CN112395458A - Video course recommendation system and video course recommendation method for fitness equipment - Google Patents
Video course recommendation system and video course recommendation method for fitness equipment Download PDFInfo
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Abstract
The invention discloses a video course recommendation system of fitness equipment, which is provided with a login module, a video database and an analysis recommendation module which are mutually connected, so that after a user logs in the video course recommendation system, the user can automatically acquire the product serial number in account information through the analysis recommendation module to judge the type of the fitness equipment actually owned by the user, further, the analysis recommendation module automatically searches out a video file which is in accordance with the type of the fitness equipment in the video database, scores are carried out according to the total click number of the screened video files and the file creation time, the priority recommendation sequence arrangement can be carried out according to the grade result, and the recommendation sequencing of the video files is completed. The invention has the efficacy of actively recommending the latest video courses which are in line with the fitness equipment actually owned by the user.
Description
Technical Field
The present invention relates to a network system for providing video courses for exercise equipment, and more particularly, to a video course recommendation system and a video course recommendation method for actively recommending video courses meeting the actual exercise requirements of a user.
Background
Modern people often cannot exercise outdoors due to busy work or limited weather, and therefore the popularity of indoor fitness equipment is brought forward nowadays.
However, after purchasing new fitness equipment, a user often unfamiliar with how to use the fitness equipment, and searches videos of related teaching courses by self on the internet to be used as a reference for self training, but even if the video courses of the fitness equipment are searched through the internet, many irrelevant or uninteresting videos are often searched, so that the user needs to know whether to meet self training requirements after clicking and watching one by one, and time of the user is wasted unnecessarily.
In addition, although some manufacturers place related video courses on the network platform for consumers to refer to according to the fitness equipment sold by the manufacturers at present, the video courses provided by the manufacturers are only classified and placed according to the types of the fitness equipment at best, but the video courses do not have the function of actively recommending the video courses, so that the users still have to select the types of the fitness equipment by themselves after entering the network platform and enter the web pages of the corresponding video courses, and even if the users enter the web pages storing the corresponding video courses, the users still have to click and watch the web pages one by one to really find the video courses meeting the self-exercise requirements.
In view of the above, how to provide a video course recommendation system and a video course recommendation method capable of actively recommending fitness equipment that is actually owned by a user is a primary subject to be solved by the present invention.
Disclosure of Invention
The invention mainly aims to provide a video course recommendation system of fitness equipment and a video course recommendation method thereof, which have the efficacy of initiatively recommending the latest video courses which are in line with the fitness equipment actually owned by a user.
To achieve the above object, the present invention provides a video course recommendation system for fitness equipment, configured to be installed on a network, the video course recommendation system for fitness equipment comprising a login module, a video database and an analysis recommendation module, wherein:
the login module stores account data pre-registered by a user, the account data at least comprises a product serial number, a user name and an account password, and the product serial number contains an identification code pointing to a specific fitness equipment type;
the video database is used for storing a plurality of video files, and each video file is respectively provided with corresponding video information, and the video information comprises a video number, a fitness equipment type, at least one remark label, a name of a lecturer, file creation time and total clicks;
the analysis recommending module can be used for capturing the product serial number in the account information to judge the type of the fitness equipment and searching the video files which accord with the type of the fitness equipment in the video database, and the analysis recommending module gives an evaluation score to each video file which accords with the type of the fitness equipment according to the total click number and the file creating time and arranges the video files which accord with the type of the fitness equipment in sequence according to the height of the evaluation score.
In addition, the invention also provides a video course recommendation method of the fitness equipment, which comprises the following steps:
the user logs in a video course recommendation system through a network by using an electronic device, the video course recommendation system of the fitness equipment comprises a login module, a video database and an analysis recommendation module which are mutually connected, the login module stores account data which is registered in advance by the user, the account data at least comprises a product serial number, a user name and an account password, the product serial number contains an identification code pointing to a specific fitness equipment type, the video database stores a plurality of video files, each video file respectively contains corresponding video information, and the video information contains a video number, the fitness equipment type, at least one remark label, a lecturer name, file creation time and total clicks;
the analysis recommending module is used for capturing the product serial number in the account information to judge the type of the fitness equipment, searching the video files which accord with the type of the fitness equipment in the video database, classifying the video files which accord with the type of the fitness equipment according to the remark labels of the video files, and eliminating repeated video files to integrate into a video file list;
giving a weighted value to each video file in the video file list according to the total click number and the file creation time of each video file through the analysis recommendation module, and then respectively adding the total click number and the weighted value of the file creation time of each video file in the video file list to respectively calculate the evaluation score of each video file in the video file list;
and arranging the video files according with the fitness equipment category according to the summed evaluation scores so as to complete the recommendation and sequencing and display the video files on a display screen of the electronic device.
The invention has the advantages that:
the video course recommendation system of the fitness equipment and the video course recommendation method thereof have the effect of initiatively recommending the latest video courses which are in line with the fitness equipment actually owned by the user.
Drawings
FIG. 1 is a block diagram of a video course recommendation system according to the present invention.
FIG. 2 is a flowchart illustrating the steps of a video course recommendation method according to the present invention.
Detailed Description
As shown in fig. 1, a video course recommendation system 10 for exercise equipment provided by the present invention is provided, the video course recommendation system 10 is composed of a server installed on the internet (internet), the video course recommendation system 10 is mainly composed of a login module 11, a video database 12 and an analysis recommendation module 13, and each module can be a program code for the server processor to run, such as a firmware or a software program stored in the server memory or hardware, wherein:
the login module 11 stores an account data pre-registered by the user, wherein the account data at least comprises a product serial number, a user name and an account password, and the product serial number contains an identification code pointing to a specific fitness equipment type (such as a flywheel vehicle, a treadmill, an elliptical machine, a fitness vehicle, a rowing machine, a weight training machine, a small fitness equipment, a stretcher. The login module 11 is capable of allowing at least one user to connect to the video course recommendation system 10 through an electronic device 21, the electronic device 21 may be a device with internet access function, such as a smart phone, a desktop computer, a notebook computer, a tablet computer, etc., and a login page is capable of being displayed through the login module 11 for the user to input account data for verification.
The Video database 12 is composed of a storage unit (e.g. hard disk and other hardware equipment) and can store a plurality of Video files, and each Video file is stored in the Video database 12 before an information editing operation is performed in advance, so that each Video file carries corresponding Video information, and the Video information includes a Video number, a Video name, a fitness equipment category, at least one remark label (tag), a lecturer name, and file creation time. The remark labels are classified and labeled by editors in advance according to the video training content of each video file, such as the first-order, the middle-order, the high-order, the heart and lung, the fat burning, the leg slimming, the muscle endurance, the sweating, the swinging, the explosive power … and the like, and a single video file can further simultaneously contain a plurality of remark labels.
The analysis recommending module 13 automatically retrieves the product serial number in the account information after the user logs in the video course recommending system 10, and determines a type of the fitness equipment according to the identification code in the product serial number, and the analysis recommending module 13 further displays a set page for the user to input at least one specific remark label, so that the analysis recommending module 13 can automatically search the video files meeting the search condition in the video database 12 by taking the type of the fitness equipment and the specific remark label as the search condition, and the analysis recommending module 13 gives an evaluation score to each video file meeting the search condition according to the total click number and the file creating time, arranges the video files meeting the type of the fitness equipment in sequence according to the level of the evaluation score, and then displays the video files on the display screen of the electronic device 21 in sequence. Furthermore, the analysis recommending module 13 can further record the total hit count of each video file and write back the total hit count to the video information of the corresponding video file, so that the video information can further include the total hit count information.
With the video course recommending system 10 composed of the above components, when a user logs in the video course recommending system 10, the product serial number in the account information can be automatically retrieved through the analyzing and recommending module 13 to determine the type of the exercise equipment actually owned by the user, and further, through the user inputting interested remark labels, the analyzing and recommending module 13 can automatically compare and search out all video files in the video database 12 that meet the search condition, and then, after scoring is performed according to the total clicks of the screened video files and the file creating time, the arrangement of the priority recommending sequence can be performed according to the height of the scoring result, so as to complete the recommending and ordering of the video files for the user to refer. Therefore, the time for the user or the beginner to search for the suitable video course can be greatly reduced, and the video course recommendation system 10 provided by the invention can ensure that the recommended course is the latest video course which is more interesting to the user by simultaneously listing the total clicks and the file creation time as the scoring items.
Referring to fig. 2, the present invention further provides a video course recommendation method for a fitness apparatus, wherein the video course recommendation method comprises the following steps:
A. the user uses an electronic device 21 to connect to the video course recommending system 10 through the network, the video course recommending system 10 of the fitness equipment comprises a login module 11, a video database 12 and an analysis recommending module 13 which are connected with each other, the login module 11 stores an account data which is registered in advance by the user, the account data at least comprises a product serial number, a user name and an account password, the product serial number contains an identification code pointing to a specific fitness equipment type (such as a flywheel car, a treadmill, an elliptical machine, a fitness car, a rowing machine, a weight trainer, a small fitness equipment, a stretcher, and the like), the login module 11 can display a login page for the user to input the account data for verification, the video database 12 comprises a plurality of video files, and each video file contains corresponding video information, the video information includes a video number, a video name, a type of exercise equipment, at least one remark label, a name of a lecturer, a file creation time and a total number of clicks. The remark labels are classified and labeled by editors in advance according to the video training contents of the video files, for example, the video remark items such as the first-order, the middle-order, the high-order, the heart and lung, the fat burning, the leg slimming, the muscle endurance, the sweating, the swinging and the explosive power … are formed, and a single video file can further simultaneously comprise a plurality of remark labels. Of course, the user who has not joined the member can log in the video course recommendation system of the present invention after a registration procedure is performed to establish the account data.
B. The analysis recommending module 13 captures the product serial number in the account information, and determines a type of the exercise equipment according to the identification code in the product serial number, and the analysis recommending module 13 further displays a set page for the user to input at least one specific remark label, so that the analysis recommending module 13 can automatically search the video files meeting the search condition in the video database 12 by using the type of the exercise equipment and the specific remark label as search conditions, classify the video files meeting the search condition according to the remark labels, and eliminate repeated video files and integrate into a video file list. The analysis and recommendation module 13 searches the video files meeting the search condition by using the product serial number in the account information and the specific remark label set by the user, and then selects at most 20 video files from the video files having the same remark label, for example, 20 video files from the flywheel vehicle (type of fitness equipment) + the initial stage (remark label), 20 video files from the flywheel vehicle (type of fitness equipment) + the heart lung (remark label), and then eliminates the repeated video files to integrate into the video file list required subsequently. In addition, when the user does not input a specific remark label, the analysis recommending module 13 will search out the video file conforming to the category of the fitness equipment according to the product serial number in the account information, so as to be referred by the user when the user needs to input the specific remark label in the following process, or be directly clicked by the user for viewing.
C. A weighted value is given to each video file in the video file list according to the total click number and the file creation time of each video file through the analysis recommendation module 13, and then the total click number and the weighted value of the file creation time of each video file in the video file list are added up respectively to calculate the evaluation score of each video file in the video file list. The analysis recommending module 13 creates two ranking tables according to the total click number and the file creating time of each video file, and gives a preset weight value according to the sequence of the total click number and the file creating time, and the obtainable weight values decrease sequentially according to the ranking order, for example, 50 video files are totally in the total click ranking table, the first video file in the ranking can obtain a weight value of 50 points, and if the same video file is ranked in the 11 th video file in the file creating time ranking table (likewise 50 video files totally), a weight value of 39 points can be obtained, and then the weight values obtained by the same video file in the total click ranking table and the file creating time ranking table are summed up, so that an evaluation score of 89 points can be obtained.
D. The video files in the video file list are arranged in sequence according to the summed evaluation scores, and the priority recommendation sequence is arranged according to the scores to complete a recommendation sequence and display on the display screen of the electronic device 21. Wherein, a user viewing record is further established in the account data of the log-in module 11, the user viewing record can record the video number of the video file viewed by the user, and the video file viewed by the user can be eliminated from the recommendation sequence completed by the analysis recommendation module according to the user viewing record.
In addition, the analysis recommending module 13 is further configured with a sorting condition in advance, and completes the recommendation sorting according to the sorting condition, so that the recommendation sorting completed by the analysis recommending module 13 at least has four recommended video files, and the sorting condition is: the first video file is the one with the highest evaluation score, the second video file is the video file with the same name of the lecturer as the first video file, the third video file is the video file with the same remark label, the fourth video file is the video file with the newest file creation time, when the video files have the same sequence, the repeated video files are removed, and the video files are supplemented by the other video file which meets the sorting condition. And through the sorting condition, the first video file can be the video file with the highest evaluation score after the analysis recommendation module carries out score calculation, and the second, third and fourth video files are the video files which are preset and recommended by the system, so that the recommended first video file can completely meet the requirements of the user, and the video files (namely the second, third and fourth video files) which are preset and recommended by the system can meet the possible potential requirements of the user, and simultaneously have the function of popularizing latest product information.
It can be clearly understood from the above detailed description that the video course recommendation method for fitness equipment provided by the present invention utilizes the user to log in the video course recommendation system 10, and then automatically retrieve the product serial number in the account information through the analysis recommendation module 13 to determine the type of the fitness equipment actually owned by the user, and further automatically input the interested remark label through the user, so that the analysis recommendation module 13 can automatically compare and search out all the video files meeting the search condition in the video database 12, and then score according to the total click number of the screened video files and the file creation time, and then arrange the priority recommendation sequence according to the level of the score result, thereby completing the recommendation and ranking of the video files. Therefore, the time for a user or a beginner to search for a suitable video course can be greatly shortened, and the video course recommending method of the fitness equipment provided by the invention can obtain the best recommendation sequence by simultaneously listing the total clicks and the file creating time as scoring items and summing up the scoring items to obtain the evaluation scores, so as to ensure that the recommended course is the latest video course which is more interesting to the user, and can simultaneously meet the possible potential requirements of the user and promote the latest product information, thereby greatly improving the operation experience of the user.
The above description is of the preferred embodiment of the present invention and the technical principles applied thereto, and it will be apparent to those skilled in the art that any changes and modifications based on the equivalent changes and simple substitutions of the technical solution of the present invention are within the protection scope of the present invention without departing from the spirit and scope of the present invention.
Claims (8)
1. A video course recommendation system of fitness equipment is built on a network and is characterized in that: the video course recommending system of the body-building equipment comprises a login module, a video database and an analysis recommending module which are mutually connected, wherein:
the login module stores account data pre-registered by a user, the account data at least comprises a product serial number, a user name and an account password, and the product serial number contains an identification code pointing to a specific fitness equipment type;
the video database is used for storing a plurality of video files, and each video file is respectively provided with corresponding video information, and the video information comprises a video number, a fitness equipment type, at least one remark label, a name of a lecturer, file creation time and total clicks;
the analysis recommending module can be used for capturing the product serial number in the account information to judge the type of the fitness equipment, and can be used for a user to input at least one specific remark label to search the video files which are in accordance with the video database, and the analysis recommending module gives an evaluation score to each video file which is in accordance with the total clicking number and the file creating time, arranges the video files in sequence according to the height of the evaluation score, and displays the video files on a display screen.
2. The video lesson recommendation system for exercise equipment of claim 1, wherein: the electronic device is a smart phone, a desktop computer, a notebook computer or a tablet computer with the internet access function, and a login page can be displayed through the login module so that a user can input account data for verification.
3. The video lesson recommendation system for exercise equipment of claim 1, wherein: the analysis recommending module can record the total clicks of each video file and write back the total clicks to the video information of the corresponding video file.
4. A video course recommendation method of fitness equipment is characterized by comprising the following steps: the method comprises the following steps:
the user logs in a video course recommendation system through a network by using an electronic device, the video course recommendation system of the fitness equipment comprises a login module, a video database and an analysis recommendation module which are mutually connected, the login module stores account data which is registered in advance by the user, the account data at least comprises a product serial number, a user name and an account password, the product serial number contains an identification code pointing to a specific fitness equipment type, the video database stores a plurality of video files, each video file respectively contains corresponding video information, and the video information contains a video number, the fitness equipment type, at least one remark label, a lecturer name, file creation time and total clicks;
the analysis recommending module is used for capturing the product serial number in the account information to judge the type of the fitness equipment, and a user inputs at least one specific remark label, so that the analysis recommending module searches the video files which accord with the type of the fitness equipment and the at least one specific remark label in the video database, classifies the accordant video files according to the remark labels, and eliminates repeated video files to integrate into a video file list;
giving a weighted value to each video file in the video file list according to the total click number and the file creation time of each video file through the analysis recommendation module, and then respectively adding the total click number and the weighted value of the file creation time of each video file in the video file list to respectively calculate the evaluation score of each video file in the video file list;
and arranging the video files in the video file list according to the summed evaluation scores to complete a recommendation sequence and display the recommendation sequence on a display screen of the electronic device.
5. The method for video lesson recommendation for exercise equipment of claim 4, wherein: the analysis recommending module respectively creates two ranking tables according to the total click number and the file creating time of each video file, and respectively gives a preset weight value according to the sequence of the total click number and the file creating time, and the height of the available weight values is sequentially decreased according to the ranking sequence.
6. The method for video lesson recommendation for exercise equipment of claim 4, wherein: a user viewing record is further established in the account data of the log-in module, the user viewing record can record the video number of the video file viewed by the user, and the video file viewed by the user is removed from the recommended sequence according to the user viewing record.
7. The method for video lesson recommendation for exercise equipment of claim 4, wherein: the analysis recommending module is further preset with a sorting condition, and completes the recommendation sorting according to the sorting condition, the recommendation sorting at least has four recommended video files, and the sorting condition is that the first video file is the one with the highest evaluation score, the second video file is the video file with the same name of the lecturer as the first video file, the third video file is the video file with the same remark label, the fourth video file is the video file with the newest file creation time, and when the video files have the same sequence, the repeated video file is removed and supplemented by another video file meeting the sorting condition.
8. The method for video lesson recommendation for exercise equipment of claim 4, wherein: the exercise equipment can be flywheel vehicle, running machine, elliptical machine, exercise vehicle, rowing machine, weight training machine, small exercise equipment or stretching machine, the remark label can be the video remark items of first order, middle order, high order, heart lung, fat burning, leg slimming, muscle endurance, sweating, swinging or explosive force, and the single video file can simultaneously contain a plurality of remark labels.
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