CN112685599A - Video recommendation method and device - Google Patents
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Abstract
The method determines the type of a video to be played by a client, acquires the running state of the client if the video type belongs to a target type, and acquires at least one recommended type video according to the running state of the client, wherein the recommended type video belongs to the target type and is matched with the running state of the client. For example, the running state of the client comprises a foreground running state and a background running state, and if the client is in the foreground running state, the recommended type video matched with the foreground running state is obtained; and if the client is in the background running state, acquiring the recommended type video matched with the background running state. According to the scheme, the recommended video matched with the running state of the client can be recommended when the video is recommended to the user, so that the matching degree between the recommended video and the running state of the client is improved, and the accuracy of video recommendation is finally improved.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a video recommendation method and apparatus.
Background
With the popularization of mobile terminals and the speed increase of networks, short and fast mass flow transmission contents are gradually favored by platforms and broad users. The video content of the video platform includes a wide variety of content.
The current video playing method generally plays a video in the form of a video stream, and then automatically plays the next video in the video stream, but the video recommendation accuracy in the related art is low.
Disclosure of Invention
The present disclosure provides a video recommendation method and apparatus, so as to at least solve the problem of low accuracy of video recommendation results in the related art. The technical scheme of the disclosure is as follows:
according to a first aspect of the embodiments of the present disclosure, there is provided a video recommendation method, including:
determining the type of a video to be played by a client;
when the video type is determined to belong to the target type, acquiring the running state of the client;
and acquiring at least one recommended type video according to the running state of the client, wherein the at least one recommended type video belongs to the target type and is matched with the running state of the client.
In a possible implementation manner of the first aspect, the obtaining, according to the operation state of the client, at least one recommended type video includes:
when the client is determined to be in a foreground running state, at least one first recommendation type video is obtained, the at least one first recommendation type video accords with a foreground recommendation rule matched with the foreground running state, and the foreground recommendation rule at least comprises: the video pictures contain human faces.
In another possible implementation manner of the first aspect, the foreground recommendation rule further includes at least: the audio quality of the video is not lower than a first preset audio quality threshold.
In another possible implementation manner of the first aspect, the foreground recommendation rule further includes at least: and the user feedback quality score of the video is higher than a preset user feedback quality threshold value, and the user feedback quality score is obtained according to user behaviors generated when the user watches the video.
In yet another possible implementation manner of the first aspect, the obtaining at least one recommended type video according to the operation state of the client further includes:
when the client is determined to be in the background running state, at least one second recommendation type video is obtained, the at least one second recommendation type video conforms to a background recommendation rule matched with the background running state, and the background recommendation rule at least comprises: the audio quality of the video is greater than a second preset audio quality threshold, and the second preset audio quality threshold is greater than the first preset audio quality threshold.
In another possible implementation manner of the first aspect, the determining a type of a video to be played by the client includes:
and in response to detecting the selection operation of the user for selecting the video type to be played on the client, determining the video type corresponding to the selection operation as the video type to be played by the client.
In another possible implementation manner of the first aspect, the determining a type of a video to be played by the client includes:
and when the video types played by the client in the preset time period before the current moment belong to the same video type, determining the same video type as the video type to be played by the client.
According to a second aspect of the embodiments of the present disclosure, there is provided a video recommendation apparatus, the apparatus including:
the video type determining module is configured to determine the type of a video to be played by the client;
the running state acquisition module is configured to acquire the running state of the client when the video type is determined to belong to the target type;
and the recommended video acquisition module is configured to acquire at least one recommended type video according to the running state of the client, wherein the at least one recommended type video belongs to the target type and is matched with the running state of the client.
In a possible implementation manner of the second aspect, the recommendation video obtaining module includes:
a first obtaining sub-module, configured to, when it is determined that the client is in a foreground operating state, obtain at least one first recommended type video, where the at least one first recommended type video conforms to a foreground recommendation rule matched with the foreground operating state, and the foreground recommendation rule at least includes: the video pictures contain human faces.
In another possible implementation manner of the second aspect, the foreground recommendation rule further includes at least: the audio quality of the video is not lower than a first preset audio quality threshold.
In another possible implementation manner of the second aspect, the foreground recommendation rule further includes at least: and the user feedback quality score of the video is higher than a preset user feedback quality threshold value, and the user feedback quality score is obtained according to user behaviors generated when the user watches the video.
In yet another possible implementation manner of the second aspect, the recommendation video obtaining module further includes:
a second obtaining sub-module, configured to obtain at least one second recommended type video when it is determined that the client is in a background running state, where the at least one second recommended type video conforms to a background recommendation rule matched with the background running state, and the background recommendation rule at least includes: the audio quality of the video is greater than a second preset audio quality threshold, and the second preset audio quality threshold is greater than the first preset audio quality threshold.
In another possible implementation manner of the second aspect, the video type determining module includes:
the first determining submodule is configured to respond to the detection of a selection operation of a user for selecting a video type to be played on the client, and determine the video type corresponding to the selection operation as the video type to be played by the client.
In yet another possible implementation manner of the second aspect, the video type determining module includes:
the second determining submodule is configured to determine the same video type as the video type to be played by the client when the video type played by the client in the preset time period before the current time belongs to the same video type.
According to a third aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the video recommendation method according to any one of the possible implementation manners of the first aspect.
According to a fourth aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium having instructions stored thereon, where the instructions, when executed by a processor of an electronic device, enable the electronic device to perform the video recommendation method according to any one of the possible implementations of the first aspect.
According to a fifth aspect of the embodiments of the present disclosure, there is provided a computer program product, where instructions are stored, and when the instructions are executed by a processor in an electronic device, the video recommendation method according to any one of the possible implementation manners of the first aspect is implemented.
The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects: determining the type of a video to be played by a client, if the video type belongs to a target type, acquiring the running state of the client, and acquiring at least one recommended type video according to the running state of the client, wherein the recommended type video belongs to the target type and is matched with the running state of the client. For example, the running state of the client comprises a foreground running state and a background running state, and if the client is in the foreground running state, the recommended type video matched with the foreground running state is obtained; and if the client is in the background running state, acquiring the recommended type video matched with the background running state. According to the scheme, the recommended video matched with the running state of the client can be recommended when the video is recommended to the user, so that the matching degree between the recommended video and the running state of the client is improved, and the accuracy of video recommendation is finally improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure and are not to be construed as limiting the disclosure.
FIG. 1 is a flow diagram illustrating a video recommendation method in accordance with an exemplary embodiment;
FIG. 2 is a flow diagram illustrating another video recommendation method in accordance with an illustrative embodiment;
FIG. 3 is a flow diagram illustrating yet another video recommendation method in accordance with an illustrative embodiment;
FIG. 4 is a block diagram illustrating a video recommendation device in accordance with an exemplary embodiment;
FIG. 5 is a block diagram illustrating another video recommendation device in accordance with an exemplary embodiment;
FIG. 6 is a block diagram illustrating an electronic device according to an exemplary embodiment.
Detailed Description
In order to make the technical solutions of the present disclosure better understood by those of ordinary skill in the art, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
Fig. 1 is a flowchart illustrating a video recommendation method according to an exemplary embodiment, which is used in a client, as shown in fig. 1, and includes the following steps.
In S110, the video type to be played by the client is determined.
After the client starts and plays the video, determining the video type of the video to be played by the client, wherein the video type at least comprises a music type and the like. The video type to be played is the video type of the video to be played.
In an application scenario, a user selects a video type to be watched on a display interface of a client, and determines that the video type selected by the user is a video type to be played by the client.
In this application scenario, the process of determining the type of the video to be played by the client may include: and in response to detecting the selection operation of the user for selecting the video type to be played on the client, determining the video type corresponding to the selection operation as the video type to be played by the client.
In a possible implementation manner, a control matched with each video type is displayed on a display interface of the client, the selection operation for the user to select the video type to be played may be a touch operation for the user to touch a certain video type control, and the video type corresponding to the touched video type control is the video type selected by the user.
In another application scenario, the user does not select the video type to be watched, but the historical playing data of the user is analyzed to find that the video types watched by the user in the preset time period are the same video type.
In this application scenario, the process of determining the type of the video to be played by the client may include: and when the video types played by the client in the preset time period before the current moment belong to the same video type, determining the same video type as the video type to be played by the client.
In S120, when it is determined that the video type is the target type, the operating state of the client is acquired.
The running states of the client comprise a foreground running state and a background running state. In one embodiment of the present disclosure, a client may obtain running state information of the client from an operating system of a mobile terminal in which the client is installed. For example, an APP may obtain an operating state of the APP from a system of a mobile phone.
In a possible implementation manner, the operating system of the mobile terminal judges whether the client is in a foreground operating state or a background operating state by monitoring whether the screen is turned off or on; and if the screen is in the screen-off state, determining that the client is in the background running state. If the screen is bright, the running state of the client needs to be further monitored to judge whether the client is currently in foreground running or background running.
In S130, at least one recommended type video is obtained according to the operating state of the client.
And the at least one recommended type video belongs to a target type and is matched with the running state of the client.
In one embodiment, the client sends the running state of the client to the server so as to obtain the recommended type video matched with the running state from the server. For example, the client may actively send the running state of the client to the server, or the server sends a request for obtaining the running state to the client, and the client returns the running state to the server after receiving the request.
In an application scenario, the style and quality of videos uploaded to a server by users of video APPs are very different, for example, for music videos, some videos are sung with exposed faces, some videos are sung with unexposed faces, some videos are made with perfect homemade mvs (music videos), and some videos are simply and simply played. These stylistic differences result in viewers having different looks, some having a better look and feel and better listening to the audio in the foreground operating state, and some having a slightly poorer look and feel and better listening to the audio only.
Therefore, the embodiment of the present disclosure provides a push scheme capable of recommending different videos respectively for foreground operating states or background operating states of a client, and different recommendation rules are set respectively for different operating states, such as foreground recommendation rules and background recommendation rules; if the client is currently in a foreground running state, recommending a video matched with a foreground recommendation rule; and if the client is in the background running state currently, recommending the video matched with the background recommendation rule.
When the client is in the foreground running state, it is generally considered that the user is watching the video content played by the APP at the moment, and at the moment, a video with better picture quality, such as a video with a human face contained in a video picture, can be recommended to the user. When the client is in the background running state, videos suitable for background playing can be recommended to the user, for example, music videos are taken as an example, and videos suitable for background playing can be videos with lower picture quality and higher audio quality. The video with better picture quality can improve the watching rate of foreground users, and the video with higher audio quality can improve the watching rate of background users, so that the video recommendation method improves the accuracy of video recommendation.
The video recommendation method provided in this embodiment determines a video type to be played by a client, and if the video type belongs to a target type, obtains an operating state of the client, and obtains at least one recommendation type video according to the operating state of the client, where the recommendation type video belongs to the target type and is matched with the operating state of the client. For example, the running state of the client comprises a foreground running state and a background running state, and if the client is in the foreground running state, the recommended type video matched with the foreground running state is obtained; and if the client is in the background running state, acquiring the recommended type video matched with the background running state. According to the scheme, the recommended video matched with the running state of the client can be recommended when the video is recommended to the user, so that the matching degree between the recommended video and the running state of the client is improved, and the accuracy of video recommendation is finally improved.
Fig. 2 is a flowchart illustrating another video recommendation method according to an example embodiment, which includes the following steps, as shown in fig. 2.
In S210, the video type to be played by the client is determined.
In S220, when the video type is determined to be the target type, the running state of the client is obtained.
In S230, when it is determined that the client is in the foreground operating state, at least one first recommended type video is acquired.
The first recommendation type video belongs to a target type and accords with a target type of a foreground recommendation rule.
In one embodiment, the foreground recommendation rules include at least: the video pictures contain human faces.
Under the condition, when the video picture contains the human face, the video is determined to accord with the foreground recommendation rule.
By taking music videos as an example, videos sung by exposing faces (namely, videos containing face images in video pictures) or well-made MVs are more suitable for being played in the foreground, and such videos can improve the watching rate of users, namely, videos recommended to the users are more in line with the requirements of the users, namely, the accuracy of video recommendation is improved.
In another embodiment, the foreground recommendation rule includes: the video picture comprises a human face, and the audio quality is not lower than a first preset audio quality threshold.
Under the condition, when the video picture contains the human face, the video is preliminarily determined to be suitable for foreground playing, the audio quality of the video is further evaluated, and if the audio quality is not lower than a first preset audio quality threshold value, the video is finally determined to accord with the foreground recommendation rule.
Wherein, the audio quality represents the high or low degree of the audio content contained in the video. Taking music-like videos as an example, the audio content may be scored using a singing scoring model. A higher score indicates a higher audio quality and a lower score indicates a lower audio quality. In other embodiments, the audio quality may be represented by other parameters, for example, setting a level of audio quality, with a higher level representing higher audio quality and conversely, a lower level representing lower audio quality.
The first preset audio quality threshold may be set according to an actual application scenario, for example, the audio quality is represented by a score, and if the full score is 100 points, the first preset audio quality threshold may be set to 60 points. Of course, in other embodiments of the present disclosure, other scores may be set, and are not limited herein.
In yet another embodiment, the foreground recommendation rule further comprises: the user feedback quality score is higher than a preset user feedback quality threshold.
The user feedback quality score represents the degree of the video favored by the audience, if the higher the user feedback quality score is, the more favored the video is by the audience, otherwise, the lower the user feedback quality score is, the less favored the video is by the audience. The user feedback quality score is obtained according to user behavior generated when the user watches the video. The preset user feedback quality threshold value can be set according to actual application requirements.
In a possible implementation manner, various behavior data of the user in the process of watching the video, such as data of whether the user finishes watching the video, the number of praise watching the video, the number of comments watching the video, the number of concerns of the author of the video, and the like, may be counted to obtain the user feedback quality score of the video.
In a possible implementation manner, the video is played completely, the number of praise, the number of comments and the attention amount of the video author are positive feedback, namely, adding the subentry; if the video playing time length is less than a certain set time length (e.g. 5s), then it is used as negative feedback, i.e. decreasing item. And calculating to obtain the user feedback score according to all the adding items and the subtracting items obtained by statistics.
In one possible implementation manner, the foreground recommendation rule includes that the video picture contains a human face, and the user feedback quality score is higher than a preset user feedback quality threshold.
In the implementation mode, when the video picture contains the human face, the video is preliminarily determined to be suitable for foreground playing, the user feedback quality score corresponding to the video is further obtained, and if the user feedback quality score is higher than a preset user feedback quality threshold value, the video is determined to accord with the foreground recommendation rule.
In another possible implementation manner, the foreground recommendation rule includes: the video picture comprises a human face, the audio quality is not lower than a first preset audio quality threshold, and the user feedback quality score is higher than a preset user feedback quality threshold.
In the implementation mode, when the video picture contains the human face, the video is preliminarily determined to be suitable for foreground playing, the audio quality corresponding to the video is further obtained, if the audio quality is not lower than a first preset audio quality threshold value, the user feedback quality score of the video is further obtained, and if the user feedback quality score is higher than a preset user feedback quality threshold value, the video is finally determined to accord with the foreground recommendation rule.
In yet another embodiment, the foreground recommendation rule includes at least a picture quality greater than or equal to a preset picture quality threshold. If the video picture quality is not lower than a preset picture quality threshold value, determining that the video accords with a foreground recommendation rule; and if the video picture quality is lower than a preset picture quality threshold value, determining that the video accords with the background recommendation rule.
The preset picture quality threshold value can be freely set according to actual requirements. In addition, the picture quality can be evaluated from at least one dimension of whether the picture contains a human face, the picture definition and the picture richness, for example, if the picture contains a human face and is clear and rich, the picture quality of the video is high.
In S240, when it is determined that the client is in the background running state, at least one second recommended type video is acquired.
Wherein the at least one second recommendation type video complies with background recommendation rules.
When the client is in a background running state, the user is generally considered not to watch the video picture and only listens to the audio content; therefore, videos with higher audio quality can be recommended to the user at this time, so that the watching rate of the background user is improved.
In one possible implementation, the background recommendation rule at least includes: the audio quality of the video is greater than a second preset audio quality threshold, wherein the second preset audio quality threshold is greater than the first preset audio quality threshold.
In this implementation, no matter whether the video picture contains a human face or not, as long as the audio quality of the video is greater than the second preset audio quality threshold, it is determined that the video meets the background recommendation rule. For example, in the case of music videos, videos which include human faces but have a single screen and are more suitable for listening to audio, such as a simple personal singing video, are recommended to the user.
In another possible implementation manner, the background recommendation rule includes: the video image does not contain the human face, and the audio quality is greater than a second preset audio quality threshold value.
In the implementation mode, if the video picture does not contain the human face, the video is preliminarily determined to be suitable for background playing, the audio quality of the video is further determined, and if the audio quality is greater than a second preset audio quality threshold value, the video is determined to accord with the background recommendation rule. For example, music-like videos that do not expose the face but have a higher singing level.
In the video recommendation method provided by this embodiment, when the client plays the target type video, if the client is in the foreground operating state, at least one first recommendation type video that meets the foreground recommendation rule is recommended to the client. And if the client is in the background running state, recommending at least one second recommendation type video which accords with the background recommendation rule to the client. Therefore, videos matched with corresponding running states are recommended respectively according to different running states of the foreground and the background, and the accuracy of the recommendation result is improved finally.
Fig. 3 is a flowchart of another video recommendation method according to an exemplary embodiment, and this embodiment will focus on a process in which a server obtains videos matching different recommendation rules, as shown in fig. 2, where the method includes the following steps.
In S310, when the server receives the target type video uploaded by the client, it determines whether the video frame includes a human face; if so, go to S320; if not, S350 is performed.
In a possible implementation manner, a target type video uploaded by any client is firstly stored in a corresponding video queue in a server, and then the server reads the video from the video queue to evaluate the audio quality of the video, the feedback quality score of a user and other indexes.
When a user uses a client to publish a video (namely, the client sends the video to a server), the server stores the video sent by the client into a queue, and then reads the video from the queue to judge whether the video contains a human face.
In S320, the audio quality of the video and the user feedback quality score are determined.
The process of determining the audio quality and the user feedback quality score is referred to in the related content of S230, and will not be described herein.
In S330, the videos are stored into the first type video set, and the audio quality and the user feedback quality score corresponding to the videos are marked.
In one embodiment, when the video is stored in the first type video set, the audio quality and the user feedback quality score corresponding to the video are stored at the same time.
In S340, when the server determines that the client is in the foreground operating state, at least one video meeting the foreground recommendation rule is selected from the first class of video set and sent to the client.
In one embodiment, when a recommended video is selected from the first category of video sets, the selected audio quality is not lower than a first preset audio threshold, and the video with the user feedback quality score higher than the preset user feedback quality score is sent to the client.
In another embodiment, the preset number of videos can be directly selected to be sent to the client according to the sequence from high audio quality and user feedback quality scores to low audio quality and user feedback quality scores.
In S350, the audio quality of the video is determined, the video is stored into the second type video set, and the audio quality of the video is marked.
In one embodiment, when the video is stored in the second type video set, the corresponding audio quality of the video is stored at the same time.
In S360, when the server determines that the client is in the background running state, at least one video meeting the background recommendation rule is selected from the second type of video set and sent to the client.
In one embodiment, videos with audio quality higher than a second preset audio quality threshold are selected from the second type of video set and sent to the client.
Wherein the second preset audio quality threshold is greater than the first preset audio quality threshold. And if the video picture does not contain the human face, continuously determining the audio quality of the video. If the audio quality of the video is greater than the second preset audio quality threshold, the audio quality of the video is higher, and the video is more suitable for background playing.
In another embodiment, when the videos recommended to the user are selected from the second type video set, a preset number of videos are selected and sent to the client side according to the sequence of high audio quality to low audio quality.
According to the video recommendation method provided by the embodiment, when a user uploads a target type video to a server, the server firstly determines whether an uploaded video picture contains a human face and is roughly divided into two types; and further determining the audio quality of the video and the user feedback quality score aiming at the video containing the face in the video picture, and storing the video, the corresponding audio quality and the corresponding user feedback quality score into a first type video set. And if the client is in a foreground running state, selecting the video meeting the foreground recommendation rule from the first class of video set and sending the video to the client. And aiming at the video without the human face in the video picture, preliminarily determining that the video is suitable for background playing, further determining the audio quality of the video, and storing the video and the corresponding audio quality into a second type video set. And if the client is in the background running state, selecting the videos meeting the background recommendation rule from the second type of video set and sending the videos to the client. According to the scheme, the high-quality videos suitable for the running state can be recommended respectively for the users in the foreground running state and the background running state, and the accuracy of video recommendation results is improved. In addition, according to the scheme, when the user uploads the video, the indexes of the uploaded video in all evaluation dimensions are evaluated and recorded, so that the video can be recommended to the user subsequently and directly according to the recorded indexes, the response time of the server when the video is recommended is shortened, and the recommendation speed is increased.
Corresponding to the video recommendation method embodiment, the disclosure further provides a video recommendation device embodiment.
Fig. 4 is a block diagram illustrating a video recommendation apparatus applied to a client according to an exemplary embodiment, and as shown in fig. 4, the apparatus includes: a video type determination module 110, an operation state acquisition module 120 and a recommended video acquisition module 130.
A video type determining module 110 configured to determine a video type to be played by the client.
In one application scenario, the video type determination module 110 includes: the first determining submodule is configured to respond to the detection of a selection operation of a user for selecting a video type to be played on the client, and determine the video type corresponding to the selection operation as the video type to be played by the client.
In another application scenario, the video type determining module 110 includes: the second determining submodule is configured to determine the same video type as the video type to be played by the client when the video type played by the client in the preset time period before the current time belongs to the same video type.
A running state obtaining module 120 configured to obtain the running state of the client when it is determined that the video type belongs to the target type.
A recommended video obtaining module 130 configured to obtain at least one recommended type video according to the operating state of the client, where the at least one recommended type video belongs to the target type and matches with the operating state of the client.
In one embodiment, as shown in fig. 4, the recommendation video acquisition module 130 includes:
the first obtaining sub-module 131 is configured to, when it is determined that the client is in a foreground operating state, obtain at least one first recommended type video, where the at least one first recommended type video conforms to a foreground recommendation rule matched with the foreground operating state.
In one possible implementation, the foreground recommendation rule at least includes: the video pictures contain human faces.
In another possible implementation manner, the foreground recommendation rule further includes at least: the audio quality of the video is not lower than a first preset audio quality threshold.
In another possible implementation manner, the foreground recommendation rule further includes at least: and the user feedback quality score of the video is higher than a preset user feedback quality threshold value, and the user feedback quality score is obtained according to user behaviors generated when the user watches the video.
In another embodiment, as shown in fig. 5, the recommended video obtaining module 130 further includes:
the second obtaining sub-module 132 is configured to, when it is determined that the client is in the background running state, obtain at least one second recommended type video, where the at least one second recommended type video conforms to the background recommendation rule matching the background running state.
In one possible implementation, the background recommendation rule at least includes: the audio quality of the video is greater than a second preset audio quality threshold, and the second preset audio quality threshold is greater than the first preset audio quality threshold.
The video recommendation device provided in this embodiment determines a video type to be played by a client, and if the video type belongs to a target type, obtains an operation state of the client, and obtains at least one recommendation type video according to the operation state of the client, where the recommendation type video belongs to the target type and is matched with the operation state of the client. For example, the running state of the client comprises a foreground running state and a background running state, and if the client is in the foreground running state, the recommended type video matched with the foreground running state is obtained; and if the client is in the background running state, acquiring the recommended type video matched with the background running state. According to the scheme, the recommended video matched with the running state of the client can be recommended when the video is recommended to the user, so that the matching degree between the recommended video and the running state of the client is improved, and the accuracy of video recommendation is finally improved.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
Fig. 6 is a block diagram illustrating an electronic device 600, which may be, for example, a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, etc., in accordance with an exemplary embodiment.
Referring to fig. 6, electronic device 600 may include one or more of the following components: a processing component 602, a memory 604, a power component 606, a multimedia component 608, an audio component 610, an interface to input/output (I/O) 612, a sensor component 614, and a communication component 616.
The processing component 602 generally controls overall operation of the electronic device 600, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 602 may include one or more processors 620 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 602 can include one or more modules that facilitate interaction between the processing component 602 and other components. For example, the processing component 602 can include a multimedia module to facilitate interaction between the multimedia component 608 and the processing component 602.
The memory 604 is configured to store various types of data to support operations at the electronic device 600. Examples of such data include instructions for any application or method operating on the electronic device 600, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 604 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The multimedia component 608 includes a screen that provides an output interface between the electronic device 600 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 608 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 600 is in an operation mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 610 is configured to output and/or input audio signals. For example, audio component 610 includes a Microphone (MIC) configured to receive external audio signals when apparatus 600 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in the memory 604 or transmitted via the communication component 616. In some embodiments, audio component 610 further includes a speaker for outputting audio signals.
The I/O interface 612 provides an interface between the processing component 602 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor component 614 includes one or more sensors for providing status assessment of various aspects of the electronic device 600. For example, the sensor component 614 may detect an open/closed state of the electronic device 600, the relative positioning of components, such as a display and keypad of the electronic device 600, the sensor component 614 may also detect a change in the position of the electronic device 600 or a component of the electronic device 600, the presence or absence of user contact with the electronic device 600, orientation or acceleration/deceleration of the electronic device 600, and a change in the temperature of the electronic device 600. The sensor assembly 614 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 614 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 614 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 616 is configured to facilitate communications between the electronic device 600 and other devices in a wired or wireless manner. The electronic device 600 may access a wireless network based on a communication standard, such as WiFi, a carrier network (e.g., 3G, 4G, 5G, etc.), or a combination thereof. In an exemplary embodiment, the communication component 616 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 616 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device 600 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the video recommendation method described above.
In an exemplary embodiment, a computer-readable storage medium comprising instructions, such as storage 604 comprising instructions, executable by processor 620 of electronic device 600 to perform the video recommendation method described above is also provided. Alternatively, the computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
In an exemplary embodiment, there is also provided a computer program product having stored therein instructions that, when executed by a processor in an electronic device, implement any of the video recommendation methods described above.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A method for video recommendation, the method comprising:
determining the type of a video to be played by a client;
when the video type is determined to belong to the target type, acquiring the running state of the client;
and acquiring at least one recommended type video according to the running state of the client, wherein the at least one recommended type video belongs to the target type and is matched with the running state of the client.
2. The video recommendation method according to claim 1, wherein said obtaining at least one recommendation type video according to the operation status of the client comprises:
when the client is determined to be in a foreground running state, at least one first recommendation type video is obtained, the at least one first recommendation type video accords with a foreground recommendation rule matched with the foreground running state, and the foreground recommendation rule at least comprises: the video pictures contain human faces.
3. The video recommendation method of claim 2, wherein the foreground recommendation rule further comprises at least: the audio quality of the video is not lower than a first preset audio quality threshold.
4. The video recommendation method according to claim 2, wherein said foreground recommendation rule further comprises at least: and the user feedback quality score of the video is higher than a preset user feedback quality threshold value, and the user feedback quality score is obtained according to user behaviors generated when the user watches the video.
5. The video recommendation method according to claim 3, wherein said obtaining at least one recommendation type video according to the operating status of the client further comprises:
when the client is determined to be in the background running state, at least one second recommendation type video is obtained, the at least one second recommendation type video conforms to a background recommendation rule matched with the background running state, and the background recommendation rule at least comprises: the audio quality of the video is greater than a second preset audio quality threshold, and the second preset audio quality threshold is greater than the first preset audio quality threshold.
6. The video recommendation method according to claim 1, wherein said determining a video type to be played by the client comprises:
in response to detecting that a user selects a video playing type selection operation on the client, determining a video type corresponding to the selection operation as a video type to be played by the client;
or, the determining the type of the video to be played by the client includes:
and when the video types played by the client in the preset time period before the current moment belong to the same video type, determining the same video type as the video type to be played by the client.
7. A video recommendation apparatus, characterized in that the apparatus comprises:
the video type determining module is configured to determine the type of a video to be played by the client;
the running state acquisition module is configured to acquire the running state of the client when the video type is determined to belong to the target type;
and the recommended video acquisition module is configured to acquire at least one recommended type video according to the running state of the client, wherein the at least one recommended type video belongs to the target type and is matched with the running state of the client.
8. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the video recommendation method of any of claims 1 to 6.
9. A computer-readable storage medium having instructions stored thereon, wherein the instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the video recommendation method of any of claims 1-6.
10. A computer program product having stored therein instructions for implementing a video recommendation method according to any one of claims 1 to 6 when executed by a processor in an electronic device.
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