CN116450929A - Media content recommendation method and system based on artificial intelligence system - Google Patents
Media content recommendation method and system based on artificial intelligence system Download PDFInfo
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Abstract
The invention provides a media content recommendation method and a system based on an artificial intelligence system, wherein the system comprises the following steps: a media library, a server, storing the media library in the server; the intelligent screen is connected with the server and used for acquiring a media library in the server, and the acquisition module is used for acquiring a face image according to a control signal when clicking any display area of the intelligent screen to acquire first media content; transmitting the face image to a processor; the processor has: the system comprises a loading module, a control module and an artificial intelligence system; in the application, the face image is acquired through the camera so as to analyze the gender and age of the face image. Based on a large amount of statistics, the favorites of different crowds on media content selection are obtained to form historical data, and iterative training is carried out through an artificial intelligence system to form a recommendation model. After the camera acquires the face image, accurate recommendation of the media content can be performed according to the analyzed gender and age.
Description
Technical Field
The invention relates to the technical field of electronic information, in particular to a media content recommendation method and system based on an artificial intelligence system.
Background
When carrying out the construction of wisdom community, wisdom screen has extensive application, can realize community management, advertisement distribution, the dynamic show of community work and peripheral shop show etc. through wisdom screen, can say that wisdom screen is the inseparable part of future wisdom community, through predetermine including foretell media content in wisdom screen, only need browse wisdom screen and just can obtain peripheral information, this is the main direction of wisdom community construction.
When people in the community browse media content through the intelligent screen, as the content on the intelligent screen is rolling, and the content focused by different people has great difference, such as just through establishing interaction between the intelligent screen and the terminal, the people can not accurately recommend interesting content to different people.
Disclosure of Invention
Accordingly, a primary object of the present invention is to provide a media content recommendation method and system based on an artificial intelligence system.
The technical scheme adopted by the invention is as follows:
the media content recommendation method based on the artificial intelligence system comprises the following steps:
setting a media library, and storing the media library in a server;
connecting the intelligent screen with a server, and displaying the media content of the media library on the intelligent screen in a plurality of display areas according to a set rule;
when any display area of the intelligent screen is clicked to acquire first media content, a feedback signal is sent to a processor of the intelligent screen based on a distribution link corresponding to the display area, after the processor receives the feedback signal, a control signal for controlling at least one camera arranged on the intelligent screen to start is formed, and the camera acquires a face image according to the control signal; transmitting the face image to a processor;
the processor receives the face image and loads the corresponding acquired first media content; the processor inputs the face image and the first media content to an artificial intelligence system, and the artificial intelligence system judges gender and age range according to the face image;
preselecting a first media content set in a media library of the server based on the gender and age range characteristics as screening basis;
the artificial intelligence system judges the association table of the first media content; performing secondary screening on the first media content set based on the association table to obtain a second media content set;
setting each media content in the second media content set as a first priority; setting each of the remaining media content in the first media content set as a second priority, and setting a recommendation list containing the first media content set based on the first priority and the second priority;
the recommendation list is input to a control module, the control module obtains display parameters of the display area, the display area is set to be a display window and a floating window based on the display parameters, the display window is used for displaying and obtaining the first media content, the floating window is used for displaying the recommendation list, and second media content is obtained according to the recommendation list.
Further, the artificial intelligence system is also provided with a labeling module and an association module;
the labeling module is used for correspondingly labeling the first media content based on the gender and age range obtained through the judgment of the face image so as to form a screening basis, and the screening basis is stored in a feature library;
the association module is used for associating the screening basis with the first media content correspondingly, and updating the associated media content in the association table correspondingly.
Further, the intelligent screen further has:
the control module is provided with a display program, and a main interface displayed on a main application screen of the intelligent screen is configured based on the display program;
the input module is connected to the control module through an input interface, and inputs a screen division strategy through the input module, and the screen division strategy is applied to a display program to divide the main interface into a plurality of display areas;
a configuration unit, configured to configure a distribution link for each display area;
the content media recommending module is used for recommending the media content to the corresponding display through the distributing link based on the selection or setting rule of the recommending list;
and the switching module is connected to the content media recommendation module and is used for switching between selection and setting rules based on the recommendation list.
Further, when a plurality of media contents are selected from the recommendation list, recording the selection sequence in the recommendation list, and sequentially calling the distribution corresponding to a plurality of distribution links to a plurality of display areas for synchronous display by the content media recommendation module according to the selection sequence;
if the number of the selected media contents is larger than the display area, corresponding sorting is carried out according to the selection sequence, and at least two groups of queues are formed according to the sorting; wherein each set of queues contains a plurality of display tasks, and the number of display tasks is equal to or less than the number of distribution links.
Further, the content media recommendation module has:
the task management module is used for acquiring a plurality of tasks to be displayed; the tasks to be displayed are correspondingly ordered according to the selection sequence;
the task management module is provided with a dispatching unit and a task execution unit, wherein the dispatching unit is used for dividing the sequenced tasks to be displayed into at least one group of queues, each group of queues comprises a plurality of tasks to be displayed, and the number of the tasks to be displayed is less than or equal to the number of distribution links;
the dispatching unit is connected with the task execution unit, and the task execution unit is used for distributing the tasks to be displayed to a plurality of display areas through the distribution links correspondingly for synchronous display.
Further, a layout relation table is correspondingly arranged in the display areas, the layout relation table is provided with a plurality of pieces of position information which are formed by coordinate sets and represent specific display areas of the intelligent screen, and each piece of position information corresponds to a designated display area.
The application also provides a media content recommendation method system based on the artificial intelligence system, which comprises the following steps:
a media library configured as a storage unit of media contents or a storage unit for media content aggregation formed based on one or a combination of the internet and a cloud network;
a server storing the media library in the server;
the intelligent screen is connected with the server and used for acquiring a media library in the server and displaying media contents of the media library on the intelligent screen in a plurality of display areas according to a set rule, wherein a plurality of cameras are arranged on the intelligent screen;
the acquisition module is used for sending a feedback signal to the processor of the intelligent screen based on a distribution link corresponding to the display area when clicking any display area of the intelligent screen to acquire the first media content, and forming a control signal after the processor receives the feedback signal, so that the camera acquires a face image according to the control signal; transmitting the face image to a processor;
the processor has: the system comprises a loading module, a control module and an artificial intelligence system;
the loading module is used for loading the received face image and loading the correspondingly acquired first media content;
an artificial intelligence system coupled to the loading module, the artificial intelligence system comprising:
a first judging module for judging gender and age range based on the face image;
a first screening module, configured to pre-select a first set of media content in a media library of the server based on the gender and age range characteristics as screening basis;
the marking module is used for marking the first media content correspondingly based on gender and age range to form a screening basis, and storing the screening basis in a feature library;
the association module is used for associating the screening basis with the first media content correspondingly, and updating the associated media content in the association table correspondingly;
the second judging module is used for judging the association table of the first media content;
the second screening module is used for carrying out secondary screening on the first media content set based on the association table to obtain a second media content set;
the priority setting module is used for setting each media content in the second media content set as a first priority; setting each of the remaining media content in the first media content set as a second priority, and setting a recommendation list containing the first media content set based on the first priority and the second priority;
the control module is used for inputting the recommendation list into the control module, the control module is used for obtaining display parameters of the display area, setting the display area to be a display window and a floating window based on the display parameters, the display window is used for displaying and obtaining the first media content, and the floating window is used for displaying the recommendation list and obtaining the second media content according to the recommendation list.
Further, the processor is arranged in the intelligent screen;
and a display program is arranged in the control module, and a main interface displayed on the intelligent screen main application screen is configured based on the display program.
Further, the processor further comprises:
the input module is connected to the control module through an input interface, and inputs a screen division strategy through the input module, and the screen division strategy is applied to a display program to divide the main interface into a plurality of display areas;
a configuration unit, configured to configure a distribution link for each display area;
the content media recommending module is used for recommending the media content to the corresponding display through the distributing link based on the selection or setting rule of the recommending list;
and the switching module is connected to the content media recommendation module and is used for switching between selection and setting rules based on the recommendation list.
Further, the content media recommendation module has:
the task management module is used for acquiring a plurality of tasks to be displayed; the tasks to be displayed are correspondingly ordered according to the selection sequence;
the task management module is provided with a dispatching unit and a task execution unit, wherein the dispatching unit is used for dividing the sequenced tasks to be displayed into at least one group of queues, each group of queues comprises a plurality of tasks to be displayed, and the number of the tasks to be displayed is less than or equal to the number of distribution links;
the dispatching unit is connected with the task execution unit, and the task execution unit is used for distributing the tasks to be displayed to a plurality of display areas through the distribution links correspondingly for synchronous display.
In this application, set up a camera on the wisdom screen, acquire face image through the camera to its gender, age of analysis. Based on a large amount of statistics, the favorites of different crowds on media content selection are obtained to form historical data, and iterative training is carried out through an artificial intelligence system to form a recommendation model. After the camera acquires the face image, accurate recommendation of the media content can be performed according to the analyzed gender and age.
When any display area of the intelligent screen is clicked to acquire first media content, the camera acquires a face image according to a control signal; transmitting the face image to a processor; the processor receives the face image and loads the corresponding acquired first media content; the processor inputs the face image and the first media content to an artificial intelligence system, and the artificial intelligence system judges gender and age range according to the face image; preselecting a first media content set in a media library of the server based on the gender and age range characteristics as screening basis; the artificial intelligence system judges the association table of the first media content; performing secondary screening on the first media content set based on the association table to obtain a second media content set; setting each media content in the second media content set as a first priority; setting each of the remaining media content in the first media content set as a second priority, and setting a recommendation list containing the first media content set based on the first priority and the second priority; the recommendation list is input to a control module, the control module obtains display parameters of the display area, the display area is set to be a display window and a floating window based on the display parameters, the display window is used for displaying and obtaining the first media content, the floating window is used for displaying the recommendation list, and second media content is obtained according to the recommendation list.
In the above, the recommendation of the next content of interest may be acquired according to the recommendation list.
Drawings
The following drawings are illustrative of the invention and are not intended to limit the scope of the invention, in which:
FIG. 1 is a flow chart of the method of the present invention;
fig. 2 is a schematic diagram of the framework of the present invention.
Detailed Description
The present invention will be further described in detail with reference to the following specific examples, which are given by way of illustration, in order to make the objects, technical solutions, design methods and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Example 1
Referring to fig. 1, the present invention provides a media content recommendation method based on an artificial intelligence system, comprising the steps of:
setting a media library, and storing the media library in a server; wherein, it is configured as the storage unit of the media content, or the media library is a storage unit for media content aggregation formed based on one or combination of internet, cloud network;
connecting the intelligent screen with a server, and displaying the media content of the media library on the intelligent screen in a plurality of display areas according to a set rule;
when any display area of the intelligent screen is clicked to acquire first media content, a feedback signal is sent to a processor of the intelligent screen based on a distribution link corresponding to the display area, after the processor receives the feedback signal, a control signal for controlling at least one camera arranged on the intelligent screen to start is formed, and the camera acquires a face image according to the control signal; transmitting the face image to a processor;
the processor receives the face image and loads the corresponding acquired first media content; the processor inputs the face image and the first media content to an artificial intelligence system, and the artificial intelligence system judges gender and age range according to the face image;
preselecting a first media content set in a media library of the server based on the gender and age range characteristics as screening basis;
the artificial intelligence system judges the association table of the first media content; performing secondary screening on the first media content set based on the association table to obtain a second media content set;
setting each media content in the second media content set as a first priority; setting each of the remaining media content in the first media content set as a second priority, and setting a recommendation list containing the first media content set based on the first priority and the second priority;
the recommendation list is input to a control module, the control module obtains display parameters of the display area, the display area is set to be a display window and a floating window based on the display parameters, the display window is used for displaying and obtaining the first media content, the floating window is used for displaying the recommendation list, and second media content is obtained according to the recommendation list.
In the above, the artificial intelligence system is further provided with a labeling module and an association module;
the labeling module is used for correspondingly labeling the first media content based on the gender and age range obtained through the judgment of the face image so as to form a screening basis, and the screening basis is stored in a feature library;
the association module is used for associating the screening basis with the first media content correspondingly, and updating the associated media content in the association table correspondingly.
In the above, the smart screen further has:
the control module is provided with a display program, and a main interface displayed on a main application screen of the intelligent screen is configured based on the display program;
the input module is connected to the control module through an input interface, and inputs a screen division strategy through the input module, and the screen division strategy is applied to a display program to divide the main interface into a plurality of display areas;
a configuration unit, configured to configure a distribution link for each display area;
the content media recommending module is used for recommending the media content to the corresponding display through the distributing link based on the selection or setting rule of the recommending list;
and the switching module is connected to the content media recommendation module and is used for switching between selection and setting rules based on the recommendation list.
When a plurality of media contents are selected from the recommendation list, recording the selection sequence in the recommendation list, and sequentially calling the corresponding distribution of a plurality of distribution links to a plurality of display areas for synchronous display by the content media recommendation module according to the selection sequence;
if the number of the selected media contents is larger than the display area, corresponding sorting is carried out according to the selection sequence, and at least two groups of queues are formed according to the sorting; wherein each set of queues contains a plurality of display tasks, and the number of display tasks is equal to or less than the number of distribution links.
In the above, the content media recommendation module has:
the task management module is used for acquiring a plurality of tasks to be displayed; the tasks to be displayed are correspondingly ordered according to the selection sequence;
the task management module is provided with a dispatching unit and a task execution unit, wherein the dispatching unit is used for dividing the sequenced tasks to be displayed into at least one group of queues, each group of queues comprises a plurality of tasks to be displayed, and the number of the tasks to be displayed is less than or equal to the number of distribution links;
the dispatching unit is connected with the task execution unit, and the task execution unit is used for distributing the tasks to be displayed to a plurality of display areas through the distribution links correspondingly for synchronous display.
In the above, a layout relation table is correspondingly provided in the plurality of display areas, and the layout relation table has a plurality of pieces of position information which are formed by coordinate sets and represent specific display areas for the intelligent screen, wherein each piece of position information corresponds to a designated display area.
In this application, set up a camera on the wisdom screen, acquire face image through the camera to its gender, age of analysis. Based on a large amount of statistics, the favorites of different crowds on media content selection are obtained to form historical data, and iterative training is carried out through an artificial intelligence system to form a recommendation model. After the camera acquires the face image, accurate recommendation of the media content can be performed according to the analyzed gender and age.
In some embodiments, in addition to performing face recognition, other characteristics of the character may be analyzed, including without limitation hair, clothing, bags, and the like. After the age and sex are acquired through face recognition, hair style characteristics, dressing characteristics and the like can be correspondingly acquired, and the characteristics are written into a recommended model, so that the method can be implemented as follows.
A media content recommendation method based on an artificial intelligence system, comprising the steps of:
setting a media library, and storing the media library in a server; wherein, it is configured as the storage unit of the media content, or the media library is a storage unit for media content aggregation formed based on one or combination of internet, cloud network;
connecting the intelligent screen with a server, and displaying the media content of the media library on the intelligent screen in a plurality of display areas according to a set rule;
the intelligent screen is provided with a monitoring camera which is used for acquiring a plurality of groups of character images within the foreground range of the monitoring camera and transmitting the character images to the artificial intelligent system;
the artificial intelligence system identifies and screens a plurality of groups of character images to obtain character images meeting the requirements (the character images can clearly obtain the characteristics of faces, heads, clothes and the like); inputting the character image into a recommended model, and training in the recommended model to obtain gender, age characteristics, hair style characteristics, dressing characteristics and the like; performing superposition screening in a media library according to the characteristics to obtain a recommendation list;
and inputting the recommendation list to a control module, wherein the control module acquires the display parameters of the display area and displays the recommendation list in the display area.
Based on the above description, in some embodiments, the area of interest may be known by analyzing some typical characteristics of the character image, such as by wearing clothes, recommending store information for selling clothes in nearby business establishments, and recommending store information for nearby business establishments based on hair styling characteristics.
Example 2
Referring to fig. 2, the present application provides a media content recommendation method system based on an artificial intelligence system, including:
a media library configured as a storage unit of media contents or a storage unit for media content aggregation formed based on one or a combination of the internet and a cloud network;
a server storing the media library in the server;
the intelligent screen is connected with the server and used for acquiring a media library in the server and displaying media contents of the media library on the intelligent screen in a plurality of display areas according to a set rule, wherein a plurality of cameras are arranged on the intelligent screen;
the acquisition module is used for sending a feedback signal to the processor of the intelligent screen based on a distribution link corresponding to the display area when clicking any display area of the intelligent screen to acquire the first media content, and forming a control signal after the processor receives the feedback signal, so that the camera acquires a face image according to the control signal; transmitting the face image to a processor;
the processor has: the system comprises a loading module, a control module and an artificial intelligence system;
the loading module is used for loading the received face image and loading the correspondingly acquired first media content;
an artificial intelligence system coupled to the loading module, the artificial intelligence system comprising:
a first judging module for judging gender and age range based on the face image;
a first screening module, configured to pre-select a first set of media content in a media library of the server based on the gender and age range characteristics as screening basis;
the marking module is used for marking the first media content correspondingly based on gender and age range to form a screening basis, and storing the screening basis in a feature library;
the association module is used for associating the screening basis with the first media content correspondingly, and updating the associated media content in the association table correspondingly;
the second judging module is used for judging the association table of the first media content;
the second screening module is used for carrying out secondary screening on the first media content set based on the association table to obtain a second media content set;
the priority setting module is used for setting each media content in the second media content set as a first priority; setting each of the remaining media content in the first media content set as a second priority, and setting a recommendation list containing the first media content set based on the first priority and the second priority;
the control module is used for inputting the recommendation list into the control module, the control module is used for obtaining display parameters of the display area, setting the display area to be a display window and a floating window based on the display parameters, the display window is used for displaying and obtaining the first media content, and the floating window is used for displaying the recommendation list and obtaining the second media content according to the recommendation list.
Further, the processor is arranged in the intelligent screen;
and a display program is arranged in the control module, and a main interface displayed on the intelligent screen main application screen is configured based on the display program.
Further, the processor further comprises:
the input module is connected to the control module through an input interface, and inputs a screen division strategy through the input module, and the screen division strategy is applied to a display program to divide the main interface into a plurality of display areas;
a configuration unit, configured to configure a distribution link for each display area;
the content media recommending module is used for recommending the media content to the corresponding display through the distributing link based on the selection or setting rule of the recommending list;
and the switching module is connected to the content media recommendation module and is used for switching between selection and setting rules based on the recommendation list.
Further, the content media recommendation module has:
the task management module is used for acquiring a plurality of tasks to be displayed; the tasks to be displayed are correspondingly ordered according to the selection sequence;
the task management module is provided with a dispatching unit and a task execution unit, wherein the dispatching unit is used for dividing the sequenced tasks to be displayed into at least one group of queues, each group of queues comprises a plurality of tasks to be displayed, and the number of the tasks to be displayed is less than or equal to the number of distribution links;
the dispatching unit is connected with the task execution unit, and the task execution unit is used for distributing the tasks to be displayed to a plurality of display areas through the distribution links correspondingly for synchronous display.
In this application, set up a camera on the wisdom screen, acquire face image through the camera to its gender, age of analysis. Based on a large amount of statistics, the favorites of different crowds on media content selection are obtained to form historical data, and iterative training is carried out through an artificial intelligence system to form a recommendation model. After the camera acquires the face image, accurate recommendation of the media content can be performed according to the analyzed gender and age.
When any display area of the intelligent screen is clicked to acquire first media content, the camera acquires a face image according to a control signal; transmitting the face image to a processor; the processor receives the face image and loads the corresponding acquired first media content; the processor inputs the face image and the first media content to an artificial intelligence system, and the artificial intelligence system judges gender and age range according to the face image; preselecting a first media content set in a media library of the server based on the gender and age range characteristics as screening basis; the artificial intelligence system judges the association table of the first media content; performing secondary screening on the first media content set based on the association table to obtain a second media content set; setting each media content in the second media content set as a first priority; setting each of the remaining media content in the first media content set as a second priority, and setting a recommendation list containing the first media content set based on the first priority and the second priority; the recommendation list is input to a control module, the control module obtains display parameters of the display area, the display area is set to be a display window and a floating window based on the display parameters, the display window is used for displaying and obtaining the first media content, the floating window is used for displaying the recommendation list, and second media content is obtained according to the recommendation list.
In this application, set up a camera on the wisdom screen, acquire face image through the camera to its gender, age of analysis. Based on a large amount of statistics, the favorites of different crowds on media content selection are obtained to form historical data, and iterative training is carried out through an artificial intelligence system to form a recommendation model. After the camera acquires the face image, accurate recommendation of the media content can be performed according to the analyzed gender and age.
In some embodiments, in addition to performing face recognition, other characteristics of the character may be analyzed, including without limitation hair, clothing, bags, and the like. After the age and sex are acquired through face recognition, hair style characteristics, dressing characteristics and the like can be correspondingly acquired, and the characteristics are written into a recommended model, so that the method can be implemented as follows.
A media content recommendation method based on an artificial intelligence system, comprising the steps of:
setting a media library, and storing the media library in a server; wherein, it is configured as the storage unit of the media content, or the media library is a storage unit for media content aggregation formed based on one or combination of internet, cloud network;
connecting the intelligent screen with a server, and displaying the media content of the media library on the intelligent screen in a plurality of display areas according to a set rule;
the intelligent screen is provided with a monitoring camera which is used for acquiring a plurality of groups of character images within the foreground range of the monitoring camera and transmitting the character images to the artificial intelligent system;
the artificial intelligence system identifies and screens a plurality of groups of character images to obtain character images meeting the requirements (the character images can clearly obtain the characteristics of faces, heads, clothes and the like); inputting the character image into a recommended model, and training in the recommended model to obtain gender, age characteristics, hair style characteristics, dressing characteristics and the like; performing superposition screening in a media library according to the characteristics to obtain a recommendation list;
and inputting the recommendation list to a control module, wherein the control module acquires the display parameters of the display area and displays the recommendation list in the display area.
Based on the above description, in some embodiments, the area of interest may be known by analyzing some typical characteristics of the character image, such as by wearing clothes, recommending store information for selling clothes in nearby business establishments, and recommending store information for nearby business establishments based on hair styling characteristics.
Example 3:
another embodiment is provided.
A media content recommendation method based on an artificial intelligence system, comprising the steps of:
setting a media library, and storing the media library in a server; wherein, it is configured as the storage unit of the media content, or the media library is a storage unit for media content aggregation formed based on one or combination of internet, cloud network;
connecting the intelligent screen with a server, and displaying the media content of the media library on the intelligent screen in a plurality of display areas according to a set rule;
the intelligent screen is provided with a monitoring camera which is used for acquiring a plurality of groups of character images within the foreground range of the monitoring camera and transmitting the character images to the identification module; wherein the identification module is arranged in the processor;
the identification module is used for selecting at least one person image meeting the requirements from a plurality of groups of person images, identifying the number of people in the person images, judging the position of each person in the foreground, inputting the judging result to the control module, controlling a plurality of cameras arranged on the intelligent screen to work simultaneously by the control module, respectively acquiring at least one group of shooting images of the foreground of each camera, respectively conveying the shooting images to the artificial intelligent system,
the artificial intelligence system respectively identifies and screens the shot images to obtain the shot images meeting the requirements (the face, the head characteristics, the clothing characteristics and the like can be clearly obtained); inputting the shot image into a recommended model, and training in the recommended model to obtain gender, age characteristics, hair style characteristics, dressing characteristics and the like; performing superposition screening in a media library according to the characteristics to obtain a plurality of recommendation lists;
and inputting a plurality of recommendation lists into a control module, wherein the control module acquires display parameters of the display area, and displaying the recommendation lists in different display areas.
In this embodiment, it is depicted that when there are a plurality of persons in the foreground of the monitoring camera (foreground refers to the imaging range of the monitoring camera), individual recommendation for a plurality of different persons can be achieved.
In this embodiment, it is required to embed a plurality of cameras on the smart screen, each camera being connected to the control module, and acquire an image in a corresponding foreground position based on a control instruction of the control module.
The foregoing description of embodiments of the invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvements in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. The media content recommendation method based on the artificial intelligence system is characterized by comprising the following steps of:
setting a media library, and storing the media library in a server;
connecting the intelligent screen with a server, and displaying the media content of the media library on the intelligent screen in a plurality of display areas according to a set rule;
when any display area of the intelligent screen is clicked to acquire first media content, a feedback signal is sent to a processor of the intelligent screen based on a distribution link corresponding to the display area, after the processor receives the feedback signal, a control signal for controlling at least one camera arranged on the intelligent screen to start is formed, and the camera acquires a face image according to the control signal; transmitting the face image to a processor;
the processor receives the face image and loads the corresponding acquired first media content; the processor inputs the face image and the first media content to an artificial intelligence system, and the artificial intelligence system judges gender and age range according to the face image;
preselecting a first media content set in a media library of the server based on the gender and age range characteristics as screening basis;
the artificial intelligence system judges the association table of the first media content; performing secondary screening on the first media content set based on the association table to obtain a second media content set;
setting each media content in the second media content set as a first priority; setting each of the remaining media content in the first media content set as a second priority, and setting a recommendation list containing the first media content set based on the first priority and the second priority;
the recommendation list is input to a control module, the control module obtains display parameters of the display area, the display area is set to be a display window and a floating window based on the display parameters, the display window is used for displaying and obtaining the first media content, the floating window is used for displaying the recommendation list, and second media content is obtained according to the recommendation list.
2. The media content recommendation method based on an artificial intelligence system according to claim 1, wherein an annotation module and an association module are further provided in the artificial intelligence system;
the labeling module is used for correspondingly labeling the first media content based on the gender and age range obtained through the judgment of the face image so as to form a screening basis, and the screening basis is stored in a feature library;
the association module is used for associating the screening basis with the first media content correspondingly, and updating the associated media content in the association table correspondingly.
3. The media content recommendation method based on an artificial intelligence system according to claim 1, wherein the intelligent screen further has:
the control module is provided with a display program, and a main interface displayed on a main application screen of the intelligent screen is configured based on the display program;
the input module is connected to the control module through an input interface, and inputs a screen division strategy through the input module, and the screen division strategy is applied to a display program to divide the main interface into a plurality of display areas;
a configuration unit, configured to configure a distribution link for each display area;
the content media recommending module is used for recommending the media content to the corresponding display through the distributing link based on the selection or setting rule of the recommending list;
and the switching module is connected to the content media recommendation module and is used for switching between selection and setting rules based on the recommendation list.
4. The media content recommendation method based on an artificial intelligence system according to claim 3, wherein when a plurality of media contents are selected from the recommendation list, recording a selection order in the recommendation list, and sequentially calling, by the content media recommendation module, distribution corresponding to a plurality of distribution links to a plurality of display areas according to the selection order for synchronous display;
if the number of the selected media contents is larger than the display area, corresponding sorting is carried out according to the selection sequence, and at least two groups of queues are formed according to the sorting; wherein each set of queues contains a plurality of display tasks, and the number of display tasks is equal to or less than the number of distribution links.
5. The artificial intelligence system based media content recommendation method of claim 3 or 4 wherein the content media recommendation module has:
the task management module is used for acquiring a plurality of tasks to be displayed; the tasks to be displayed are correspondingly ordered according to the selection sequence;
the task management module is provided with a dispatching unit and a task execution unit, wherein the dispatching unit is used for dividing the sequenced tasks to be displayed into at least one group of queues, each group of queues comprises a plurality of tasks to be displayed, and the number of the tasks to be displayed is less than or equal to the number of distribution links;
the dispatching unit is connected with the task execution unit, and the task execution unit is used for distributing the tasks to be displayed to a plurality of display areas through the distribution links correspondingly for synchronous display.
6. The media content recommendation method based on an artificial intelligence system according to claim 1, wherein a layout relation table is provided corresponding to a plurality of the display areas, the layout relation table has a plurality of pieces of position information representing specific display areas for the intelligent screen formed by a set of coordinates, and each piece of position information corresponds to a designated display area.
7. The media content recommendation method system based on the artificial intelligence system is characterized by comprising the following steps:
a media library configured as a storage unit of media contents or a storage unit for media content aggregation formed based on one or a combination of the internet and a cloud network;
a server storing the media library in the server;
the intelligent screen is connected with the server and used for acquiring a media library in the server and displaying media contents of the media library on the intelligent screen in a plurality of display areas according to a set rule, wherein a plurality of cameras are arranged on the intelligent screen;
the acquisition module is used for sending a feedback signal to the processor of the intelligent screen based on a distribution link corresponding to the display area when clicking any display area of the intelligent screen to acquire the first media content, and forming a control signal after the processor receives the feedback signal, so that the camera acquires a face image according to the control signal; transmitting the face image to a processor;
the processor has: the system comprises a loading module, a control module and an artificial intelligence system;
the loading module is used for loading the received face image and loading the correspondingly acquired first media content;
an artificial intelligence system coupled to the loading module, the artificial intelligence system comprising:
a first judging module for judging gender and age range based on the face image;
a first screening module, configured to pre-select a first set of media content in a media library of the server based on the gender and age range characteristics as screening basis;
the marking module is used for marking the first media content correspondingly based on gender and age range to form a screening basis, and storing the screening basis in a feature library;
the association module is used for associating the screening basis with the first media content correspondingly, and updating the associated media content in the association table correspondingly;
the second judging module is used for judging the association table of the first media content;
the second screening module is used for carrying out secondary screening on the first media content set based on the association table to obtain a second media content set;
the priority setting module is used for setting each media content in the second media content set as a first priority; setting each of the remaining media content in the first media content set as a second priority, and setting a recommendation list containing the first media content set based on the first priority and the second priority;
the control module is used for inputting the recommendation list into the control module, the control module is used for obtaining display parameters of the display area, setting the display area to be a display window and a floating window based on the display parameters, the display window is used for displaying and obtaining the first media content, and the floating window is used for displaying the recommendation list and obtaining the second media content according to the recommendation list.
8. The artificial intelligence system based media content recommendation method system according to claim 7, wherein the processor is provided in the smart screen;
and a display program is arranged in the control module, and a main interface displayed on the intelligent screen main application screen is configured based on the display program.
9. The artificial intelligence system based media content recommendation method system of claim 7, wherein the processor further comprises:
the input module is connected to the control module through an input interface, and inputs a screen division strategy through the input module, and the screen division strategy is applied to a display program to divide the main interface into a plurality of display areas;
a configuration unit, configured to configure a distribution link for each display area;
the content media recommending module is used for recommending the media content to the corresponding display through the distributing link based on the selection or setting rule of the recommending list;
and the switching module is connected to the content media recommendation module and is used for switching between selection and setting rules based on the recommendation list.
10. The artificial intelligence system-based media content recommendation method system of claim 9, wherein the content media recommendation module has:
the task management module is used for acquiring a plurality of tasks to be displayed; the tasks to be displayed are correspondingly ordered according to the selection sequence;
the task management module is provided with a dispatching unit and a task execution unit, wherein the dispatching unit is used for dividing the sequenced tasks to be displayed into at least one group of queues, each group of queues comprises a plurality of tasks to be displayed, and the number of the tasks to be displayed is less than or equal to the number of distribution links;
the dispatching unit is connected with the task execution unit, and the task execution unit is used for distributing the tasks to be displayed to a plurality of display areas through the distribution links correspondingly for synchronous display.
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