CN112135169B - Media content loading method, device, equipment and medium - Google Patents

Media content loading method, device, equipment and medium Download PDF

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Publication number
CN112135169B
CN112135169B CN202010987452.9A CN202010987452A CN112135169B CN 112135169 B CN112135169 B CN 112135169B CN 202010987452 A CN202010987452 A CN 202010987452A CN 112135169 B CN112135169 B CN 112135169B
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media content
target media
loading
viewing
amount
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CN112135169A (en
Inventor
张行功
许智敏
张颢丹
班怡璇
郭宗明
孟胜彬
李军林
王悦
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Peking University
Lemon Inc Cayman Island
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Peking University
Lemon Inc Cayman Island
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
    • H04N21/251—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
    • H04N21/44213—Monitoring of end-user related data
    • H04N21/44222—Analytics of user selections, e.g. selection of programs or purchase activity
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • H04N21/4662—Learning process for intelligent management, e.g. learning user preferences for recommending movies characterized by learning algorithms
    • H04N21/4665—Learning process for intelligent management, e.g. learning user preferences for recommending movies characterized by learning algorithms involving classification methods, e.g. Decision trees
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • H04N21/4667—Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • H04N21/4668—Learning process for intelligent management, e.g. learning user preferences for recommending movies for recommending content, e.g. movies

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  • Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Social Psychology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computing Systems (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Information Transfer Between Computers (AREA)

Abstract

The invention discloses a media content loading method, a device, equipment and a medium, comprising the following steps: acquiring historical viewing behavior information of a user and attribute information of each target media content, and determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information; determining the loading priority of each target media content according to the predicted watching amount of each target media content; and loading each target media content according to the loading priority. According to the method and the device, the target media content watching amount is predicted through the historical watching behavior information of the user and the attribute information of the target media content, the loading priority of each target media content is determined based on the predicted watching amount, the target media content is loaded with fixed byte number or fixed duration according to the priority sequence, the first frame time and the pause are reduced, and unnecessary bandwidth waste is reduced.

Description

Media content loading method, device, equipment and medium
Technical Field
The present disclosure relates to streaming media processing technologies, and in particular, to a method, an apparatus, a device, and a medium for loading media content.
Background
With the popularization of mobile networks and the development of streaming media technology, mobile end media application products become a main tool for entertainment in people's life. In a multimedia application, a user may switch to a next media content at any time during the process of watching the media content, which may cause a relatively long first frame time when the user watches the next media content, and cause an additional pause in case of insufficient network bandwidth.
Disclosure of Invention
The embodiment of the disclosure provides a media content loading method, a device, equipment and a medium, which are used for reducing the first frame time and pause and reducing unnecessary bandwidth waste.
In a first aspect, an embodiment of the present disclosure provides a media content loading method, including:
acquiring historical viewing behavior information of a user, wherein the historical viewing behavior information is used for indicating relevant information of behaviors made by the user when the user views media content in the past;
acquiring attribute information of each target media content, wherein the attribute information comprises the duration of each target media content;
according to the historical viewing behavior information and the attribute information, determining the predicted viewing amount of each target media content;
determining the loading priority of each target media content according to the predicted watching amount of each target media content;
and loading each target media content according to the loading priority.
In a second aspect, an embodiment of the present disclosure further provides a media content loading apparatus, where the apparatus includes:
the system comprises a historical watching behavior information acquisition module, a historical watching behavior information acquisition module and a media content display module, wherein the historical watching behavior information acquisition module is used for acquiring historical watching behavior information of a user, and the historical watching behavior information is used for indicating behavior related information made by the user when the user watches media content in the past;
the attribute information acquisition module is used for acquiring the attribute information of each target media content, and the attribute information comprises the duration of each target media content;
the predicted viewing amount determining module is used for determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information;
a loading priority determining module, configured to determine a loading priority of each target media content according to the predicted viewing amount of each target media content;
and the loading processing module is used for loading each target media content based on the loading priority.
In a third aspect, an embodiment of the present disclosure further provides an apparatus, including:
one or more processors;
a memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a media content loading method as in any one of the embodiments of the disclosure.
In a fourth aspect, this disclosed embodiment also provides a medium, where a computer program is stored, and when executed by a processor, the computer program implements the media content loading method according to any one of the disclosed embodiments.
The media content loading method, device, equipment and medium provided by the present disclosure include: acquiring historical viewing behavior information of a user and attribute information of each target media content, and determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information; determining the loading priority of each target media content according to the predicted watching amount of each target media content; and loading each target media content according to the loading priority. According to the method and the device, the target media content watching amount is predicted through the historical watching behavior information of the user and the attribute information of the target media content, the loading priority of each target media content is determined based on the predicted watching amount, the target media content is loaded with fixed byte number or fixed duration according to the priority sequence, the first frame time and the pause are reduced, and unnecessary bandwidth waste is reduced.
Drawings
The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale.
Fig. 1 is a flowchart of a media content loading method provided by an embodiment of the present disclosure;
FIG. 2 is a flowchart of another media content loading method provided by an embodiment of the present application;
FIG. 3 is a flow chart of media content loading provided by an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of a media content loading device according to an embodiment of the present disclosure;
fig. 5 is a block diagram of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more complete and thorough understanding of the present disclosure. It should be understood that the drawings and the embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
Fig. 1 is a flowchart of a media content loading method provided by an embodiment of the present disclosure, where the present embodiment is applicable to a case of preloading media content in streaming media, and the method may be executed by a media content loading apparatus, where the apparatus may be implemented by software and/or hardware. The media content loading means may be integrated in a terminal device, for example.
Alternatively, the terminal device in the embodiments of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (e.g., a car navigation terminal), and the like, and a fixed terminal such as a digital TV, a desktop computer, and the like.
Optionally, this embodiment is applied to a typical scenario, which is a feed media stream, that is, when a user watches a current media content, the feed media stream may be switched to a next media content by downslide or switched to a previous media content by upslide.
Optionally, the present embodiment is applied to another typical scenario in which a plurality of media contents are displayed in a window of a mobile phone, and a user can browse different media contents by sliding up and down and click to watch different media contents.
In this embodiment, the terminal device may have a media content playing application installed therein, and may play the media content by using the media content playing application. Illustratively, a media content loading device may be added to the media content playing application for executing the method of the present disclosure. The media content may be audio, video, pictures, text, or a combination of any two or more of the foregoing.
As shown in fig. 1, the media content loading method provided by this embodiment mainly includes steps S11, S12, S13, S14, and S15.
S11, obtaining historical watching behavior information of the user, wherein the historical watching behavior information is used for indicating relevant information of behaviors made by the user when the user watches media content in the past.
Wherein the historical viewing behavior information is used for indicating the behavior related information made by the user when the user views the media content in the past. For example, may include at least one of: the media content that the user watched in the past, the watching duration of each media content watched in the past, the like behavior information of each media content watched in the past, the comment behavior information of each media content watched in the past, and the like.
The target media content may be understood to include media content that the user is currently watching, a number of media content following the media content being watched, and media content that the user switches to after sliding down or up, etc. The method is characterized in that a user can switch to the next media content at any time in the process of watching the media content, and aims to solve the problems that when the user watches the next media content, the first frame time is long, and in addition, under the condition that the network bandwidth is insufficient, extra pause is caused. In order to solve the problems of long time of the first frame and pause, the target media content needs to be preloaded. The first frame time refers to a time difference from a starting moment of clicking to play the media content or automatically playing the media content to a first frame picture of the media content after the media content is switched to the fixed media content.
Specifically, the target media content may be a media content in a recommended media content list that is issued to the client in advance by the media server. Or the media content is delivered by the media server after the client sends the media content request to the media server. In the present embodiment, only the target media content is described, but not limited.
Further, the obtaining of the historical viewing behavior information of the user may be obtaining of historical viewing behavior information stored locally (for example, in a log) by the client, or obtaining of the historical viewing behavior information of the user from the media server. Furthermore, after the client updates the viewing behavior information of the user, the updated viewing behavior information is sent to a local storage and recording device, or is uploaded to a media server for storage and recording.
S12, obtaining attribute information of each target media content, wherein the attribute information comprises the duration of each target media content.
The attribute information of the target media content may include a duration of each target media content, and may further include at least one of an address of each target media content, a bit rate of the media content, a resolution of the media content, a coding type of the media content, and the like.
Further, the obtaining of the attribute information of each target media content may be obtaining the attribute information of the target media content carried in a recommended media content list issued to the client by the media server in advance, or requesting and obtaining the attribute information of each target media content from the media server.
And S13, determining the predicted watching amount of each target media content according to the historical watching behavior information and the attribute information.
The predicted viewing amount may be a size of the predicted user viewing the media content or a parameter indicating the size of the media content. The predicted viewing amount may be a predicted number of viewing bytes, for example, the predicted viewing amount is 2M. The predicted viewing amount may also be a predicted viewing duration, for example: the predicted viewing amount is 10 seconds. The predicted viewing amount may be expressed in other measurement manners, which is not limited in this application.
The predicted viewing amount of the target media content refers to the viewing amount of the loading target media content predicted based on the historical viewing behavior information and the attribute information of the target media content and based on a certain prediction mode.
Further, the historical viewing behavior information may include a historical viewing amount of each past viewed media content, where the historical viewing amount refers to a viewing amount of the media content that the user has viewed in the past, that is, a played amount of the media content that the user has viewed in the past. The historical viewing volume may be the number of bytes historically viewed, e.g., the historical viewing volume is 4M. The historical viewing volume may also be a historical viewing duration, such as: the historical viewing volume is 10 seconds. The historical viewing amount may also be expressed in other measurement manners, which are not limited in this application.
Alternatively, an average value of the historical viewing amounts of a plurality of past viewed media contents may be used as the predicted viewing amount of the target media content.
Alternatively, the predicted viewing volume of each target media content may be determined based on the historical viewing proportion and the attribute information. Wherein the historical viewing proportion is a ratio of the historical viewing amount to the total amount of the media content viewed in the past. Specifically, the product of the historical viewing proportion and the total amount of the target media content is used as the predicted viewing amount of the target media content.
Furthermore, other prediction methods can be adopted to determine the predicted viewing volume of each target media content, for example, methods such as linear regression, LSTM, and the like can be used to predict the viewing volume; the user and the video can be clustered, and the characteristics of the category are used for prediction; the viewing volumes of the N media contents may be directly output as the predicted viewing volumes without predicting the viewing volumes.
And S14, determining the loading priority of each target media content according to the predicted watching amount of each target media content.
The loading priority refers to an amount representing the precedence order of loading the preset loading amount of the plurality of target media in the media content list.
Further, the loading priority of each target media content is determined according to the predicted viewing amount of each target media content, which may be determined according to the numerical value of the predicted viewing amount of each target media content. For example: the larger the predicted viewing amount of the target media content is, the higher the loading priority of the target media content is; it may be that the smaller the predicted viewing amount of the target media content, the higher the loading priority of the target media content.
Further, according to the predicted viewing amount, the loading priority of each target media content is determined based on the Lyapunov function.
Among them, the Lyapunov function is a function for proving the stability of a dynamic system or an autonomous differential equation. If a function might prove the stability of the system or differential equation at some point of equilibrium, then the function of degree is called the Lyapunov function.
In this embodiment, after the predicted viewing amount of each target media content and the Lyapunov function are subjected to certain mathematical operation and logical inference, the loading priority of each target media content is determined.
Furthermore, the loading priority of each target media content can be determined according to the predicted viewing amount, the loaded total amount and the loaded non-viewing amount of each target media content.
In this embodiment, the loaded total amount may be understood as the total amount of the target media content that has been loaded, and the loaded unviewed amount may be understood as the amount of the target media content that has been loaded but not viewed by the user, i.e., the amount of the target media content that has been loaded but not played.
It should be noted that, in the case that the target media content is the media content currently being played, the loaded total amount is greater than the loaded unviewed amount. I.e., the total amount loaded equals the sum of the amount viewed by the user and the amount not viewed by the user. The target media content is the media content in the list of media content, but the media content is not played, the total amount loaded is equal to the amount loaded and not viewed.
Specifically, the loading priority of each target media content is determined through certain mathematical operations according to the predicted viewing amount, the loaded total amount and the loaded non-viewing amount of each target media content.
And S15, loading each target media content according to the loading priority.
In this embodiment, the loading process includes loading the target media content according to a preset load amount.
The preset loading amount may be a size of the target media content loading or a parameter characterizing the size of the media content loading. The preset load amount is set to be a preset number of load bytes, for example, the preset load amount is 2M. The preset loading amount may also be a preset loading duration, for example: the predicted viewing amount is 10 seconds, and the preset loading amount can be expressed in other measurement manners, which is not limited in the present application.
It should be noted that the larger the preset load, the better the theoretical performance of the present disclosure, but since each download in the actual network has extra overhead, the smaller the preset load, the larger the extra overhead. Thus, the preset load time period is typically set to 1-5 seconds when measured in terms of the preset load time period. In this embodiment, a preset loading time period is taken as an example for explanation.
Further, the loading processing of each target media content according to the loading priority includes: if the target media content with the priority smaller than the preset numerical value exists, the target media content with the priority smaller than the preset numerical value is suspended and loaded, and after the target media content is suspended for the preset time, the operation of determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information is executed again; and if the target media content with the priority greater than the preset numerical value exists, loading the target media content with the priority greater than the preset numerical value according to the sequence of the priority from high to low and the preset loading amount.
In this embodiment, if the priority is smaller than the preset value, it indicates that the loaded unviewed amount of the target media content corresponding to the priority can meet the viewing requirement of the user, that is, the playing is not paused, and at this time, the loading of the target media content may be paused. And determining the predicted viewing amount of each target media content and the priority of each target media content based on the historical viewing behavior information and the attribute information again after the pause for the preset time length.
The preset time length of the pause can be determined according to the preset loading amount. When the preset loading amount is the preset loading duration, the size of the preset duration may be set to any fixed value between 0 and the preset loading duration, or the time that the priority of the media content is greater than zero at the next time may be predicted, and the preset duration is set to this time. In this embodiment, a preset time period of 0.5 second is taken as an example for description.
If the priority is larger than the preset numerical value, the loaded unviewed amount of the target media content corresponding to the priority cannot meet the watching requirement of the user, and at the moment, the target media content is loaded according to the preset loading amount.
Furthermore, the target media contents with the priority levels larger than the preset numerical value are arranged according to the sequence from high to low, and then the target media contents with the priority levels larger than the preset numerical value are loaded in sequence according to the sequence from high to low.
Further, loading the target media content with the priority greater than the preset value according to the sequence of the priority from high to low and the preset loading amount, including: and parallelly loading the target media contents ranked at the top L, wherein L is an integer greater than or equal to 1.
And loading the preset load quantity to the first L target media contents in parallel according to the sequence from high priority to low priority of the target media contents with the priority greater than the preset numerical value. Wherein L is less than or equal to the total number of target media content.
Further, in the process that the user does not switch the media content, that is, the user views the current media content, the steps of S11-S15 may also be repeatedly executed for multiple times to perform the loading processing operation of the media content.
Further, the steps of executing S11-S15 may be performed periodically, and the decision is made once every fixed time, where the step of executing S11-S15 may be a multi-thread parallel decision.
The media content loading method, device, equipment and medium provided by the present disclosure include: acquiring historical viewing behavior information of a user and attribute information of each target media content, and determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information; determining the loading priority of each target media content according to the predicted watching amount of each target media content; and loading each target media content according to the loading priority. According to the method and the device, the target media content watching amount is predicted through the historical watching behavior information of the user and the attribute information of the target media content, the loading priority of each target media content is determined based on the predicted watching amount, the target media content is loaded with fixed byte number or fixed duration according to the priority sequence, the first frame time and the pause are reduced, and unnecessary bandwidth waste is reduced.
On the basis of the above embodiment, before obtaining the historical viewing behavior information of the user, the method further includes: after detecting that a user opens a client or switches media contents, acquiring a media content list recommended by a media server; and determining the media content in the media content list as the target media content.
In this embodiment, after the user opens the client, the client obtains the recommended media content list from the media server, and after obtaining the recommended media content list, the client performs the operations of determining the priority and performing the loading processing with the media content in the media content list as the target media content.
In this embodiment, if it is detected that the user switches the media content, the client re-acquires the recommended media content list from the media server, and after acquiring the recommended media content list, performs the operations of determining the priority and performing the loading processing with the media content in the media content list as the target media content.
Fig. 2 is a flowchart of another media content loading method according to an embodiment of the present application. As shown in fig. 2, another media content loading method provided by this embodiment mainly includes steps S21, S22, S23, S24, S25, and S26.
S21, obtaining historical watching behavior information of the user, wherein the historical watching behavior information is used for indicating relevant information of behaviors made by the user when the user watches the media content in the past.
S22, obtaining attribute information of each target media content, wherein the attribute information comprises the duration of each target media content.
And S23, determining the predicted watching amount of each target media content according to the historical watching behavior information and the attribute information.
And S24, aiming at each target media content, determining an expected viewing increment corresponding to the target media content based on the predicted viewing amount and the loaded total amount of the target media content.
In this embodiment, the loaded total amount may be understood as the total amount of the target media content that has been loaded, and the loaded unviewed amount may be understood as the amount of the target media content that has been loaded but not viewed by the user. The amount that the user is not viewing may also be understood as the amount that the target media content has been loaded but not played.
It should be noted that, in the case that the target media content is the media content currently being played, the loaded total amount is greater than the loaded unviewed amount. I.e. the total amount loaded equals the sum of the amount watched by the user and the amount not watched loaded. The target media content is the media content in the list of media content, but the media content is not played, the total amount loaded is equal to the amount loaded unviewed.
Specifically, the loading priority of each target media content is determined through certain mathematical operations according to the predicted viewing amount, the loaded total amount and the loaded non-viewing amount of each target media content.
Further, the difference between the loaded total amount and the predicted viewing amount may be directly used as the desired viewing increment.
Further, the expected viewing increment I corresponding to the target media content can be determined by the following formula n ，
I n ＝min{max{P n -A n ,0},p n }
Where n is the number of the target media content, p n Is a preset load amount, I, of a one-time load corresponding to the target media content n n Is the desired viewing increment, P, corresponding to the target media content n n Is the predicted viewing volume, A, corresponding to the target media content n n Is a target media content n pairsThe total amount should be loaded.
The above formula shows that if the difference between the total amount loaded and the predicted viewing amount is less than 0, it indicates that the target media content n does not need to be loaded during the loading process, and the viewing increment I is expected n Is 0.
If the difference between the total loaded amount and the predicted viewing amount is greater than 0, it indicates that the target media content n needs to be loaded in the process of this loading. It expects to view delta I n The difference value of the total loaded amount and the predicted viewing amount corresponds to the preset loading amount p of the target media content n n And (4) determining. If the difference value between the total loaded amount and the predicted viewing amount is less than the preset loading amount p of one loading corresponding to the target media content n n Then it is desired to view the delta I n Is the difference between the total amount loaded and the predicted viewing amount. If the difference value between the total loaded amount and the predicted viewing amount is larger than the preset loading amount p of one loading corresponding to the target media content n n Then expect to view delta I n Is a preset loading amount p of one time loading corresponding to the target media content n n . I.e. desired viewing increment I n Can not be larger than the preset loading amount p of one-time loading corresponding to the target media content n n 。
And S25, determining the priority of the target media content based on the expected viewing increment and the loaded unviewed amount.
In this embodiment, the priority of the target media content may be determined according to the relationship between the desired viewing delta and the loaded amount of non-viewed content.
Specifically, determining the priority of the target media content based on the desired viewing increment and the loaded unviewed amount includes:
the priority of the target media content is determined by the following formula,
Y n ＝λI n -w n Q n p n
wherein Y is n For the priority of the target media content n, λ is a parameter of the buffer size, w n Is the weight, Q, of the target media content n n Is in the target mediumLoaded unviewed volume of n, p n Is a preset load of the target media content n.
Further, determining a priority of the target media content based on the desired viewing delta and the loaded amount of unviewed content comprises: determining the time length required by loading based on the network loading rate and the preset loading time length and code rate corresponding to the target media content; determining a priority of the target media content based on the desired viewing delta, a length of time required to load, and the amount of loaded unviewed.
The time length required by loading is the time length required by loading the p-second target media content at the network loading rate. The time length required by loading can be determined according to the required loading time length p seconds, the network loading rate and the code rate of the target media content. In this embodiment, details of the specific method for determining the duration required for loading are not described, and all methods for determining the duration required for loading are within the scope of the present disclosure.
The network loading rate can be directly obtained through a network device of the terminal, and can also be determined through the data downloading speed of the client.
In this embodiment, the expected viewing increment is an expected viewing increase time length in terms of time length, and the loaded unviewed amount is a loaded unviewed time length in terms of time length.
Determining a priority of the target media content based on the desired viewing delta, the length of time required to load, and the amount of the loaded unviewed content, including: based on functions
Figure BDA0002689720130000141
And determining the loading priority of each target media content.
Wherein n is the number of the target media content, Y' n Is priority, I 'of the target media content n' n Is a desired viewing increase duration of the target media content n, λ is a parameter indicating a buffer size, w' n Is the weight, Q 'of the target media content n' n Is the loaded unviewed duration, p 'of the target media content n' n Is an objectPreset loading duration, T, of media content n n Is the time required for loading.
Desired viewing increase duration I 'of the target media content n' n Reference may be made to the method for determining the desired viewing increment in the foregoing embodiment, and details in this embodiment are not repeated.
And S26, loading each target media content according to the loading priority.
After calculating the priority of each target media content, if the priority of the target media content is less than 0, suspending downloading the target media content, and after waiting for a preset time length, recalculating the priority; otherwise, selecting the media content with the highest priority and downloading for p seconds.
In addition, the loading priority determining method can determine n media content lists and their priority lists, and give the download duration of the n media contents. Wherein, the download duration can also be converted into download bytes.
On the basis of the above embodiments, the embodiments of the present disclosure further optimize the method for determining the predicted viewing amount.
In one embodiment, the historical viewing behavior information includes a historical viewing amount or a historical viewing proportion of the user to historically viewed media content when viewing the media content in the past. The determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information includes: determining a plurality of historical viewing media contents which have been viewed by a user within a preset past time period; determining an average of the historical viewing amounts of the plurality of historical viewing media content or determining an average of the historical viewing proportions of the plurality of historical viewing media content; and determining the predicted viewing amount of each target media content according to the average value of the historical viewing amount or the average value of the historical viewing proportion.
In the embodiment, a plurality of historical viewing media contents which are watched by a user in a preset past time period are determined; and determining the average value of the historical watching time lengths of the plurality of historical watching media contents, and determining the predicted watching time length of each target media content according to the average value of the historical watching time lengths.
The plurality of historical viewing media contents viewed by the user in the past time period can be extracted from the historical viewing behavior information of the user, the total time length for the user to view the plurality of historical viewing media contents is extracted from the historical viewing behavior information, the ratio of the total time length for viewing the plurality of historical viewing media contents to the number of the historical viewing media contents is determined as the average value of the historical viewing time lengths of the plurality of historical viewing media contents, and the average value of the historical viewing time lengths is determined as the predicted viewing time length of each target media content.
For example: the user watches the historical watching media content A, the historical watching media content B, the historical watching media content C and the historical watching media content D in the past time period, and the watching time lengths are T1, T2, T3 and T4 respectively. And determining the ratio of the sum of T1, T2, T3 and T4 to the number 4 of the media contents watched historically as the average value of the historical watching time length. The predicted viewing time of each target media content is an average value of the historical viewing time.
In the embodiment, a plurality of historical viewing media contents watched by a user in a preset past time period are determined; determining an average of the historical viewing proportions of the plurality of historical viewing media content; and determining the predicted watching time length of each target media content according to the average value of the historical watching proportions.
The method comprises the steps of extracting a plurality of historical viewing media contents viewed by a user in past time periods from historical viewing behavior information of the user, extracting viewing time of the user for viewing the plurality of historical viewing media contents from the historical viewing behavior information, obtaining total content time of each historical viewing media content, determining the ratio of the viewing time of the historical viewing media content to the total content time of the historical viewing media content as a historical viewing proportion aiming at each historical viewing media content, and calculating the average value of the historical viewing proportion determined by the historical viewing proportion of the plurality of historical viewing media contents.
On the basis of the foregoing embodiment, the historical viewing behavior information may further include: at least one of praise behavior information, comment behavior information, content category information and content address information when the user watches the historical watching media content in the past; and/or the attribute information further comprises at least one of address, category, code rate, resolution and coding type of each target media content; the determining the predicted viewing duration of each target media content according to the historical viewing behavior information and the attribute information further comprises: determining the predicted viewing duration of the respective target media content based on at least one of the above information.
On the basis of determining the predicted viewing time length according to the historical viewing amount or the historical viewing proportion, at least one of praise behavior information, comment behavior information, content category information and content address information of the user who views the historical viewing media content in the past can be further used; and/or the attribute information further comprises at least one of address, category, code rate, resolution and coding type of each target media content to determine the predicted watching duration.
Further, other prediction methods may be adopted to determine the predicted viewing amount of each target media content, for example, methods such as linear regression, LSTM, etc. may be used to perform viewing amount prediction; the users and videos can also be clustered, and the characteristics of the categories can be used for prediction.
Furthermore, the praise behavior information and comment behavior information of the user who watches the media content in the past can indicate that the user has a high degree of love or attention to the media content. The predicted viewing duration of the category of media content may be increased.
Furthermore, the time length required for loading the video with higher code rate or higher resolution ratio is longer, and the predicted watching time length of the media content of the category can also be increased.
Thus, the predicted watching time length can be adjusted according to the user's preference degree or the attribute information of the media content.
On the basis of the foregoing embodiments, the present embodiment provides an application example of a media content loading method, and fig. 3 is a flowchart for loading media content according to the embodiment of the present disclosure.
As shown in fig. 3, the media content loading process starts after the user opens the client. First, a client obtains a list of recommended media content. After the media content list is obtained, the predicted viewing time length of the media content in the media content list is predicted. And determining whether each media content is loaded, loading priority and loading duration according to the predicted watching duration and the current buffer area information, and delivering the loaded media content to a client loading data module for loading. If the user closes the client, the media content loading process stops running; if the user does not switch the media content, predicting, deciding and loading again; and if the user switches the media content, the recommended media content list is obtained again, and prediction, decision and loading are carried out. The present disclosure may also perform decision making periodically, once every fixed time, wherein the decision making may be a multi-threaded parallel decision.
Fig. 4 is a schematic structural diagram of a media content loading apparatus according to an embodiment of the present disclosure, where the embodiment is applicable to a case of preloading media content in streaming media, and the media content loading apparatus may be implemented in a software and/or hardware manner. The media content loading means may for example be integrated in the client.
As shown in fig. 4, the media content loading apparatus provided in this embodiment mainly includes a historical viewing behavior information obtaining module 41, an attribute information obtaining module 42, a predicted viewing duration determining module 43, a loading priority determining module 44, and a loading processing module 45.
The historical viewing behavior information acquiring module 41 is configured to acquire historical viewing behavior information of a user, where the historical viewing behavior information is used to indicate information about behaviors that the user made when viewing media content in the past;
an attribute information obtaining module 42, configured to obtain attribute information of each target media content, where the attribute information includes a duration of each target media content;
a predicted viewing duration determining module 43, configured to determine, according to the historical viewing behavior information and the attribute information, a predicted viewing amount of each target media content;
a loading priority determining module 44, configured to determine a loading priority of each target media content according to the predicted viewing amount of each target media content;
and a loading processing module 45, configured to perform loading processing on each target media content based on the loading priority.
The media content loading device acquires historical watching behavior information of a user and attribute information of each target media content, and determines the predicted watching amount of each target media content according to the historical watching behavior information and the attribute information; determining the loading priority of each target media content according to the predicted watching amount of each target media content; and loading each target media content according to the loading priority. According to the method and the device, the viewing amount of the target media content is predicted through the historical viewing behavior information of the user and the attribute information of the target media content, the loading priority of each target media content is determined based on the predicted viewing amount, the target media content is loaded with fixed byte number or fixed duration according to the priority sequence, and the first frame time and the pause are reduced.
In an embodiment, the loading priority determining module 44 is specifically configured to determine the loading priority of each target media content according to the predicted viewing amount based on a Lyapunov function.
In one embodiment, the load processing module 45 includes:
a pause loading unit, configured to, if there is a target media content with a priority smaller than a preset value, pause loading the target media content with the priority smaller than the preset value, and after a preset time is paused, re-execute an operation of determining a predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information;
and the loading unit is used for loading the target media contents with the priority levels larger than the preset numerical value according to the sequence from high priority levels to low priority levels and the preset loading amount if the target media contents with the priority levels larger than the preset numerical value exist.
In an embodiment, the loading unit is specifically configured to load, in parallel, the target media content ranked at top L, where L is an integer greater than or equal to 1.
In an embodiment, the loading priority determining module 44 is specifically configured to determine the loading priority of each target media content according to the predicted viewing amount, the loaded total amount and the loaded non-viewing amount of each target media content
In one embodiment, the load priority determination module 44 includes;
the expected viewing increment determining unit is used for determining an expected viewing increment corresponding to each target media content based on the predicted viewing amount and the loaded total amount of the target media content;
a priority determining unit for determining a priority of the target media content based on the desired viewing delta and the loaded amount of not viewed.
In an embodiment, the expected viewing increment determining unit is specifically configured to determine an expected viewing increment I corresponding to the target media content according to the following formula n ，
I n ＝min{max{P n -A n ,0},p n }
Where n is the number of the target media content, p n Is a preset load amount, I, of a one-time load corresponding to the target media content n n Is the desired viewing increment, P, corresponding to the target media content n n Is the predicted viewing amount, A, corresponding to the target media content n n Is the loaded total amount corresponding to the target media content n.
In an embodiment, the priority determining unit is specifically configured to determine the priority of the target media content by the following formula,
Y n ＝λI n -w n Q n p n
wherein, Y n For the priority of the target media content n, λ is a parameter of the buffer size,w n is the weight, Q, of the target media content n n Is the loaded unviewed amount, p, of the target media content n n Is a preset load amount of the target media content n.
In an embodiment, the priority determining unit is specifically configured to determine, based on a network loading rate, a duration required for loading according to a preset loading duration and a code rate corresponding to the target media content;
determining a priority of the target media content based on the desired viewing delta, a length of time required to load and the amount of loaded unviewed.
In one embodiment, the desired viewing increment is a desired viewing increase duration in duration, the loaded unviewed amount is a loaded unviewed duration in duration,
determining a priority of the target media content based on the desired viewing delta, the length of time required to load, and the amount of the loaded unviewed content, including:
based on functions
Figure BDA0002689720130000211
Determining a loading priority for the respective target media content, where n is a number, Y 'of the target media content' n Is priority, I 'of the target media content n' n Is a desired viewing increase time duration of the target media content n, λ is a parameter, w ', indicative of a buffer size' n Is the weight, Q 'of the target media content n' n Is the loaded unviewed duration, p 'of the target media content n' n Is a preset loading duration, T, of the target media content n n Is the time required for loading.
In one embodiment, the historical viewing behavior information includes a historical viewing amount or a historical viewing proportion of the user to the historical viewing media content when viewing the media content in the past.
In one embodiment, the predicted viewing duration determining module 43 is specifically configured to determine a plurality of historical viewing media contents that have been viewed by the user within a preset past time period; determining an average of the historical viewing amounts of the plurality of historical viewing media content or determining an average of the historical viewing proportions of the plurality of historical viewing media content; and determining the predicted viewing amount of each target media content according to the average value of the historical viewing amount or the average value of the historical viewing proportion.
In one embodiment, the historical viewing behavior information further includes at least one of praise behavior information, comment behavior information, content category information, and content address information of the user who viewed the historical viewing media content in the past; and/or the attribute information further comprises at least one of address, category, code rate, resolution and coding type of each target media content.
In one embodiment, the predicted viewing time length determining module 43 is further specifically configured to determine the predicted viewing time length of each target media content based on at least one of the above information.
In one embodiment, the apparatus further comprises:
the media content list acquisition module is used for acquiring a media content list recommended by the media server after detecting that the user opens the client or switches media content;
and the target media content determining module is used for determining the media content in the media content list as the target media content.
The device can execute the method provided by any embodiment of the disclosure, and has the corresponding functional modules and beneficial effects of the execution method.
Referring now to fig. 5, a block diagram of an electronic device (e.g., a terminal device) 500 suitable for use in implementing embodiments of the present disclosure is shown. The terminal device in the embodiments of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (e.g., a car navigation terminal), and the like, and a stationary terminal such as a digital TV, a desktop computer, and the like. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 5, electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be loaded and installed from a network via the communication means 509, or from the storage means 508, or from the ROM 502. The computer program, when executed by the processing device 501, performs the above-described functions defined in the methods of the embodiments of the present disclosure.
It should be noted that the computer readable medium of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, 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), an optical fiber, 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. In contrast, in the present disclosure, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring historical viewing behavior information of a user, wherein the historical viewing behavior information is used for indicating relevant information of behaviors made by the user when the user views media content in the past; acquiring attribute information of each target media content, wherein the attribute information comprises the duration of each target media content; according to the historical viewing behavior information and the attribute information, determining the predicted viewing amount of each target media content; determining the loading priority of each target media content according to the predicted watching amount of each target media content; and loading each target media content according to the loading priority.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, smalltalk, C + +, including conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, 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 and/or flowchart illustration, and combinations of blocks in the block diagrams and/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.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. The name of a unit does not in some cases form a limitation on the unit itself, and for example, the receiving module may also be described as "a unit for receiving a mail to be sent".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems on a chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, 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), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
acquiring historical viewing behavior information of a user, wherein the historical viewing behavior information is used for indicating relevant information of behaviors made by the user when the user views media content in the past;
acquiring attribute information of each target media content, wherein the attribute information comprises the duration of each target media content;
according to the historical viewing behavior information and the attribute information, determining the predicted viewing amount of each target media content;
determining the loading priority of each target media content according to the predicted watching amount of each target media content;
and loading each target media content according to the loading priority.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
and determining the loading priority of each target media content based on a Lyapunov function according to the predicted watching quantity.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
if the target media content with the priority smaller than the preset numerical value exists, pausing and loading the target media content with the priority smaller than the preset numerical value, and after pausing for a preset time, re-executing the operation of determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information;
and if the target media content with the priority greater than the preset numerical value exists, loading the target media content with the priority greater than the preset numerical value according to the sequence from high priority to low priority and the preset loading amount.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
and parallelly loading the target media contents ranked at the top L, wherein L is an integer greater than or equal to 1.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
and determining the loading priority of each target media content according to the predicted viewing amount, the loaded total amount and the loaded non-viewing amount of each target media content.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
for each target media content, determining a desired viewing increment corresponding to the target media content based on the predicted viewing amount and the loaded total amount of the target media content;
determining a priority of the target media content based on the desired viewing delta and the loaded unviewed amount.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
determining a desired viewing increment I corresponding to the target media content by the following formula n ，
I n ＝min{max{P n -A n ,0},p n }
Where n is the number of the target media content, p n Is a preset load amount, I, of a load corresponding to the target media content n n Is a desired viewing increment, P, corresponding to the target media content n n Is the predicted viewing volume, A, corresponding to the target media content n n Is the loaded total amount corresponding to the target media content n.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
the priority of the target media content is determined by the following formula,
Y n ＝λI n -w n Q n p n
wherein, Y n For the priority of the target media content n, λ is a parameter of the buffer size, w n Is the weight, Q, of the target media content n n Is the loaded unviewed amount, p, of the target media content n n Is a preset load of the target media content n.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
determining the time length required by loading based on the network loading rate and the preset loading time length and code rate corresponding to the target media content;
determining a priority of the target media content based on the desired viewing delta, a length of time required to load and the amount of loaded unviewed.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
the desired viewing increment is a desired viewing increase duration in terms of a duration, the loaded unviewed amount is a loaded unviewed duration in terms of a duration,
determining a priority of the target media content based on the desired viewing delta, the time required to load, and the amount of loaded unviewed content, comprising:
based on functions
Figure BDA0002689720130000291
Determining a loading priority for the respective target media content,
wherein n is the number of the target media content, Y' n Is priority, l 'of the target media content n' n Is a desired viewing increase time duration of said target media content n, λ isParameter indicating buffer size, w' n Is the weight, Q 'of the target media content n' n Is the loaded unviewed duration, p 'of the target media content n' n Is a preset loading duration, T, of the target media content n n Is the time required for loading.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
the historical viewing behavior information includes a historical viewing amount or a historical viewing proportion of the user to the historical viewing media content when viewing the media content in the past.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
determining a plurality of historical viewing media contents which have been viewed by a user within a preset past time period;
determining an average of the historical viewing amounts of the plurality of historical viewing media content or determining an average of the historical viewing proportions of the plurality of historical viewing media content;
and determining the predicted viewing amount of each target media content according to the average value of the historical viewing amount or the average value of the historical viewing proportion.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
the historical viewing behavior information also comprises at least one of praise behavior information, comment behavior information, content category information and content address information of the user when viewing the historical viewing media content in the past; and/or the attribute information further comprises at least one of address, category, code rate, resolution and coding type of each target media content;
the determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information further comprises:
determining the predicted viewing amount of the respective target media content based on at least one of the above information.
According to one or more embodiments of the present disclosure, there is provided a media content loading method/apparatus/device/medium, including:
after detecting that a user opens a client or switches media contents, acquiring a media content list recommended by a media server;
and determining the media content in the media content list as the target media content.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other embodiments in which any combination of the features described above or their equivalents does not depart from the spirit of the disclosure. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims (16)

1. A method for loading media content, comprising:
acquiring historical viewing behavior information of a user, wherein the historical viewing behavior information is used for indicating relevant information of behaviors performed by the user when the user views media content in the past;
acquiring attribute information of each target media content, wherein the attribute information comprises the duration of each target media content;
according to the historical viewing behavior information and the attribute information, determining the predicted viewing amount of each target media content;
determining the loading priority of each target media content according to the predicted watching amount of each target media content; the loading priority represents the sequence of loading preset loading amounts of the target media contents;
loading each target media content according to the loading priority;
wherein, the loading processing of each target media content according to the loading priority comprises:
if the target media content with the priority smaller than the preset numerical value exists, the target media content with the priority smaller than the preset numerical value is suspended and loaded, and after the target media content is suspended for the preset time, the operation of determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information is executed again;
and if the target media content with the priority greater than the preset numerical value exists, loading the target media content with the priority greater than the preset numerical value according to the sequence of the priority from high to low and the preset loading amount.
2. The method of claim 1, wherein determining the loading priority of each target media content according to the predicted viewing amount of each target media content comprises:
and determining the loading priority of each target media content based on a Lyapunov function according to the predicted viewing amount.
3. The method of claim 1, wherein loading the target media contents with priorities higher than the preset value according to the priority order from high to low and the preset loading amount comprises:
and parallelly loading the target media contents ranked at the top L, wherein L is an integer greater than or equal to 1.
4. The method of claim 1 or 2, wherein determining the loading priority of each target media content according to the predicted viewing amount of each target media content comprises:
and determining the loading priority of each target media content according to the predicted viewing amount, the loaded total amount and the loaded non-viewing amount of each target media content.
5. The method of claim 4, wherein determining the loading priority of each target media content according to the predicted viewing volume, the loaded total volume and the loaded non-viewing volume of each target media content comprises:
for each target media content, determining a desired viewing increment corresponding to the target media content based on the predicted viewing amount and the loaded total amount of the target media content;
determining a priority of the target media content based on the desired viewing delta and the loaded amount of unviewed.
6. The method of claim 5, wherein determining the desired viewing increment corresponding to the target media content based on the predicted viewing amount and the loaded total amount corresponding to the target media content comprises:
determining a desired viewing increment I corresponding to the target media content by the following formula n ，
I n ＝min{max{P n -A n ,0},p n }
Where n is the number of the target media content, p n Is a preset load amount, I, of a one-time load corresponding to the target media content n n Is the desired viewing increment, P, corresponding to the target media content n n Is the predicted viewing volume, A, corresponding to the target media content n n Is the loaded total amount corresponding to the target media content n.
7. The method of claim 6, wherein determining the priority of the target media content based on the desired viewing delta and the loaded unviewed amount comprises:
the priority of the target media content is determined by the following formula,
Y n ＝λI n -w n Q n p n
wherein, Y n For the priority of the target media content n, λ is a parameter of the buffer size, w n Is the weight, Q, of the target media content n n Is the loaded unviewed amount, p, of the target media content n n Is a preset load of the target media content n.
8. The method of claim 5, wherein determining the priority of the target media content based on the desired viewing delta and the loaded amount of unviewed comprises:
determining the time length required by loading based on the network loading rate and the preset loading time length and code rate corresponding to the target media content;
determining a priority of the target media content based on the desired viewing delta, a length of time required to load and the amount of loaded unviewed.
9. The method of claim 8, wherein the desired viewing increment is a desired viewing increase duration in duration, wherein the loaded unviewed amount is a loaded unviewed duration in duration,
determining a priority of the target media content based on the desired viewing delta, the time required to load, and the amount of loaded unviewed content, comprising:
based on functions
Figure FDA0003845142210000031
Determining a loading priority for the respective target media content,
wherein n is the number of the target media content, Y' n Is priority, l 'of the target media content n' n Is a desired viewing increase time duration of the target media content n, λ is a parameter, w ', indicative of a buffer size' n Is weight, Q 'of target media content n' n Is the loaded unviewed duration, p 'of the target media content n' n Is a preset loading duration, T, of the target media content n n Is the length of time required for loading.
10. The method according to any one of claims 1 to 3 and 5 to 9, wherein the historical viewing behavior information includes a historical viewing amount or a historical viewing proportion of the user to the historical viewing media content when viewing the media content in the past.
11. The method of claim 10, wherein determining the predicted viewing volume of the respective target media content according to the historical viewing behavior information and the attribute information comprises:
determining a plurality of historical viewing media contents which have been viewed by a user within a preset past time period;
determining an average of the historical viewing amounts of the plurality of historical viewing media content or determining an average of the historical viewing proportions of the plurality of historical viewing media content;
and determining the predicted viewing amount of each target media content according to the average value of the historical viewing amount or the average value of the historical viewing proportion.
12. The method according to claim 10, wherein the historical viewing behavior information further comprises at least one of praise behavior information, comment behavior information, content category information, and content address information of the user who viewed the historical viewing media content in the past; and/or the attribute information further comprises at least one of address, category, code rate, resolution and coding type of each target media content;
the determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information further comprises:
determining the predicted viewing amount of the respective target media content based on at least one of the above information.
13. The method of claim 1, further comprising, prior to obtaining the historical viewing behavior information of the user:
after detecting that a user opens a client or switches media contents, acquiring a media content list recommended by a media server;
and determining the media content in the media content list as the target media content.
14. An apparatus for loading media content, the apparatus comprising:
the system comprises a historical watching behavior information acquisition module, a historical watching behavior information acquisition module and a media content display module, wherein the historical watching behavior information acquisition module is used for acquiring historical watching behavior information of a user, and the historical watching behavior information is used for indicating behavior related information made by the user when the user watches media content in the past;
the attribute information acquisition module is used for acquiring the attribute information of each target media content, and the attribute information comprises the duration of each target media content;
the predicted viewing amount determining module is used for determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information;
a loading priority determining module, configured to determine a loading priority of each target media content according to the predicted viewing amount of each target media content; the loading priority represents the sequence of loading preset loading amounts of the plurality of target media contents;
the loading processing module is used for loading each target media content based on the loading priority;
wherein, the loading processing module comprises:
the pause loading unit is used for pausing and loading the target media content with the priority less than the preset value if the target media content with the priority less than the preset value exists, and re-executing the operation of determining the predicted viewing amount of each target media content according to the historical viewing behavior information and the attribute information after pausing for the preset time;
and the loading unit is used for loading the target media contents with the priority levels larger than the preset numerical value according to the sequence from high priority levels to low priority levels and the preset loading amount if the target media contents with the priority levels larger than the preset numerical value exist.
15. An electronic device, comprising:
one or more processors;
a memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a media content loading method as recited in any of claims 1-13.
16. A storage medium, characterized in that the medium stores a computer program which, when executed by a processor, implements a media content loading method according to any one of claims 1-13.
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