiments of the present disclosure, program code for executing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, these computer programs may be implemented using high level procedural and/or object oriented programming languages, and/or assembly/machine languages. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user computing device, partly on the user device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.
The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.
Claims (10)
1. An information recommendation method, comprising:
displaying an action skeleton diagram;
capturing the action of the user imitating the action skeleton diagram to obtain user action skeleton data;
determining the action matching degree of the user action bone data and the action bone graph; and
recommending product marketing information corresponding to the action skeleton map to the user when the action matching degree reaches a preset threshold value.
2. The method of claim 1, wherein after recommending product marketing information to the user corresponding to the action skeletal map when the action match reaches a predetermined threshold, the method further comprises:
in the case that the user selects a continuing challenge, updating the action skeleton map, and repeatedly performing the operations of capturing, determining an action matching degree, and recommending information when the action matching degree reaches a preset threshold;
wherein the updated action skeleton map is more complex than the action skeleton map before updating.
3. The method of claim 1, wherein the method further comprises:
displaying an image of the motion made by the user while capturing the motion of the user.
4. The method of claim 3, wherein the presenting the image of the action by the user comprises:
replacing the user's avatar in the presentation based on the user-selected image object; and
and displaying the image of the action made by the image object.
5. The method of claim 4, wherein the recommending, to the user, product marketing information corresponding to the action skeletal graph when the action match reaches a predetermined threshold comprises:
and recommending the product marketing information to the user through the demonstration or broadcast of the image object.
6. The method of claim 1, wherein said determining an action match of said user action skeletal data to said action skeletal map comprises:
and calculating the action matching degree based on the matching number of the user action skeleton data and the human skeleton points and the skeletons in the action skeleton map.
7. The method of any of claims 1-6, wherein the content of the action skeletal graph is associated with the product marketing message comprises at least one of:
the action content of the action skeleton diagram is the action made by the service personnel or the user of the product related to the product marketing information;
setting business knowledge related to the product marketing information in the background of the action skeleton diagram;
setting multimedia data of a business scene related to the product marketing information in the background of the action skeleton diagram; or
The action content of the action skeleton graph is set for the guide based on one or more questions related to the product marketing information.
8. An information recommendation apparatus comprising:
the display module is used for displaying the action skeleton map;
the capturing module is used for capturing the motion of the user imitating the motion skeleton diagram to obtain the motion skeleton data of the user;
the matching degree determining module is used for determining the action matching degree of the user action bone data and the action bone graph; and
and the reward module is used for recommending product marketing information corresponding to the action skeleton map to the user when the action matching degree reaches a preset threshold value.
9. An electronic device, comprising:
one or more memories storing executable instructions; and
one or more processors executing the executable instructions to implement the method of any one of claims 1-7.
10. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 7.
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