CN116910303B - Dance video recommendation method and device based on dance room learning stage - Google Patents
Dance video recommendation method and device based on dance room learning stage Download PDFInfo
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Abstract
The application discloses a dance video recommending method and device based on a dance room learning stage, wherein the method comprises the following steps: dividing learning dance videos in a dance room into a plurality of learning stages according to learning behaviors of learning dance through dance videos by students; the dance room is used for learning dance movements and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior; acquiring interactive data of a learner for learning a current dance video in each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn to set categories; obtaining a similar video list corresponding to the current dance video in each learning stage; obtaining learning preference interestingness of each learning stage according to the interaction data; obtaining recommended learning stages according to the learning preference interestingness of each learning stage; and obtaining target recommended dance videos according to the similar video list corresponding to the recommended learning stage.
Description
Technical Field
The present application relates to the field of computers and the internet technologies, and in particular, to a dance video recommendation method and apparatus, an electronic device, and a computer readable storage medium based on a dance room learning stage.
Background
With the development of internet technology, it is becoming more convenient for people to learn a wide variety of knowledge by watching video. For example, a user may learn a dance of interest by watching dance teaching video.
At present, historical data of the corresponding relation between the user and the video is utilized to analyze which videos are favorite videos of the user so as to recommend the favorite videos of the user to the user. However, the video which is analyzed according to the historical data and liked by the user is biased to the video with high click rate, and the interest requirement of the user in the learning process is ignored, so that the recommended dance teaching video is inaccurate, and personalized recommendation is not realized aiming at the interest of the user.
Disclosure of Invention
Object of the application
The application aims to provide a dance video recommendation method, device, electronic equipment and computer-readable storage medium based on a dance room learning stage.
(II) technical scheme
The embodiment of the application provides a dance video recommending method based on a dance room learning stage, which comprises the following steps: dividing learning dance videos in a dance room into a plurality of learning stages according to learning behaviors of learning dance through dance videos by students; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior; acquiring interactive data of a learner for learning a current dance video in each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories; obtaining a similar video list corresponding to the current dance video in each learning stage; obtaining learning preference interestingness of each learning stage according to the interaction data; obtaining recommended learning stages according to the learning preference interestingness of each learning stage; and obtaining target recommended dance videos according to the similar video list corresponding to the recommended learning stage.
Further, the obtaining the interactive data of the current dance video learned by the learner at each learning stage includes: acquiring the exposure times of the current dance video; acquiring the clicking times of clicking the current dance video by a student; obtaining learning behavior scores of students in each learning stage; wherein the learning behavior score is obtained by scoring the learning behavior of the learner at each learning stage.
Further, the learning phase includes at least one of: a stage of watching segmented video, a stage of playing video in depth, a stage of training with jump, a stage of uploading dance video and a stage of learning dance knowledge.
Further, the obtaining the similar video list corresponding to the current dance video in each learning stage includes: according to the learning behaviors of a learner in each learning stage, a plurality of first dance videos with the same learning behaviors of all users are obtained, and the similarity between the current dance video and the plurality of first dance videos is calculated by adopting a cosine similarity formula; and sequencing and screening the first dance videos according to the similarity to obtain a similar video list.
Further, the obtaining the learning preference interestingness of each learning stage according to the interaction data includes: and obtaining the learning preference interestingness of each learning stage according to the exposure times of the current dance video and the learning behavior score of each learning stage.
Further, the learning stage of obtaining the recommendation according to the learning preference interestingness of each learning stage includes: comparing the learning preference interestingness of each learning stage, screening out the maximum value of the learning preference interestingness in all learning stages, and obtaining a recommended learning stage; or taking the exposure times of the current dance video and the learning behavior score of each learning stage as a first parameter and a second parameter of the beta distribution respectively, sampling according to the beta distribution, and obtaining a recommended learning stage according to a sampling result.
The embodiment of the application provides another dance video recommending method based on a dance room learning stage, which comprises the following steps: dividing learning dance videos in a dance room into a plurality of learning stages according to learning behaviors of learning dance through dance videos by students; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior; acquiring interactive data of a learner for learning a current dance video in each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories; obtaining learning preference interestingness of each learning stage according to the interaction data; obtaining recommended learning stages according to the learning preference interestingness of each learning stage; screening one or more second dance videos according to the first dance videos corresponding to the recommended learning stage; the first dance video is a dance video which a learner has learned; the second dance video is dance video of which at least a part of students are learned; and sequencing the second dance videos according to the reverse sequence of the time when the dance videos enter the dance room, and obtaining target recommended dance videos.
The embodiment of the application provides a dance video recommending device based on a dance room learning stage, which comprises the following components: the dividing module is used for dividing the learning dance video in the dance room into a plurality of learning stages according to learning behaviors of learning dance by a learner through the dance video; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior; the first acquisition module is used for acquiring interactive data of a learner for learning the current dance video in each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories; the second acquisition module is used for acquiring a similar video list corresponding to the current dance video in each learning stage; the interest degree module is used for obtaining learning preference interest degree of each learning stage according to the interaction data; the first recommendation module is used for obtaining recommended learning stages according to the learning preference interestingness of each learning stage; and the second recommendation module is used for obtaining target recommended dance videos according to the similar video list corresponding to the recommended learning stage.
The embodiment of the application provides another dance video recommending device based on a dance room learning stage, which comprises the following components: the dividing module is used for dividing the learning dance video in the dance room into a plurality of learning stages according to learning behaviors of learning dance by a learner through the dance video; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior; the first acquisition module is used for acquiring interactive data of a learner for learning the current dance video in each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories; the interest degree module is used for obtaining learning preference interest degree of each learning stage according to the interaction data; the first recommendation module is used for obtaining recommended learning stages according to the learning preference interestingness of each learning stage; the screening module is used for screening one or more second dance videos according to the first dance videos corresponding to the recommended learning stage; the first dance video is a dance video which a learner has learned; the second dance video is dance video of which at least a part of students are learned; and the second recommending module is used for sequencing the second dance videos according to the reverse order of the time when the dance videos enter the dance room, so as to obtain target recommended dance videos.
An embodiment of the present application provides an electronic device including a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements the steps of the method as described above.
Embodiments of the present application provide a computer readable storage medium having stored thereon computer program instructions which when executed by a processor perform the steps of the method as described above.
Embodiments of the present application provide a computer program product comprising computer program instructions which, when executed by a processor, implement the steps of the method as described above.
(III) beneficial effects
The technical scheme of the application has the following beneficial technical effects:
1. in the embodiment of the application, aiming at all current dance videos learned by a certain learner, the learner possibly has different learning phases when learning each current dance video, correspondingly has different learning behaviors, searches similar videos learned by other students and the same learning phase with the learner and the current dance videos, calculates learning preference interestingness of the learner to the different learning phases to determine a recommended learning phase, and determines a final recommended dance video and an accompanying text according to the similar videos learned by the other students and the recommended learning phase when the learner is in the recommended learning phase, so that each learner can learn different dances across different dance rooms and realize recommendation diversification; therefore, according to learning behaviors of interest of a learner, a recommended learning stage is obtained, and then according to the recommended learning stage, a target recommended dance video is obtained, so that the recommended dance teaching video is more accurate, and personalized recommendation aiming at the interests of a user can be realized.
2. According to the embodiment of the application, aiming at all current dance videos learned by a certain student, the student possibly has different learning phases when learning each current dance video, correspondingly has different learning behaviors, the recommended learning phase is determined by calculating the learning preference interestingness of the student in the different learning phases, and the final recommended dance video and the accompanying text are determined according to the dance videos which the student has learned but not completed all learning in the recommended learning phase, so that each student can learn a plurality of interesting dances in a dance room; therefore, according to learning behaviors of interest of a learner, a recommended learning stage is obtained, and then according to the recommended learning stage, a target recommended dance video is obtained, so that the recommended dance teaching video is more accurate, and personalized recommendation aiming at the interests of a user can be realized.
Drawings
In order to more clearly describe the technical solution of the embodiments of the present application, the following description briefly describes the drawings in the embodiments of the present application.
FIG. 1 is a schematic diagram of a system architecture according to an embodiment of the present application.
Fig. 2 is a flowchart of a dance video recommendation method based on a dance room learning stage according to an embodiment of the application.
FIG. 3 is a block flow diagram of another dance video recommendation method based on dance room learning phase according to an embodiment of the present application.
Fig. 4 is a block diagram of a dance video recommendation device based on a dance room learning stage according to an embodiment of the application.
FIG. 5 is a block diagram of another dance video recommendation device based on a dance room learning stage according to an embodiment of the present application.
FIG. 6 is a schematic diagram of an electronic device for implementing a dance video recommendation method based on a dance room learning phase according to an embodiment of the present application.
Detailed Description
The principles and spirit of the present application will be described below with reference to several exemplary embodiments. It will be appreciated that such embodiments are provided to make the principles and spirit of the application clear and thorough, and enabling those skilled in the art to better understand and practice the principles and spirit of the application. The exemplary embodiments provided herein are merely some, but not all embodiments of the application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the embodiments herein, are within the scope of the present application.
Embodiments of the present application relate to a terminal device and/or a server. Those skilled in the art will appreciate that embodiments of the application may be implemented as a system, apparatus, device, method, computer readable storage medium, or computer program product. Accordingly, the present disclosure may be embodied in at least one of the following forms: complete hardware, complete software, or a combination of hardware and software. According to the embodiment of the application, the application discloses a dance video recommending method, a dance video recommending device, electronic equipment, a computer-readable storage medium and a computer program product based on a dance room learning stage. Fig. 1 shows a schematic diagram of a system architecture according to an embodiment of the application. As shown in fig. 1, the system includes a terminal device 102 and a server 104. Wherein the terminal device 102 may comprise at least one of: smart phones, tablet computers, notebook computers, desktop computers, smart televisions, various wearable devices, augmented reality AR devices, virtual reality VR devices, and the like. The terminal device 102 may be provided with a client, for example, the client may be a client that specifically performs a specific function (such as an app), or a client embedded with multiple kinds of applets (different functions), or may be a client that logs in through a browser. The user may operate on the terminal device 102, for example, the user may open a client installed on the terminal device 102 and input an instruction through a client operation, or the user may open a browser installed on the terminal device 102 and input an instruction through a browser operation. After the terminal device 102 receives the instruction input by the user, request information including the instruction is transmitted to the server 104. The server 104 performs a corresponding process after receiving the request information, and then returns the process result information to the terminal device 102. User instructions are completed through a series of data processing and information interaction.
In this document, terms such as first, second, third, etc. are used solely to distinguish one entity (or action) from another entity (or action) without necessarily requiring or implying any order or relationship between such entities (or actions).
Fig. 2 is a schematic flow chart of a dance video recommendation method based on a dance room learning stage according to an embodiment of the application, the method includes the following specific steps:
s101: dividing learning dance videos in a dance room into a plurality of learning stages according to learning behaviors of learning dance through dance videos by students; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly contains a learning behavior.
In the embodiment of the application, a plurality of students with the same or similar interests are aggregated in a newly created dance room, so that the students can conveniently learn the dance movements and the dance knowledge in a certain type of dance video on line, and the dance types can be divided according to classical dance, folk dance, ballet, modern dance and the like, can be divided according to finer types, and can set dance types according to a certain specific style; the learning phase can be divided into, for example, the following five phases: (1) a stage of watching segmented video, (2) a stage of playing video in depth, (3) a stage of exercising with jump, (4) a stage of uploading dance video and (5) a stage of learning dance knowledge; the learning phases can be realized by correspondingly creating functional modules in the dance room. In addition, correspondingly, the learning behavior of the learner in the stage of watching the segmented video is embodied as watching the segmented video; the learning behavior of the learner at the stage of playing the video in depth is embodied as playing the video in depth; the learning behavior of the learner in the heel-jump training stage is embodied as heel-jump training; the learning behavior of the learner in the stage of uploading the dance video is reflected in uploading the dance; the learning behavior of the learner in the stage of learning dance knowledge is embodied as learning dance knowledge; by dividing each learning stage from shallow to deep, the learning device meets the interest requirement of students in the process of learning a dance, and can also meet the requirement of more students in different learning stages for co-learning in the dance room.
S102: acquiring interactive data of a learner for learning a current dance video in each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories.
In the embodiment of the application, some latest popular current dance videos can be pushed to the terminal equipment 102 of the student through the server 104 at irregular intervals, so that the student can learn conveniently; when the current dance video is put in, one or more dance videos can be put in aiming at each learning stage, and different learning stage texts can be attached, so that a learner can click to learn or not click on the current dance video; thus, the available interaction data may for example comprise one or several of the following: exposure times, clicking times, and accumulated points for the learner to click on the current dance video for learning to obtain learning behavior scores, etc.
S103: and obtaining a similar video list corresponding to the current dance video in each learning stage.
According to the embodiment of the application, according to the fact that a certain student may be in different learning stages when learning each current dance video, the student has different learning behaviors correspondingly, and similar videos of the current dance video, which are learned by other students when the student is in the same learning stage, are searched, so that a corresponding similar video list can be formed in each learning stage, and the similar video lists can be ordered according to the magnitude of similarity values.
S104: and obtaining the learning preference interestingness of each learning stage according to the interaction data.
According to the embodiment of the application, the learning preference interestingness of each learning stage is calculated according to the interactive data of the learner in different learning stages, and the interactive data are used for evaluating and considering the learning behaviors of the learner, so that the learning preference interestingness can accurately reflect the interests of the learner.
S105: and obtaining recommended learning stages according to the learning preference interestingness of each learning stage.
In the embodiment of the application, the learning stage with the largest calculated value in the learning preference interestingness of each learning stage is used as the recommended learning stage, so that the recommended learning stage can be obtained according to the learning behavior interested by the learner. Some students may prefer to watch dance videos, while some may prefer to upload dance videos, with learning behaviors of interest being different for each student.
S106: and obtaining target recommended dance videos according to the similar video list corresponding to the recommended learning stage. According to the recommended learning stage, the dance video with the maximum similarity is screened out from the similar video list corresponding to the learning stage to serve as the target recommended dance video, so that the problem that the recommended video is inaccurate due to the fact that learning behaviors of students are ignored in the prior art is solved.
In the embodiment of the application, aiming at all current dance videos learned by a certain learner, the learner possibly has different learning phases when learning each current dance video, correspondingly has different learning behaviors, searches similar videos learned by other students and the same learning phase with the learner and the current dance videos, calculates learning preference interestingness of the learner to the different learning phases to determine a recommended learning phase, and determines a final recommended dance video and an accompanying text according to the similar videos learned by the other students and the recommended learning phase when the learner is in the recommended learning phase, so that each learner can learn different dances across different dance rooms and realize recommendation diversification; therefore, according to learning behaviors of interest of a learner, a recommended learning stage is obtained, and then according to the recommended learning stage, a target recommended dance video is obtained, so that the recommended dance teaching video is more accurate, and personalized recommendation aiming at the interests of a user can be realized.
In some embodiments, step S102, the obtaining the interactive data of the current dance video learned by the learner at each learning stage includes:
s1021: acquiring the exposure times of the current dance video;
S1022: acquiring the clicking times of clicking the current dance video by a student;
s1023: obtaining learning behavior scores of students in each learning stage; wherein the learning behavior score is obtained by scoring the learning behavior of the learner at each learning stage. The learner's learning behavior score at each learning stage is calculated by cumulatively calculating the learning score, for example, (1) during the viewing segment video stage: the student watches the video segments for 1 minute, or watches the time length of the sub-segment video to exceed 70%, or collects or downloads, and any piece can be counted into 1 score, otherwise, the learning integral of the stage can be cumulatively increased, but the watching integral accumulation of each segmented video is not more than 5 scores; (2) in the depth play video phase: the learner clicks the high-definition playing for 30 seconds, slowly plays for 5 seconds, or plays for 30 seconds by a mirror, or plays for 30 seconds by AB circulation, 1 score can be counted as long as one time is satisfied, otherwise, 0 is counted, learning integral of the stage can be accumulated and increased, but the accumulated depth play integral of each segmented video is not more than 5 scores; (3) during the heel-strike practice phase: the duration of the student clicking and playing dance video exceeds 70%, which can be counted as 5 minutes, otherwise, the duration is 0; (4) uploading stage of dance video: each sub-segment video can dance, a learner can count 10 points when finishing the uploading of the dance video of one segment, and each learning segment can count 10 points when finishing the uploading of the dance video of a plurality of segments; (5) in the stage of learning dance knowledge: the duration of watching and learning dance knowledge video play exceeds 70% and can be counted as 5 minutes, otherwise, 0. Of course, the learning behavior score of the learner at each learning stage may be calculated by other methods or algorithms, which are not limited in the present application.
In some embodiments, the learning phase includes at least one of: a stage of watching segmented video, a stage of playing video in depth, a stage of training with jump, a stage of uploading dance video and a stage of learning dance knowledge.
In some embodiments, step S103, the obtaining a similar video list corresponding to the current dance video in each learning stage includes:
s1031: according to the learning behaviors of a learner in each learning stage, a plurality of first dance videos with the same learning behaviors of all users are obtained, and the similarity between the current dance video and the plurality of first dance videos is calculated by adopting a cosine similarity formula;
s1032: and sequencing and screening the first dance videos according to the similarity to obtain a similar video list.
In an exemplary embodiment, similar videos of all students in all dance rooms corresponding to the current dance video for different learning phases are obtained, for example, similar videos divided into the above 5 learning phases are calculated by the following method:
(1) During the viewing segment video phase: learning behavior to view segmented video may include, in particular: viewing, collecting, downloading, etc.; aiming at the watching behavior of a certain student on the current segmented dance video, a plurality of first dance videos (namely segmented dance videos) corresponding to learning behaviors of all students on the current segmented dance video are obtained, and the similarity between the plurality of first dance videos and the current segmented dance video is calculated. The similarity can be calculated using the following cosine similarity formula 1:
(equation 1)
Where a represents the user vector of the click segment video i, b represents the user vector of the click segment video j,representing the inner product of the two user vectors (i.e. the para-multiplication and then the addition).
(2) In the stage of deep video playing: the learning behavior of the depth play video may specifically include: click over slow release, AB circulation, mirror surface, screen projection, etc.; and aiming at the depth playing behavior of a certain student on the current segmented dance video, acquiring a plurality of first dance videos corresponding to the learning behavior of the depth playing of all students, and calculating the similarity between the plurality of first dance videos with the depth playing behavior and the current segmented dance video. The similarity can be calculated using cosine similarity formula 1 described above.
(3) In the heel jump training stage: the learning behavior of the dance training may be, for example, dance video playing with dance or dance training actions, and for playing behavior of a certain student on current dance video, a plurality of first dance videos (dance video) playing with dance or dance training actions by all students are obtained, and similarity between the plurality of first dance videos and the current dance video is calculated. The similarity can be calculated using cosine similarity formula 1 described above.
(4) Uploading stage of dance video: and uploading the dance video according to the learned current dance teaching video by a certain student, acquiring a plurality of learned first dance videos (dance teaching videos) corresponding to learning behaviors of all students for uploading the dance video, and calculating the similarity between the plurality of first dance videos (dance teaching videos) and the current dance teaching video. The similarity can be calculated using cosine similarity formula 1 described above.
(5) In the stage of learning dance knowledge: the learning behavior of learning the dance knowledge may be, for example, playing dance teaching video with shared knowledge and answer knowledge, playing the current dance teaching video for a certain student, obtaining a plurality of played first dance videos (dance teaching video with shared knowledge and answer knowledge) corresponding to the learning behavior of learning the dance knowledge for all users, and calculating the similarity between the plurality of first dance videos (dance teaching videos) and the current dance teaching video. The similarity can be calculated using cosine similarity formula 1 described above.
In each learning stage, the calculated similarity can be sequenced from large to small according to the similarity value, for example, to obtain a corresponding similar video list L of each learning stage, and the similar video list L can be represented by L1, L2, L3, L4, L5 and the like.
In some embodiments, step S104, the obtaining the learning preference interestingness of each learning stage according to the interaction data includes: and obtaining the learning preference interestingness of each learning stage according to the exposure times of the current dance video and the learning behavior score of each learning stage. Specifically, the calculation of learning preference interestingness of a certain learner in each learning stage can be calculated by the following conditional expression:
wherein P is X,Y The learning preference interestingness of the learner X in a Y-th learning stage (for example, a stage of watching segmented video, a stage of playing video deeply, a stage of exercising with jump, a stage of uploading dance video, and a stage of learning dance knowledge) is shown; s is S X,Y A learning behavior score representing the learner X at a Y-th learning stage; v represents the number of exposures of the current dance video placed in the dance room.
In some embodiments, step S105, the obtaining a recommended learning stage according to the learning preference interestingness of each learning stage includes: and comparing the learning preference interestingness of each learning stage, screening out the maximum value of the learning preference interestingness in all the learning stages, and obtaining the recommended learning stage. Specifically, if the learning preference interestingness P of the learner a in the 1 st learning stage A,1 The view segmented video phase may be considered a recommended learning phase for learner a, with values greater than other learning phases.
In other embodiments, step S105, the obtaining a recommended learning stage according to the learning preference interestingness of each learning stage includes: and taking the exposure times of the current dance video and the learning behavior score of each learning stage as a first parameter and a second parameter of the beta distribution respectively, sampling according to the beta distribution, and obtaining a recommended learning stage according to a sampling result. Specifically, the exposure times V of the current dance video and the learning behavior score of each learning stage are calculatedS X,Y As the parameter α and the parameter β of the beta distribution, respectively, in the above 5 learning phases, the maximum value of the sampling of the beta distribution is used as the next recommended learning phase, and the similar videos corresponding to the recommended learning phase acquired in step S103 are sequentially output as candidates from the similar video list L (L1, L2, L3, L4, L5) with the top ranking as the target recommended dance video. For example, when learning preference interestingness P of learner B B,1 And P B,4 Is equal, i.e. learner B likes 1 st learning stage and also likes 4 th learning stage, assuming that learner B is at S1 st learning stage B,1 A value of 10 and a V value of 100, S of the learner B in the 4 th learning stage B,4 The value is 1000 and the value V is 10000, so that the learning preference interest degree P of the learner B B,4 The confidence of (1) is higher, i.e. the recommended learning phase is the stage of uploading the dance video.
The embodiment of the application provides another dance video recommending method based on a dance room learning stage, as shown in fig. 3, which comprises the following specific steps:
s201: dividing learning dance videos in a dance room into a plurality of learning stages according to learning behaviors of learning dance through dance videos by students; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior;
s202: acquiring interactive data of a learner for learning a current dance video in each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories;
s203: obtaining learning preference interestingness of each learning stage according to the interaction data;
s204: obtaining recommended learning stages according to the learning preference interestingness of each learning stage;
s205: screening one or more second dance videos according to the first dance videos corresponding to the recommended learning stage; the first dance video is a dance video which a learner has learned; the second dance video is dance video of which at least a part of students are learned;
S206: and sequencing the second dance videos according to the reverse sequence of the time when the dance videos enter the dance room, and obtaining target recommended dance videos.
In the embodiment of the present application, the same points as those in the method steps S101 to S106 are not described in detail, and the difference is that:
s205: screening one or more second dance videos according to the first dance videos corresponding to the recommended learning stage; the first dance video is a dance video which a learner has learned; the second dance video is dance video of which at least a part of the students are learned. Specifically, for example, a learning stage recommended by a certain learner is a depth play video stage, which illustrates learning behavior that the learner likes the depth play video; in the stage of playing the video in depth, one or more second dance videos are selected from all dance videos which are learned by the student, namely, complete or incomplete in depth, and the second dance videos can be, for example, click too slow dance videos.
S206: and sequencing the second dance videos according to the reverse sequence of the time when the dance videos enter the dance room, and obtaining target recommended dance videos. Specifically, when the number of the second dance videos is multiple, the second dance videos are prioritized according to the reverse order of the time when the dance videos enter the dance room, and the second dance videos which enter the dance room newly are output as target recommended dance videos.
According to the embodiment of the application, aiming at all current dance videos learned by a certain student, the student possibly has different learning phases when learning each current dance video, correspondingly has different learning behaviors, the recommended learning phase is determined by calculating the learning preference interestingness of the student in the different learning phases, and the final recommended dance video and the accompanying text are determined according to the dance videos which the student has learned but not completed all learning in the recommended learning phase, so that each student can learn a plurality of interesting dances in a dance room; therefore, according to learning behaviors of interest of a learner, a recommended learning stage is obtained, and then according to the recommended learning stage, a target recommended dance video is obtained, so that the recommended dance teaching video is more accurate, and personalized recommendation aiming at the interests of a user can be realized.
The foregoing describes implementations and advantages of embodiments of the application in terms of a number of embodiments. The following describes in detail the specific processing procedure of the embodiment of the present application in conjunction with specific examples.
Example 1
The maximum value of the current learner is the 1 st learning stage, which indicates that the learning stage recommended to the current learner is the stage of watching the segmented video, the current learner prefers to watch the segmented video, the first unviewed dance video or the unviewed segmented dance video is required to be recommended to be obtained from the similar video L1 as the target recommended dance video, and the following scheme is attached:
Text1 (never viewed): "xxx video already has multiple dance rooms in itCollecting and storingLearning bar is started after learning;
text2 (not completely viewed): the "xxx video is already in your dance room,viewing ofThe integral can be increased.
Example 2
The maximum value of the current learner is the 2 nd learning stage, which indicates that the learning stage recommended to the current learner is the depth playing video stage, the current learner likes the depth playing video, the current learner can recommend to acquire the first dance video which is never watched from the similar video L2 to learn the same, and also recommend the dance video which is already learned but not yet completed with the depth playing, and the following is attached:
text3 (never viewed): "xxx video already has multiple dance rooms in itCirculation playingLearning bar is started after learning;
text4 (watched but not yet deep play), "you have completed segment learning of xxx video, the system provides you with more learning tools, convenienceDeep intoLearning).
Example 3
The maximum value of the current learner is the 3 rd learning stage, which indicates that the learning stage recommended to the current learner is the heel-and-jump training stage, the current learner prefers the heel-and-jump/heel-and-jump training learning behavior, the first non-watched dance video can be recommended to learn from the similar video L3, the dance video which has been learned but not completed the heel-and-jump/heel-and-jump training can be recommended, and the following is attached to the following document:
Text5 (not viewed): "xxx video has someone in multiple dance roomsHeel jumpLearning bar is started after learning;
text6 (viewed but not yet skip/heel-hold), "you have completed the learning of the view of xxx video, but not so muchHeel with heel body Training deviceA section of dance, strengthening learning.
Example 4
The maximum value of the current learner is the 4 th learning stage, which indicates that the learning stage recommended to the current learner is the stage of uploading the dance video, the current learner prefers the learning behavior of uploading the dance, the first non-watched dance video can be recommended to be obtained from the similar video L4 to learn and dance, the dance video which is learned but not finished with the dance can also be recommended, and the following scheme is attached:
text7 (not viewed): "xxx video already exists in multiple dance roomsDance-free toyPlease show a dance uploading bar "
Text8 (viewed), "you have completed part of the learning of xxx videos, please continueXiuyi sectionDance, promote study bar.
Example 5
The maximum value of the current learner is the 5 th learning stage, which indicates that the learning stage recommended to the current learner is the learning dance knowledge stage, the current learner is interested in learning behaviors of acquiring knowledge and sharing knowledge, the first non-learned dance video can be recommended to be acquired from the similar video L5, the dance video which is already learned but not completely learned can also be recommended, and the following scheme is attached:
Text9 (not learned): "xxx video includes dance actions you are interested inKnowledge ofPleaseBegin learning bar ";
text10 (learned): "someone asks you for knowledge of the xxx video learned in the dance room, please guide Ta down the bar".
The bolded and underlined typeface in examples 1-5 represents the corresponding learning stage keywords in the text.
Corresponding to the embodiments in the method steps S101 to S106, the embodiment of the present application provides a dance video recommendation device based on a dance room learning stage, as shown in fig. 4, which specifically may include:
the dividing module 410 divides learning dance video in the dance room into a plurality of learning phases according to learning behaviors of a learner learning dance through the dance video; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior;
a first obtaining module 420, configured to obtain interactive data of a learner learning a current dance video at each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories;
A second obtaining module 430, configured to obtain a similar video list corresponding to the current dance video in each learning stage;
an interestingness module 440, configured to obtain learning preference interestingness of each learning stage according to the interaction data;
a first recommendation module 450, configured to obtain recommended learning phases according to the learning preference interestingness of each learning phase;
and the second recommending module 460 is configured to obtain a target recommended dance video according to the similar video list corresponding to the recommended learning stage.
Corresponding to the embodiments in the method steps S201 to S206, the embodiment of the present application provides another dance video recommendation device based on a dance room learning stage, as shown in fig. 5, which specifically may include:
the dividing module 510 divides learning dance video in the dance room into a plurality of learning phases according to learning behaviors of learning dance by a learner through the dance video; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior;
a first obtaining module 520, configured to obtain interactive data of a learner learning a current dance video at each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories;
An interestingness module 530, configured to obtain a learning preference interestingness of each learning stage according to the interaction data;
a first recommendation module 540, configured to obtain recommended learning phases according to the learning preference interestingness of each learning phase;
a screening module 550, configured to screen one or more second dance videos according to the first dance video corresponding to the recommended learning stage; the first dance video is a dance video which a learner has learned; the second dance video is dance video of which at least a part of students are learned;
and the second recommending module 560 is configured to sort the second dance videos according to a reverse order of the time when the dance videos enter the dance room, so as to obtain target recommended dance videos.
The electronic device in the embodiment of the application can be user terminal equipment, a server, other computing devices and a cloud server. Fig. 6 shows a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application, where the electronic device may include a processor 601 and a memory 602 storing computer program instructions, where the processor 601 implements the flow or functions of any of the methods of the embodiments described above when executing the computer program instructions.
In particular, the processor 601 may include a Central Processing Unit (CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present application. Memory 602 may include mass storage for data or instructions. For example, the memory 602 may be at least one of: hard Disk Drive (HDD), read-only memory (ROM), random-access memory (RAM), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, universal serial bus (Universal Serial Bus, USB) Drive, or other physical/tangible memory storage device. As another example, the memory 602 may include removable or non-removable (or fixed) media. For another example, memory 602 may be internal or external to the integrated gateway disaster recovery device. The memory 602 may be a non-volatile solid state memory. In other words, generally the memory 602 includes a tangible (non-transitory) computer-readable storage medium (e.g., a memory device) encoded with computer-executable instructions and when the software is executed (e.g., by one or more processors) may perform the operations described by the methods of embodiments of the application. The processor 601 implements the flow or functions of any of the methods of the above embodiments by reading and executing computer program instructions stored in the memory 602.
In one example, the electronic device shown in fig. 6 may also include a communication interface 603 and a bus 610. The processor 601, the memory 602, and the communication interface 603 are connected to each other through a bus 610 and perform communication with each other. The communication interface 603 is mainly used to implement communications between modules, apparatuses, units, and/or devices in the embodiments of the present application. Bus 610 includes hardware, software, or both, and may couple components of the online data flow billing device to each other. For example, the bus may include at least one of: accelerated Graphics Port (AGP) or other graphics bus, enhanced Industry Standard Architecture (EISA) bus, front Side Bus (FSB), hyperTransport (HT) interconnect, industry Standard Architecture (ISA) bus, infiniBand interconnect, low Pin Count (LPC) bus, memory bus, micro channel architecture (MCa) bus, peripheral Component Interconnect (PCI) bus, PCI-Express (PCI-X) bus, serial Advanced Technology Attachment (SATA) bus, video electronics standards Association local (VLB) bus, or other suitable bus. Bus 610 may include one or more buses. Although embodiments of the application describe or illustrate a particular bus, embodiments of the application contemplate any suitable bus or interconnection.
In connection with the methods of the above embodiments, embodiments of the present application also provide a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the flow or function of any of the methods of the above embodiments.
In addition, the embodiment of the present application further provides a computer program product, where the computer program product stores computer program instructions, and the computer program instructions implement the flow or the function of any one of the methods in the above embodiments when the computer program instructions are executed by a processor.
The foregoing exemplarily describes the flow diagrams and/or block diagrams of methods, apparatus, systems, and computer program products according to embodiments of the present application, and describes various aspects related thereto. It will be understood that each block of the flowchart illustrations and/or block diagrams, or combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions, special purpose hardware which perform the specified functions or acts, and combinations of special purpose hardware and computer instructions. For example, 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 present application, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit.
Functional blocks shown in the block diagrams of the embodiments of the present application can be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like; when implemented in software, are the programs or code segments used to perform the required tasks. The program or code segments can be stored in a memory or transmitted over transmission media or communication links through data signals carried in carrier waves. The code segments may be downloaded via computer networks such as the internet, intranets, etc.
It should be noted that the present application is not limited to the specific configurations and processes described above or shown in the drawings. The foregoing is merely specific embodiments of the present application, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working processes of the described system, apparatus, module or unit may refer to corresponding processes in the method embodiments, and need not be repeated. It should be understood that the scope of the present application is not limited thereto, and any person skilled in the art may conceive various equivalent modifications or substitutions within the technical scope of the present application, which are intended to be included in the scope of the present application.
Claims (9)
1. A dance video recommendation method based on a dance room learning stage is characterized by comprising the following steps:
dividing learning dance videos in a dance room into a plurality of learning stages according to learning behaviors of learning dance through dance videos by students; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior;
acquiring interactive data of a learner for learning a current dance video in each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories;
obtaining a similar video list corresponding to the current dance video in each learning stage;
obtaining learning preference interestingness of each learning stage according to the interaction data;
obtaining recommended learning stages according to the learning preference interestingness of each learning stage;
obtaining target recommended dance videos according to the similar video list corresponding to the recommended learning stage; wherein,
the obtaining the interactive data of the current dance video learned by the learner in each learning stage comprises the following steps: acquiring the exposure times of the current dance video; acquiring the clicking times of clicking the current dance video by a student; obtaining learning behavior scores of students in each learning stage; the learning behavior score is obtained by scoring the learning behaviors of the learner in each learning stage;
The learning preference interestingness of each learning stage is obtained according to the interaction data, and the learning preference interestingness comprises the following steps: and obtaining the learning preference interestingness of each learning stage according to the exposure times of the current dance video and the learning behavior score of each learning stage.
2. The method of claim 1, wherein the learning phase comprises at least one of: a stage of watching segmented video, a stage of playing video in depth, a stage of training with jump, a stage of uploading dance video and a stage of learning dance knowledge.
3. The method of claim 1, wherein the obtaining a list of similar videos corresponding to the current dance video for each learning phase comprises:
according to the learning behaviors of a learner in each learning stage, a plurality of first dance videos with the same learning behaviors of all users are obtained, and the similarity between the current dance video and the plurality of first dance videos is calculated by adopting a cosine similarity formula;
and sequencing and screening the first dance videos according to the similarity to obtain a similar video list.
4. The method of claim 1, wherein the learning phase for obtaining the recommendation based on the learning preference interestingness of each learning phase comprises:
Comparing the learning preference interestingness of each learning stage, screening out the maximum value of the learning preference interestingness in all learning stages, and obtaining a recommended learning stage; or,
and taking the exposure times of the current dance video and the learning behavior score of each learning stage as a first parameter and a second parameter of the beta distribution respectively, sampling according to the beta distribution, and obtaining a recommended learning stage according to a sampling result.
5. A dance video recommendation method based on a dance room learning stage is characterized by comprising the following steps:
dividing learning dance videos in a dance room into a plurality of learning stages according to learning behaviors of learning dance through dance videos by students; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior;
acquiring interactive data of a learner for learning a current dance video in each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories;
obtaining learning preference interestingness of each learning stage according to the interaction data;
Obtaining recommended learning stages according to the learning preference interestingness of each learning stage;
screening one or more second dance videos according to the first dance videos corresponding to the recommended learning stage; the first dance video is a dance video which a learner has learned; the second dance video is dance video of which at least a part of students are learned;
sequencing the second dance videos according to the reverse sequence of the time when the dance videos enter the dance room, and obtaining target recommended dance videos; wherein,
the obtaining the interactive data of the current dance video learned by the learner in each learning stage comprises the following steps: acquiring the exposure times of the current dance video; acquiring the clicking times of clicking the current dance video by a student; obtaining learning behavior scores of students in each learning stage; the learning behavior score is obtained by scoring the learning behaviors of the learner in each learning stage;
the learning preference interestingness of each learning stage is obtained according to the interaction data, and the learning preference interestingness comprises the following steps: and obtaining the learning preference interestingness of each learning stage according to the exposure times of the current dance video and the learning behavior score of each learning stage.
6. Dance video recommending apparatus based on dance room study stage, characterized by comprising:
the dividing module is used for dividing the learning dance video in the dance room into a plurality of learning stages according to learning behaviors of learning dance by a learner through the dance video; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior;
the first acquisition module is used for acquiring interactive data of a learner for learning the current dance video in each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories;
the second acquisition module is used for acquiring a similar video list corresponding to the current dance video in each learning stage;
the interest degree module is used for obtaining learning preference interest degree of each learning stage according to the interaction data;
the first recommendation module is used for obtaining recommended learning stages according to the learning preference interestingness of each learning stage;
the second recommendation module is used for obtaining target recommended dance videos according to the similar video list corresponding to the recommended learning stage; wherein,
The method for acquiring the interactive data of the current dance video learned by the learner in each learning stage comprises the following steps: acquiring the exposure times of the current dance video; acquiring the clicking times of clicking the current dance video by a student; obtaining learning behavior scores of students in each learning stage; the learning behavior score is obtained by scoring the learning behaviors of the learner in each learning stage;
obtaining learning preference interestingness of each learning stage according to the interaction data, wherein the learning preference interestingness comprises the following steps: and obtaining the learning preference interestingness of each learning stage according to the exposure times of the current dance video and the learning behavior score of each learning stage.
7. Dance video recommending apparatus based on dance room study stage, characterized by comprising:
the dividing module is used for dividing the learning dance video in the dance room into a plurality of learning stages according to learning behaviors of learning dance by a learner through the dance video; the dance room is used for learning dance actions and dance knowledge in the set category dance video by students; each learning phase correspondingly comprises a learning behavior;
the first acquisition module is used for acquiring interactive data of a learner for learning the current dance video in each learning stage; the current dance video is one or more of dance videos which are put in a dance room and used for students to learn the set categories;
The interest degree module is used for obtaining learning preference interest degree of each learning stage according to the interaction data;
the first recommendation module is used for obtaining recommended learning stages according to the learning preference interestingness of each learning stage;
the screening module is used for screening one or more second dance videos according to the first dance videos corresponding to the recommended learning stage; the first dance video is a dance video which a learner has learned; the second dance video is dance video of which at least a part of students are learned;
the second recommending module is used for sequencing the second dance videos according to the reverse order of the time when the dance videos enter the dance room, so as to obtain target recommended dance videos; wherein,
the method for acquiring the interactive data of the current dance video learned by the learner in each learning stage comprises the following steps: acquiring the exposure times of the current dance video; acquiring the clicking times of clicking the current dance video by a student; obtaining learning behavior scores of students in each learning stage; the learning behavior score is obtained by scoring the learning behaviors of the learner in each learning stage;
Obtaining learning preference interestingness of each learning stage according to the interaction data, wherein the learning preference interestingness comprises the following steps: and obtaining the learning preference interestingness of each learning stage according to the exposure times of the current dance video and the learning behavior score of each learning stage.
8. An electronic device, the electronic device comprising: a processor and a memory storing computer program instructions; the electronic device implementing the method of any one of claims 1-4 or claim 5 when executing the computer program instructions.
9. A computer readable storage medium, having stored thereon computer program instructions which, when executed by a processor, implement the method of any one of claims 1-4 or claim 5.
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