CN113271478B - Learning video recommendation method, information interaction method and device - Google Patents
Learning video recommendation method, information interaction method and device Download PDFInfo
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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
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/234—Processing of video elementary streams, e.g. splicing of video streams, manipulating MPEG-4 scene graphs
- H04N21/23418—Processing of video elementary streams, e.g. splicing of video streams, manipulating MPEG-4 scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics
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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
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/231—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion
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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
- H04N21/258—Client or end-user data management, e.g. managing client capabilities, user preferences or demographics, processing of multiple end-users preferences to derive collaborative data
- H04N21/25866—Management of end-user data
- H04N21/25891—Management of end-user data being end-user preferences
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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
- H04N21/266—Channel or content management, e.g. generation and management of keys and entitlement messages in a conditional access system, merging a VOD unicast channel into a multicast channel
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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]
- H04N21/40—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
- H04N21/431—Generation of visual interfaces for content selection or interaction; Content or additional data rendering
- H04N21/4312—Generation of visual interfaces for content selection or interaction; Content or additional data rendering involving specific graphical features, e.g. screen layout, special fonts or colors, blinking icons, highlights or animations
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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]
- H04N21/40—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
Abstract
The embodiment of the invention relates to a learning video recommendation method, an information interaction method and a device, wherein the learning video recommendation method of the embodiment of the invention obtains a highlight video file by processing a pre-recorded course recording video file, receives a teaching theme video file uploaded by a user side, and integrates richer video content; and the integrated video content is recommended to the user in the form of short video stream according to the acquired user information, so that the video watching efficiency is improved, and the social attribute of the learning video is increased. By the method, the enthusiasm of parents and children for making and sharing videos is improved, so that the parents can better monitor the learning effect of the children and plan subsequent learning plans.
Description
Technical Field
The invention relates to the field of online learning, in particular to a learning video recommendation method, an information interaction method and an information interaction device.
Background
Some learning videos uploaded by parents or children exist in online learning application, the parents and/or watching videos can sense the learning effect of the children, and the generated videos also have certain commemorative value. In the existing products, learning effect videos of children are generated through AI technologies and some theme activities such as dubbing, lecture, post-class theater and the like, and the learning videos are displayed in a list/squared figure form. However, the video watching rate of parents and children is not enough, and many parents do not watch the video of children, so that the learning effect of the children cannot be sensed; although a small number of parents watch the learning effect videos of the children, the learning effect videos of the children are not compared with the learning effect videos of other children, and the learning effect of the children is not evaluated well.
That is to say, the generation and sharing of past videos are single in presentation form and lack of social attributes, so that the enthusiasm of parents and children for making and sharing videos cannot be well mobilized.
Disclosure of Invention
In view of the above, the present invention provides an online learning video recommendation method, an information interaction method, and an online learning video recommendation device, which are used for integrating richer video content, improving video viewing efficiency, and increasing social attributes of a learning video, so as to improve enthusiasm of parents and children for making and sharing videos, and enable parents to better monitor learning effects of children and plan subsequent learning plans.
In a first aspect, an embodiment of the present invention provides a learning video recommendation method, where the learning video recommendation method includes: processing according to a pre-recorded course recording video file to obtain a highlight video file; receiving a teaching theme video file uploaded by a user side; acquiring user information, wherein the user information comprises user personal information, associated users of the users, user behavior data and user position information; and determining that the first short video stream is recommended to the user according to the highlight video file and the teaching subject video file according to the user information.
Further, the learning video recommendation method further includes: acquiring a recommendable video set from the highlight video file and the teaching subject video file, wherein the recommendable video set comprises the highlight video file and the teaching subject video file; determining a heat value of each video file in the recommendable video set; determining, based on the set of recommendable videos, that a second short video stream is recommended to the user according to the ranking of the heat value.
Further, the highlight video file and the teaching theme video file have modifiable public attributes, the default public attribute of the highlight video file is not public, and the default public attribute of the teaching theme video file is public; the step of obtaining a recommendable video set from the highlight video file and the teaching theme video file comprises: and acquiring a set of all teaching theme video files and highlight video files with the disclosure attributes set to be publicable as the recommendable video set.
Further, the learning video recommendation method further includes: and recommending the highlight video file and the teaching theme video file belonging to the user according to the time sequence.
Further, according to the user information, determining that the first short video stream is recommended to the user according to the highlight video file and the teaching theme video file comprises: according to a preset priority sequence, selecting the highlight video file and the teaching theme video file from the video file belonging to the user person, the video file related to the associated user and the video file corresponding to the user position, and determining the first short video stream to recommend in combination with the user behavior data, wherein the video file belonging to the user person is prior to the video file related to the associated user, and the video file related to the associated user is prior to the video file corresponding to the user position.
Further, the user behavior data includes: the user watching video type data, the user watching video attribution data and the user praise video attribution data.
Further, the associating the user includes: friend users, referral recommendation users and mobile phone address book friend users.
Further, the video files corresponding to the associated user of the user include video files attributed to the associated user and video files approved by the associated user; the recommendation priority of the video file belonging to the associated user is higher than the recommendation priority of the video file favored by the associated user.
Further, the learning video recommendation method further includes: determining attributions of the highlight video file and the teaching theme video file; allowing the user to forward the highlight video file and the instructional topic video file attributed to the user to a third party; not allowing the user to forward the highlight video file and the instructional subject video file not attributed to the user to a third party.
In a second aspect, an embodiment of the present invention further provides an information interaction method, where the method includes: displaying a teaching application user interface, wherein a video watching inlet is arranged on the user interface; responding to the received trigger of the video watching inlet, jumping to a video watching interface and establishing connection with a server; in response to switching to a first mode of a video viewing interface, receiving and displaying a first short video stream, wherein the first short video stream comprises the highlight video file and the teaching topic video file recommended according to user information.
Further, the information interaction method further includes: and receiving and displaying a second short video stream in response to switching to a second mode of the video viewing interface, wherein the second short video stream is determined according to the video files in the recommendable video set and sorted according to the popularity value.
Further, the information interaction method further includes: and in response to switching to a third mode of the video viewing interface, receiving and displaying a highlight video file and the teaching subject video file which belong to the user, wherein the recommendation sequence of the video files is determined according to the time sequence.
In a third aspect, an embodiment of the present invention further provides an electronic device for implementing the above method, including a memory and a processor, where the memory is used to store one or more computer program instructions, where the one or more computer program instructions are executed by the processor to implement the method in the first aspect or the second aspect.
Embodiments of the present invention also provide a computer-readable storage medium for implementing the above method, and storing computer program instructions, which when executed by a processor, implement the method of the first aspect or the second aspect.
According to the learning video recommendation method, the information interaction method and the device, the wonderful fragment video file is obtained through processing of the pre-recorded course recording video file, the teaching theme video file uploaded by the user side is received, and richer video contents are integrated; and the integrated video content is recommended to the user in the form of short video stream according to the acquired user information, so that the video watching efficiency is improved, and the social attribute of the learning video is increased. By the method, the enthusiasm of parents and children for making and sharing videos is improved, so that the parents can better monitor the learning effect of the children and plan subsequent learning plans.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent from the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:
FIG. 1 is a diagram of a hardware system architecture according to an embodiment of the present invention;
fig. 2 is a flowchart of a server and terminal interaction method according to an embodiment of the present invention;
FIG. 3 is a flowchart of a learning video recommendation method according to an embodiment of the present invention;
FIG. 4 is another flowchart of a learning video recommendation method according to an embodiment of the present invention;
FIG. 5 is a flowchart of an information interaction method according to an embodiment of the present invention;
FIG. 6 is a schematic view of a video viewing interface according to an embodiment of the present invention;
FIG. 7 is a second schematic diagram of a video viewing interface according to an embodiment of the invention;
fig. 8 is a schematic diagram of an electronic device according to an embodiment of the invention.
Detailed Description
The present invention will be described below based on examples, but the present invention is not limited to only these examples. In the following detailed description of the present invention, certain specific details are set forth. It will be apparent to one skilled in the art that the present invention may be practiced without these specific details. Well-known methods, procedures, components and circuits have not been described in detail so as not to obscure the present invention.
Furthermore, those of ordinary skill in the art will appreciate that the drawings provided herein are for illustrative purposes and are not necessarily drawn to scale.
Unless the context clearly requires otherwise, throughout the description, the words "comprise", "comprising", and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is, what is meant is "including, but not limited to".
In the description of the present invention, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present invention, "a plurality" means two or more unless otherwise specified.
Fig. 1 is a diagram of a hardware system architecture according to an embodiment of the present invention, and as shown in fig. 1, the hardware system architecture of the embodiment includes an image pickup apparatus 1, a terminal 2, and a server 3. The camera device 1 may be a single camera device, or may be a camera device installed on a terminal 2 such as a mobile phone or a computer, and is used for recording the state of a student during an online course. The terminal 2 is a terminal device such as a mobile phone, a computer, a tablet computer, and the like, and is used for executing terminal side operations, and a user can operate the terminal 2 to perform operations such as online lessons, creation and uploading of video files, and video watching. The server 3 may be an independent server, a server group, or a cloud server, and is configured to perform operations of acquiring a video file and user information, analyzing and processing the user information, sorting the video file according to the user information, uploading a short video stream to a network, and the like.
Specifically, the learning video recommendation method according to the embodiment of the present invention is implemented by the information interaction method shown in fig. 2, wherein the server end completes the actions shown in fig. 3 or fig. 4, and the terminal completes the actions shown in fig. 5.
Fig. 2 is a flowchart of a server and terminal interaction method according to an embodiment of the present invention. As shown in fig. 2, the information interaction process includes the following steps:
in step S21, the terminal records a course recording video file, creates a teaching theme video file, and obtains user information.
In step S22, the terminal uploads the recorded curriculum recording video file, the created teaching theme video file, and the acquired user information to the server.
After the server receives the above video file and the user information at step S23, the lesson recording video file is processed to obtain a highlight video clip file and the teaching theme video file are saved in the storage device. The storage may be a storage device of the server itself, or may be an independent storage device or a file server separately provided.
In step S24, the server processes the user information and analyzes the video file corresponding to the user information. .
In step S25, the server sorts the video files according to the user information to generate a first short video stream, and sends the first short video stream to the terminal.
In step S26, when the terminal enters the first mode of the video viewing interface in response to the user operation, the first short video stream can be received for viewing.
And the terminal automatically records the watching number and the like of the video file in the watching process. In step S27, the terminal feeds back the recorded viewing data to the server.
After the server receives the data fed back by the terminal, in step S28, the server analyzes and determines the heat value of the video according to the number of watched videos and the number of praise.
In step S29, the server sorts the videos by heat to generate a second short video stream and transmits the second short video stream to the terminal side.
Thus, in step S210, when the terminal enters the second mode of the video viewing interface in response to the user operation, the second short video stream will be received for viewing.
In some embodiments, after the step S23, the method further includes:
in step S211, the server analyzes the attribution and uploading time of the video files, and then sorts the video files attributed to a certain user in a time sequence to generate a video file list.
In step S212, the server transmits the video file list to the user terminal.
Thus, in step S213, when the terminal enters the third mode of the video viewing interface in response to the user operation, the video file list may be received.
Fig. 3 is a flowchart of a learning video recommendation method according to an embodiment of the present invention. The learning video recommendation method is executed on the server side and is used for forming a short video stream according to interaction with the terminal and sending the short video stream to the terminal. In a specific embodiment, as shown in fig. 3, the learning video recommendation method includes the following steps:
in step S31, a highlight video file is acquired. Wherein the highlight video clip file is obtained by processing according to a pre-recorded course recording video file.
In step S32, a teaching theme video file is received. Wherein, the teaching theme video file is recorded and uploaded by the terminal.
In step S33, user information is acquired, and the user information includes user personal information, associated users of the users, user behavior data, and user location information. The server obtains the user information and uses the information for further analysis.
In step S34, the user information is analyzed, and the video file belonging to the user and the video file related to the user associated with the user, and the video files related to other users in a certain area near the user are found out according to the user information, and are analyzed by combining the user behavior data.
In step S35, a first short video stream is generated, and the server sorts the highlight video file and the teaching theme video file according to the user information, and generates the first short video stream. The specific sorting mode is that the video files belonging to the user individuals are sorted in preference to the video files related to the associated users in preference to the video files related to the users in the nearby areas, and the sorting is carried out in combination with the user behavior data in each priority level.
The first short video stream is sent to the user terminal for recommendation to the user at step S36.
In the above steps, the course recording video file is a course video recorded by the system when the student learns the online live course, the course video is automatically recorded and uploaded to the network by the camera device 1 as shown in fig. 1, and then is transmitted to the background server 3 by the network, and is manually or automatically edited to become a highlight video file. The teaching theme video file is recorded and uploaded for the user, the teaching theme video file comprises themes such as a post-class theater, a dubbing, a speech and the like, and the user uploads the video to the network through the terminal 2 shown in fig. 1 after making the video, and then transmits the video to the background server 3 through the network. The two types of video files are stored together in the storage device of the background server 3 to be recommended to the user. After the server 3 acquires the user information, the video file in the storage device is recommended to the user in the form of the first short video stream.
In summary, in the embodiment, the highlight video file is obtained by processing the pre-recorded course recording video file, and the teaching theme video file uploaded by the user side is received, so that richer video content is integrated. The integrated video content is recommended to the user in a short video stream mode according to the acquired user information, the video watching efficiency is improved, and the user information comprises associated user information which comprises a friend relation chain, a referral recommendation relation, mobile phone address book information and the like, so that the video content related to the associated user can be recommended to the user, and the social attribute of the learning video is increased. Therefore, the enthusiasm of parents and children for making and sharing videos can be effectively improved through the method, so that the parents can better monitor the learning effect of the children and plan subsequent learning plans.
In a specific embodiment, determining, from the highlight video file and the instructional topic video file, that the first short video stream is recommended to the user based on the user information comprises: selecting a highlight video file and a teaching theme video file from video files belonging to a user person, video files related to a related user and video files corresponding to the user position according to a preset priority sequence, and determining a first short video stream to recommend according to user behavior data. The video file belonging to the user person has priority over the video file related to the associated user, and the video file related to the associated user has priority over the video file corresponding to the user position. Namely, the first short video stream is ordered in such a way that the video of the user is recommended first, then the video related to friends is recommended, and finally the video of people nearby is recommended. The video with the strongest watching intention of the user is preferentially recommended to the user, and the enthusiasm of the user for watching and making the video is increased.
In a particular embodiment, associating the user includes: friend users, referral recommendation users and mobile phone address book friend users. In some embodiments, the associated users may also be sorted and then prioritized. For example, users who are friends of each other have priority over one-way friend users, one-way friend users have priority over mobile phone address book friend users, and mobile phone address book friend users have priority over referral recommending users.
In a specific implementation manner, the video files corresponding to the associated user information of the user include video files attributed to the associated user and video files approved by the associated user. The recommendation priority of the video file attributed to the associated user is higher than the recommendation priority of the video file complied with by the associated user. Namely, the video of the friend is recommended firstly, and then the video complied with by the friend is recommended.
In an optional implementation manner, the user information further includes user behavior data, the server further analyzes the user behavior data when generating the first short video stream, and sorts video files in the same priority according to the user behavior data in the same priority, so that the first short video stream generated in this manner can preferentially recommend a video that the user may have the strongest viewing will to the user more accurately, and the positivity of the user in viewing and making the video is increased. Specifically, the user behavior data includes: the video type data watched by the user, the video attribution data watched by the user and the video attribution data praised by the user. The server obtains the types of videos frequently watched by the user, the home users of the videos frequently watched by the user and the videos of other users favored by the user, then obtains the videos which are possibly most intensely watched by the user through data analysis and weighting calculation, and then arranges the videos in the front in the same priority to recommend the user. For example, data shows that the video type that the user a watches most frequently is "highlight video", and the video files that the user a watches are the most video files belonging to the user B, and the video files that the user a likes are also the most video files belonging to the user B, then when the user B is the associated user of the user a, the server preferentially recommends the highlight video files belonging to the user B among the priorities of the video files belonging to the associated user. Fig. 4 is another flowchart of the learning video recommendation method according to the embodiment of the present invention, wherein steps S31 and S32 in fig. 3 constitute step S41 in fig. 4, and steps S33 and S34 constitute step S42. In an alternative embodiment, shown in fig. 4, steps S41, S42, S43, S44 are the same as steps S31-S36 described above. In addition, the learning video recommendation method further comprises the following steps:
in step S45, a video heat value is acquired and analyzed. The method comprises the steps of firstly obtaining video files from highlight video files and teaching theme video files to form a recommendable video set, meanwhile obtaining the praise number and the watching number of the video files in the recommendable video set, and then calculating the heat value of each video file according to the praise number and the watching number in a weighting mode.
In step S46, a second short video stream is generated. And the server sorts the video files in the recommendable video set according to the heat value to generate a second short video stream.
In step S47, the second short video stream is sent to the user terminal for recommendation to the user.
And then, the video heat value information in the second short video stream is fed back in real time, and step S35 is executed again to adjust the video sequence in the second short video stream in real time. In some embodiments, the video heat value information in the first short video stream is also fed back in real time, and step S35 is executed to perform real-time adjustment on the video sequence in the second short video stream. Specifically, the popularity value is determined by the popularity number and the watching number of the video, the popularity number and the watching number are calculated according to a certain weight, and then the video with the higher popularity value is preferentially recommended. For example: the praise count is 8, the view count is 1, i.e. 8 views correspond to 1 praise, and if a video views 15 praise 1,B and views 8 praise 2, B is arranged before a. And if the heat values of a plurality of videos are equal, sorting the videos with the equal heat values from new videos to old videos according to the time sequence and recommending the videos. Through the method, the video with higher content quality can be preferentially recommended to the user, so that parents can efficiently perceive the learning effect of children per se compared with other children.
In a specific embodiment, the highlight video file and the teaching theme video file have modifiable public attributes, the default public attribute of the highlight video file is not public, and the default public attribute of the teaching theme video file is public. The method for acquiring the recommendable video set from the highlight video file and the teaching theme video file comprises the following steps: and acquiring a set of all teaching subject video files and highlight video files with public attributes set as public as a recommendable video set. The wonderful section videos are recorded videos of students in the class and are not uploaded actively by the users, so that the videos are not publicized by default due to the requirement of privacy protection, and can be acquired into a recommendable video set and recommended to other users only after the videos are authorized to be publicized by the users. By the method, the privacy of the user can be better protected, and the situation that some video clips which the user does not want to disclose are recommended to others to watch and cause discontent of the user is avoided.
As shown in fig. 4, in an alternative embodiment, the learning video recommendation method further includes the following steps in addition to the above steps S41 to S47:
in step S48, the video file attribution and uploading time is analyzed. Step S48 is executed after step S31 for finding out a video file belonging to the user himself, and the time of upload to the server.
In step S49, a video file list is generated. And the server sorts the highlight video files and the teaching theme video files belonging to the user in sequence according to the uploading time sequence and generates a video file list.
In step S310, the information is transmitted to the user terminal. And the server sends the video file list to the user terminal to recommend the video file list to the user.
In the embodiment, the user can check the teaching theme video uploaded by the user and the highlight video generated by the server background according to the time sequence, so that the user can conveniently search and watch the video.
In some alternative embodiments, the first short video stream and the second short video stream are updated at a certain time. For example, videos published publicly on the day are updated daily, and then recommendations are sorted by the first short video stream; the hot videos of the week are updated weekly and then the recommendations are sorted by the second short video stream. This enables the video to remain updated, avoiding the user from brushing the same video each time.
In some optional embodiments, the learning video recommendation method further comprises: after determining the attribution of the highlight video file and the teaching subject video file in the step S48, the user is allowed to forward the highlight video file and the teaching subject video file belonging to the user himself to the third party, and the user is not allowed to forward the highlight video file and the teaching subject video file not belonging to the user himself to the third party. Specifically, fig. 6 is a schematic view of a video viewing interface according to an embodiment of the present invention, as shown in fig. 6, when a user views a video file belonging to the user on the video viewing interface, a praise button 4 and a forward button 5 appear on the video viewing interface, and the user can forward the video file belonging to the user to a third party by clicking the forward button 5. Fig. 7 is a second schematic diagram of a video viewing interface according to an embodiment of the present invention, as shown in fig. 7, when the user views a video file that is not owned by the user, the user cannot forward the video of the user to a third party only by the ok button 4 but not by the forward button 5 on the video viewing interface. Through this kind of mode, can realize the relative closed loop of information to effectual protection user's privacy avoids user's video to be revealed by other people under the condition of unwittingly.
Fig. 5 is a flowchart of an information interaction method according to an embodiment of the present invention, and as shown in fig. 5, an embodiment of the present invention further provides an information interaction method implemented according to the learning video recommendation method, including the following steps:
in step S51, the tutorial application is opened and the tutorial application user interface is displayed.
In step S52, the application program will automatically acquire and upload the user information after being authorized.
In step S53, an online lesson video is recorded. The user can take an online lesson in the application program, and the application program automatically records the online lesson.
In step S54, the curriculum recording video file is automatically uploaded to the server.
Further, in step S55, a subject video file is produced. The user can also make teaching theme video files in the application program.
Then, in step S56, the teaching theme video file is manually uploaded to the server. After the course recording video file and the teaching theme video file are uploaded to the server, a series of processing is carried out on the server side and finally the processing is transmitted back to the application program terminal for the user to watch.
The user interface is provided with a video watching inlet, and the application program can respond to the received trigger of the video watching inlet and jump to the video watching interface to establish connection with the server.
Thereafter, in step S57, in response to a user operation, switching to the first mode of the video viewing interface is performed.
In step S58, a first short video stream is received and displayed, wherein the first short video stream includes a highlight video file and a teaching theme video file recommended according to the user information.
In some optional embodiments, step S58 is followed by:
in step S59, the viewing count and the like of the video file in the first short video stream are uploaded. And the heat value of the video file is obtained through subsequent analysis.
When the user opens the teaching application program and enters the user interface, the online lesson or teaching theme video file can be made or the video can be watched. When a user carries out on-line class teaching, the teaching application program can automatically record a course recording video file through a camera device carried by the user terminal and upload the course recording video file to a server terminal; if the user makes the teaching theme video file, the user can manually upload the made video file to the server through the teaching application program. After receiving the course recording video file, the server carries out clipping processing on the course recording video file by background workers to obtain a wonderful video clip file, and the wonderful video clip file and a teaching theme video file manually uploaded by a user are stored in a storage together. When the user clicks the video viewing entrance, the user enters the video viewing interface. The server end establishes connection with the user terminal and transmits the video file to the user terminal in the form of short video stream. As shown in fig. 6 and 7, the user may enter the first mode by clicking the first mode entry 6, and after the user enters the first mode of the viewing interface, the server sorts the video files according to the obtained user information to generate a first short video stream, and then recommends the video to the user in the first short video stream.
As shown in fig. 5, in an alternative embodiment, the information interaction method further includes the following steps executed after the above steps S51 to S56:
in step S510, a switch is made to the second mode of the video viewing interface in response to a user operation.
In step S511, a second short video stream is received and displayed, where the second short video stream is determined according to video files sorted according to the popularity value in the recommendable video set.
After the step S511, a step S59 is further included, in which the watching number and the like of the video file are uploaded for subsequent analysis to obtain a heat value of the video file, so as to perform real-time adjustment according to the heat value on the video sequence of the second short video stream in the second mode.
As shown in fig. 6 and 7, the user can enter the second mode by clicking on the second mode entry 7. Before entering the second mode, the server acquires the watching number and the like of each video file in the recommendable video set from the terminal side, analyzes the watching number and the like, calculates the heat value of the video file according to a certain proportion through weighting, sorts the video files according to the heat value of the video files to generate a second short video stream, and recommends the video to the user through the second short video stream. In the process, the server can acquire the watching number and the like of each video file in real time, and therefore the sequencing of the second short video stream is adjusted in real time.
As shown in fig. 5, in an alternative embodiment, the information interaction method further includes the following steps executed after the above steps S51 to S56:
in step S512, a switch is made to the third mode of the video viewing interface in response to a user operation.
In step S513, the highlight video file and the teaching theme video file belonging to the user are received and displayed, and the video file recommendation order is determined in chronological order to form a video file list.
As shown in fig. 6 and 7, the user can enter the third mode by clicking on the third mode entry 8. In a third mode, the server sorts the videos belonging to the user himself one by one according to the sequence of time from new to old, then transmits the videos to the user terminal, and displays the videos one by one in the third mode.
Fig. 8 is a schematic diagram of an electronic device according to an embodiment of the invention. The electronic device shown in fig. 8 is a general-purpose data processing apparatus comprising a general-purpose computer hardware structure including at least a processor 801 and a memory 802. The processor 801 and the memory 802 are connected by a bus 803. The memory 802 is adapted to store instructions or programs executable by the processor 801. The processor 801 may be a stand-alone microprocessor or a collection of one or more microprocessors. Thus, the processor 801 implements the processing of data and the control of other devices by executing commands stored in the memory 802 to thereby execute the method flows of embodiments of the present invention as described above. The bus 803 connects the above components together, and also connects the above components to a display controller 804 and a display device and an input/output (I/O) device 805. Input/output (I/O) devices 805 may be a mouse, keyboard, modem, network interface, touch input device, motion sensing input device, printer, and other devices known in the art. Typically, input/output (I/O) devices 805 are connected to the system through an input/output (I/O) controller 806.
The memory 802 may store, among other things, software components such as an operating system, communication modules, interaction modules, and application programs. Each of the modules and applications described above corresponds to a set of executable program instructions that perform one or more functions and methods described in embodiments of the invention.
The flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention described above illustrate various aspects of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
Also, as will be appreciated by one skilled in the art, aspects of embodiments of the present invention may be embodied as a system, method or computer program product. Accordingly, various aspects of embodiments of the invention may take the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a "circuit," module "or" system. Further, aspects of the invention may take the form of: a computer program product embodied in one or more computer readable media having computer readable program code embodied thereon.
Any combination of one or more computer-readable media may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. 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 suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: 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 context of embodiments of the present invention, 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.
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 signal may take any of a variety of forms, including, but not limited to: electromagnetic, optical, or any suitable combination thereof. The computer readable signal medium may be any of the following computer readable media: is not a computer readable storage medium and may communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including: object oriented programming languages such as Java, smalltalk, C + +, PHP, python, and the like; and 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; executing in part on the user computer and in part on the remote computer; or entirely on a remote computer or server. In the latter scenario, 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 above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (13)
1. A learning video recommendation method is characterized by comprising the following steps:
processing according to a pre-recorded course recording video file to obtain a highlight video file;
receiving a teaching theme video file uploaded by a user side;
acquiring user information, wherein the user information comprises user personal information, associated users of the users, user behavior data and user position information; and
determining a first short video stream to recommend to a user according to the highlight video file and the teaching subject video file according to the user information;
wherein determining that a first short video stream is recommended to a user according to the highlight video file and the teaching topic video file according to the user information comprises:
the highlight video file and the instructional topic video file are ordered according to a predetermined priority order, and are ordered within each priority in combination with user behavior data to determine that a first short video stream is recommended to a user, the predetermined priority order being that a video file attributed to the user individual is prioritized over a video file associated with the user, a video file associated with the user is prioritized over a video file corresponding to the user location, and the highlight video file and the instructional topic video file include the video file attributed to the user individual, the video file associated with the user, and the video file corresponding to the user location.
2. The learning-video recommendation method according to claim 1, further comprising:
acquiring a recommendable video set from the highlight video file and the teaching subject video file, wherein the recommendable video set comprises the highlight video file and the teaching subject video file;
determining a heat value of each video file in the recommendable video set; determining a second short video stream to recommend to the user based on the set of recommendable videos according to the ranking of the heat value.
3. The learning video recommendation method according to claim 1 or 2, wherein the highlight video file and the teaching subject video file have modifiable public attributes, a default public attribute of the highlight video file is not publicable, and a default public attribute of the teaching subject video file is publicable;
the step of obtaining a recommendable video set from the highlight video file and the teaching theme video file comprises:
and acquiring a set of all teaching theme video files and highlight video files with the disclosure attributes set to be publicable as the recommendable video set.
4. The learning-video recommendation method according to claim 1, further comprising:
and determining a video file list to recommend the highlight video file and the teaching subject video file belonging to the user according to the time sequence.
5. The learning video recommendation method of claim 1, wherein the user behavior data comprises: the user watching video type data, the user watching video attribution data and the user praise video attribution data.
6. The learning video recommendation method of claim 1, wherein the associating the user comprises: friend users, referral recommendation users and mobile phone address book friend users.
7. The learning video recommendation method according to claim 1, wherein the video files corresponding to the associated user of the user include video files attributed to the associated user and video files praised by the associated user;
the recommendation priority of the video file belonging to the associated user is higher than the recommendation priority of the video file favored by the associated user.
8. The learning video recommendation method according to claim 1, 2 or 4, further comprising:
determining the affiliation of the highlight video file and the teaching theme video file;
allowing the user to forward the highlight video file and the instructional theme video file attributed to the user to a third party;
not allowing the user to forward the highlight video file and the instructional subject video file not attributed to the user to a third party.
9. An information interaction method, characterized in that the information interaction method comprises:
displaying a teaching application user interface, wherein a video watching inlet is arranged on the user interface;
responding to the received trigger of the video watching inlet, jumping to a video watching interface and establishing connection with a server;
receiving and displaying a first short video stream in response to switching to a first mode of a video viewing interface;
wherein the first short video stream is determined by:
the server sorts the highlight video file and the teaching theme video file according to a preset priority sequence, and sorts the highlight video file and the teaching theme video file in combination with user behavior data in each priority to determine that the first short video stream is recommended to the user, wherein the preset priority sequence is that the video file belonging to the user person is prioritized over the video file related to the associated user, and the video file related to the associated user is prioritized over the video file corresponding to the user position, and the highlight video file and the teaching theme video file comprise the video file belonging to the user person, the video file related to the associated user and the video file corresponding to the user position.
10. The information interaction method according to claim 9, further comprising:
and receiving and displaying a second short video stream in response to switching to a second mode of the video viewing interface, wherein the second short video stream is determined according to the video files in the recommendable video set and sorted according to the popularity value.
11. The information interaction method according to claim 10, further comprising:
and in response to switching to a third mode of the video viewing interface, receiving and displaying a highlight video file and the teaching subject video file which belong to the user, wherein the recommendation sequence of the video files is determined according to the time sequence.
12. An electronic device comprising a memory and a processor, wherein the memory is configured to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method of any of claims 1-11.
13. A computer readable storage medium storing computer program instructions, which when executed by a processor implement the method of any one of claims 1-11.
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