Education information management and maintenance system based on education platform

Abstract

The invention belongs to the technical field of educational information management, and relates to an educational information management and maintenance system based on an educational platform. Analyzing the current playing function completeness degree, the reference data timeliness degree and the teaching competitiveness index of the specified teaching video to judge whether the specified teaching video has the relative teaching value or not, if so, extracting each storage position allocated by the target education platform for the specified teaching video according to a hierarchical tag storage mode, and storing the extracted storage positions in the target education platform; whether the specified teaching video storage position has an adjustment requirement or not is judged, corresponding adjustment operation is executed under the judgment condition, if not, the specified teaching video is cleared from the target education platform, maintenance clearing and storage optimization of education platform teaching video resources are effectively achieved, fair distribution and sustainable development of the education resources are promoted, and the education efficiency is improved. And the management efficiency of the education platform is obviously improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of educational information management, and relates to an educational information management and maintenance system based on an educational platform. Background Art

[0002] With the rapid development of online education, as an important carrier of teaching activities, the importance of educational platforms has become increasingly prominent. To maintain the timeliness, accuracy, and attractiveness of teaching content and ensure a high-quality teaching experience, a robust educational information management and maintenance system is indispensable.

[0003] In the prior art, there are also solutions related to educational information management and maintenance. For example, an educational platform educational management information maintenance system with the Chinese patent publication number CN110807723A includes a registration / login module, a lesson preparation module, a storage module, a learning system generation module, an interactive platform, a learning module, an information collection module, an authentication module, and a modification module, which can effectively ensure the stability of the update management of educational management information, ensure that the modified content is within the expected modification range, and prevent the intrusion of content that does not conform to the educational platform, with high stability.

[0004] Another Chinese patent with the publication number CN110717734A is an educational resource management platform, which includes a student information management unit that records and stores the personal profile information of students, the browsing record information of students on course resources, and the collection information of students on course resources; a teacher information management unit that records and stores the personal profile and teaching file information uploaded by each teacher, the created test papers and assignments, and the recorded student achievement information; the teaching management unit that tracks and records the online learning process of students and saves the assignments completed by students online; a system maintenance unit that updates and saves the update logs and user operation logs of the platform in the working state, and the system maintenance unit establishes multiple departments according to the different majors of students and multiple identity permissions according to the different identities of users; a system security unit that maintains the physical security and network security of the platform in the working state in real time.

[0005] However, there are still certain limitations in the prior art regarding the management and maintenance of teaching video resources in educational information. Specifically, 1. In the prior art, there is a regular cleaning and maintenance mechanism for teaching video resources on educational platforms. However, the video cleaning evaluation criteria overly rely on two relatively single dimensions, namely the input time and viewing popularity of teaching videos, ignoring the relative teaching value evaluation of the educational platforms where the teaching videos are located, deviating from the core requirement of optimizing the allocation of educational resources, and being unable to accurately screen out truly low-quality or redundant teaching videos, thus making it difficult to promote the high-quality development of teaching resources on educational platforms.

[0006] 2. The existing technology lacks a mechanism for regularly adjusting the storage locations of teaching videos in an educational platform. It mostly adopts a static storage strategy, making it difficult to ensure the rationality and effectiveness of the storage locations, and thus unable to improve the retrieval efficiency of teaching video resources for users of the educational platform. Summary of the Invention

[0007] In view of this, to solve the problems raised in the above background technology, a teaching information management and maintenance system based on an educational platform is proposed.

[0008] The object of the present invention can be achieved through the following technical solutions: The present invention provides a teaching information management and maintenance system based on an educational platform, including: a source data extraction module, a teaching value judgment module, a video storage adjustment module, a video deletion module, and a cloud database.

[0009] The source data extraction module is connected to the teaching value judgment module. The teaching value judgment module is respectively connected to the video storage adjustment module and the video deletion module. The cloud database is respectively connected to the teaching value judgment module and the video storage adjustment module.

[0010] The source data extraction module is used to extract the specified teaching video source data on the regular data maintenance day of the target educational platform, including the author, teaching subject, teaching grade stage, video title name, reference teaching material version, release time, and high-frequency keyword set of the video text content.

[0011] The teaching value judgment module is used to conduct a playback test on the specified teaching video, and in combination with the source data of the specified teaching video, analyze the current playback function integrity, reference material timeliness, and teaching competitiveness index of the specified teaching video, so as to judge whether the specified teaching video currently has relative teaching value. If not, the video deletion module is executed. If so, the video storage adjustment module is executed.

[0012] The video storage adjustment module is used to extract each storage location assigned to the specified teaching video by the target educational platform according to the hierarchical label storage method, and judge whether there is a need to adjust the storage location of the specified teaching video. If it is judged that there is a need, the corresponding adjustment operation is executed.

[0013] The video deletion module is used to delete the specified teaching video from the target educational platform.

[0014] The cloud database is used to store the preset compliance thresholds corresponding to the playback function integrity, reference material timeliness, and teaching competitiveness index of the teaching videos with relative teaching value in the target educational platform, store the knowledge graphs formulated for each teaching subject in the target educational platform, and store the preset trigger thresholds of the adjustment demand index corresponding to the teaching grade stage and the high-frequency keyword set of the video text content when there is a need to adjust the storage location of the teaching videos in the target educational platform.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) By analyzing the current integrity of the playback function of a specified teaching video, the timeliness of reference materials, and the teaching competitiveness index, the present invention accurately determines whether the specified teaching video currently has relative teaching value, and uses this as the basis for video deletion, which helps the target education platform to promptly identify and delete teaching videos with low teaching value or those that are outdated, thereby optimizing the management and allocation of educational resources.

[0016] (2) For each storage location allocated by the target education platform of the present invention for the specified teaching video according to the hierarchical tag storage method, the storage location of the teaching video can be accurately located by virtue of the hierarchical tags, which not only realizes efficient retrieval but also provides a basis for the subsequent execution of storage location adjustment operations.

[0017] (3) By analyzing the teaching grade stage of the specified teaching video and the adjustment requirement index of the high-frequency keyword set of the video text content, the present invention determines whether there is a need to adjust the storage location of the specified teaching video, making the storage structure of the target education platform more reasonable and orderly, further improving the efficiency of users retrieving videos, and optimizing the resource allocation of the target education platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 It is a schematic diagram of the module connection of the present invention.

[0020] Figure 2 It is a schematic diagram of the logic for analyzing the current integrity of the playback function of the specified teaching video of the present invention.

[0021] Figure 3 It is a schematic diagram of the logic for analyzing the current teaching competitiveness index of the specified teaching video of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0023] Please refer to Figure 1As shown in the figure, the present invention provides an educational information management and maintenance system based on an educational platform, including: a source data extraction module, a teaching value judgment module, a video storage adjustment module, a video clearing module, and a cloud database.

[0024] The source data extraction module is connected to the teaching value judgment module, the teaching value judgment module is respectively connected to the video storage adjustment module and the video clearing module, and the cloud database is respectively connected to the teaching value judgment module and the video storage adjustment module.

[0025] The source data extraction module is used to extract the specified teaching video source data on the regular data maintenance day of the target educational platform, including the author, teaching subject, teaching grade stage, video title name, reference teaching material version, release time, and high-frequency keyword set of the video text content.

[0026] It should be noted that the high-frequency keyword set of the above video text content contains each keyword whose repeated occurrence times in the video text content are greater than or equal to the preset repeated occurrence times. The data source of the preset repeated occurrence times is: counting the repeated occurrence times of each keyword extracted from the video text content of the specified teaching video, calculating the average repeated occurrence times and the standard deviation of the repeated occurrence times of the keywords extracted from the video text content of the specified teaching video, performing a difference operation on the average repeated occurrence times and the standard deviation of the repeated occurrence times, and performing a ceiling processing on the calculated difference. The calculated difference after the ceiling processing is used as the preset repeated occurrence times. In particular, the average repeated occurrence times and the standard deviation of the repeated occurrence times of the keywords are respectively calculated using the mean calculation formula and the standard deviation calculation formula, which will not be elaborated here.

[0027] The teaching value judgment module is used to perform a playback test on the specified teaching video, and analyze the current playback function integrity, reference material timeliness, and teaching competitiveness index of the specified teaching video in combination with the source data of the specified teaching video, so as to judge whether the specified teaching video currently has relative teaching value. If not, the video clearing module is executed; if so, the video storage adjustment module is executed.

[0028] Please refer to Figure 2 As shown in the figure, specifically, analyzing the current playback function integrity of the specified teaching video includes: performing data verification processing on the specified teaching video during the playback test of the specified teaching video to obtain its verification hash value, and comparing it with the preset verification hash value recorded when the specified teaching video was initially stored. If the comparison is the same, the current data integrity index of the specified teaching video is output as 1; if the comparison is different, the current data integrity index of the specified teaching video is output as 0.

[0029] During the specified teaching video playback test process, perform preset number of plays on the specified teaching video, collect the complete play count of the specified teaching video, the interruption count for each play process, and the interruption duration for each interruption, and calculate the playback success rate of the specified teaching video and the playback interruption rate , and output the current playback integrity index of the specified teaching video accordingly.

[0030] It should be noted that the above playback success rate is the ratio of the complete play count of the specified teaching video to the preset number of plays, and the playback interruption rate is the calculated average of the cumulative interruption duration ratio for each play process, where the cumulative interruption duration ratio for each play process specifically refers to the ratio of the cumulative interruption duration for each play process to the total duration of a single play of the specified teaching video.

[0031] Multiply the current data integrity index and the playback integrity index of the specified teaching video to obtain the current playback functionality integrity of the specified teaching video.

[0032] Specifically, the calculation and analysis method of the current playback integrity index of the specified teaching video includes:

[0033] Compare the playback success rate with the preset reasonable playback success rate threshold. If the playback success rate exceeds the preset reasonable playback success rate threshold, take the difference between the playback success rate and the preset reasonable playback success rate threshold; otherwise, take 0.

[0034] Compare the preset permitted playback interruption rate threshold with the actual playback interruption rate. If the actual playback interruption rate is less than the preset permitted playback interruption rate threshold, take the difference between the preset permitted playback interruption rate threshold and the actual playback interruption rate for the exceeded part; otherwise, take 0.

[0035] Add the above two obtained values as the independent variable of the natural exponential function, and take the difference between the calculated value and 1 as the final playback integrity index.

[0036] Specifically, analyzing the current timeliness degree of the reference materials of the specified teaching video includes: Retrieving whether the version of the reference teaching materials of the specified teaching video belongs to the currently authorized and trusted teaching materials version of the target education platform. If not, set the current timeliness degree of the reference materials of the specified teaching video to , if so, further retrieve whether there are updated key points corresponding to the content of the specified teaching video within the time span from the release time of the specified teaching video to the current time for its reference teaching materials version. If there are, set the current timeliness degree of the reference materials of the specified teaching video to , if not, set the current timeliness degree of the reference materials of the specified teaching video to , where .

[0037] Please refer to Figure 3 As shown, specifically, the analysis specifies the current teaching competitiveness index of the teaching video, including: extracting other teaching videos within the target education platform that have the same teaching subject and the same reference teaching material version as the specified teaching video, denoted as each comparison teaching video, comparing the video title names in the source data of each comparison teaching video with the video title name of the specified teaching video to obtain the theme similarity between each comparison teaching video and the specified teaching video, and comparing the high-frequency keyword sets of the video text content in the source data of each comparison teaching video with the high-frequency keyword set of the video text content of the specified teaching video to obtain the content coverage of each comparison teaching video and the specified teaching video.

[0038] It should be noted that the above-mentioned theme similarity is mainly obtained by extracting keywords from the video title name to obtain the keyword set extracted from the video title name, retrieving the number of keywords with similar or the same semantics in the keyword set extracted from the video title names of each comparison teaching video and the specified teaching video, and taking the ratio of the number of keywords with similar or the same semantics to the number of keywords in the keyword set extracted from the video title name of the specified teaching video as the theme similarity between each comparison teaching video and the specified teaching video.

[0039] The above-mentioned content coverage is mainly obtained by retrieving the number of keywords with similar or the same semantics in the high-frequency keyword sets of the video text content of each comparison teaching video and the specified teaching video, and taking the ratio of the number of keywords with similar or the same semantics to the number of keywords in the high-frequency keyword set of the video text content of the specified teaching video as the content coverage of each comparison teaching video and the specified teaching video.

[0040] It should be especially noted that the retrieval process of the number of keywords with similar or the same semantics in the above-mentioned keyword set is obtained based on the semantic analysis tools configured in the system, such as Lancsbox, Gensim, etc.

[0041] Combining the theme similarity and the content coverage, screening each comparison teaching video with a high degree of redundancy possibility with the specified teaching video and counting its quantity .

[0042] It should be noted that each of the above comparison teaching videos with a high degree of redundancy possibility with the specified teaching video satisfies the conditions that the theme similarity is greater than the preset theme similarity compliance threshold and the content coverage is greater than the preset content coverage compliance threshold, where the preset theme similarity compliance threshold and the preset content coverage compliance threshold are determined by the system developers through experimental test analysis using the experimental combinations of each known teaching video with redundancy associations.

[0043] Specifically, analyzing the current teaching competitiveness index of the specified teaching video further includes: collecting the learning interaction data of the specified teaching video on the target education platform, including the viewing behavior indicators, interaction behavior indicators, and quiz behavior indicators of each participating interactive student user, accumulating the products of the viewing behavior indicators, interaction behavior indicators, and quiz behavior indicators and their corresponding preset weights respectively to obtain the comprehensive evaluation behavior indicators of each participating interactive student user of the specified teaching video, and further obtaining the teaching effectiveness indicator of the specified teaching video through mean calculation.

[0044] It should be noted that the specific analysis process of the viewing behavior indicators, interaction behavior indicators, and quiz behavior indicators of each participating interactive student user of the above-specified teaching video is as follows: collecting the cumulative viewing duration and the proportion of traversed video frames of each participating interactive student user for the specified teaching video, calculating the ratio of the cumulative viewing duration to the total duration of a single play of the specified teaching video, and further multiplying it by the proportion of traversed video frames to obtain the viewing behavior indicators of each participating interactive student user of the specified teaching video.

[0045] Collecting the like status indicators of each participating interactive student user for the specified teaching video, with specific values of 1 or 0, where 1 indicates liked and 0 indicates not liked, and taking the like status indicator as the interaction behavior indicator.

[0046] Collecting the scores of the after-class quizzes of each participating interactive student user for the specified teaching video, and taking the ratio of the score to the full score value of the after-class quiz of the specified teaching video as the quiz behavior indicator.

[0047] Similarly, collecting the learning interaction data of each comparison teaching video with a high degree of redundancy possibility with the specified teaching video on the target education platform, analyzing the teaching effectiveness indicators of each comparison teaching video with a high degree of redundancy possibility with the specified teaching video, recording each comparison teaching video with a teaching effectiveness indicator greater than or equal to that of the specified teaching video as each alternative teaching video, and counting the number of alternative teaching videos , and then from the formula analyzing the current teaching competitiveness index of the specified teaching video, where is the total number of comparison teaching videos.

[0048] Specifically, the judgment of whether the specified teaching video currently has relative teaching value includes: extracting the preset compliance thresholds corresponding to the playback function integrity, reference material timeliness, and teaching competitiveness index of the teaching videos with relative teaching value stored in the cloud database. If any one of the current playback function integrity, reference material timeliness, and teaching competitiveness index of the specified teaching video is less than its corresponding preset compliance threshold, it is determined that the specified teaching video currently does not have relative teaching value. On the contrary, if the current playback function integrity, reference material timeliness, and teaching competitiveness index of the specified teaching video are all greater than or equal to their corresponding preset compliance thresholds, it is determined that the specified teaching video currently has relative teaching value.

[0049] By analyzing the current playback function integrity, reference material timeliness, and teaching competitiveness index of the specified teaching video, the embodiment of the present invention accurately judges whether the specified teaching video currently has relative teaching value, and uses this as the basis for video clearing, which helps the target education platform to timely identify and clear teaching videos with low teaching value or outdated ones, thereby optimizing the management and allocation of educational resources.

[0050] The video storage adjustment module is used to extract each storage location allocated for the specified teaching video by the target education platform according to the hierarchical label storage method, and judge whether there is a need to adjust the storage location of the specified teaching video. If it is judged that there is a need, the corresponding adjustment operation is executed.

[0051] Specifically, the hierarchical label storage method specifically includes: using the teaching subject of the teaching video as the first-level label, the teaching grade stage as the second-level label, extracting the keyword set from the video title name as the third-level label, and the high-frequency keyword set of the video text content as the fourth-level label, and randomly matching according to the label order to obtain each hierarchical label group of the teaching video. The hierarchical label group corresponds to the storage sub-library of the target teaching platform, and thus each storage location of the teaching video is allocated.

[0052] For each storage location allocated for the specified teaching video by the target education platform in the embodiment of the present invention according to the hierarchical label storage method, the storage location of the teaching video is accurately positioned by virtue of the hierarchical label, which not only realizes efficient retrieval but also provides a basis for the subsequent execution of the storage location adjustment operation.

[0053] Specifically, the judgment of whether there is a need to adjust the storage location of the specified teaching video includes: obtaining the current grades of each participating interactive student user of the specified teaching video through the user registration information of the target education platform, counting the proportion of the number of participating interactive student users in each grade outside the teaching grade stage of the specified teaching video, screening each grade with a proportion of the number of participating interactive student users greater than the preset value as each potential adaptation grade, extracting the knowledge graph formulated for the teaching subject corresponding to the specified teaching video from the knowledge graph formulated for each teaching subject of the target education platform stored in the cloud database and retrieving it to obtain the content correlation degree between each potential adaptation grade and the specified teaching video.

[0054] Extract the comprehensive evaluation behavior indicators of each potential adaptation grade corresponding to each participating interactive student user of the specified teaching video, and obtain the depth of interaction feedback between each potential adaptation grade and the specified teaching video through mean calculation.

[0055] Integrate the content correlation degree between each potential adaptation grade and the specified teaching video and the depth of interaction feedback , For the numbering of each potential adaptation grade, , from the formula Analyze the adjustment demand index of the teaching grade stage of the specified teaching video, where is the th adjustment demand factor between the potential adaptation grade and the specified teaching video, , are the preset reference adjustment demand factor, reference interaction feedback depth, and reference content correlation degree respectively.

[0056] Specifically, the judgment of whether there is a need to adjust the storage location of the specified teaching video also includes: according to the retrieval log of the target education platform, collecting each keyword used in each user retrieval behavior that causes the specified teaching video to appear in the search results during the time span from the release time of the specified teaching video to the current time, and further screening them into each direct keyword and each indirect keyword according to the rule of whether they belong to the high-frequency keyword set of the video text content of the specified teaching video, calculating the proportion of the number of user retrieval behaviors in which the direct keyword and the indirect keyword cause the specified teaching video to appear in the search results, and respectively recording them as , from the formula Analyze the year-on-year conversion rate of the high-frequency keyword set of the video text content of the specified teaching video, where is a preset constant to prevent the denominator from being 0.

[0057] Record each keyword in the high-frequency keyword set of the video text content of the specified teaching video as each specified keyword. According to the retrieval logs of the target education platform, collect the usage frequencies of each specified keyword and each keyword with a semantically similar relationship within the time span from the release time of the specified teaching video to the current time. Calculate the average usage frequency of the keywords with a semantically similar relationship to each specified keyword, and record it as the reference usage frequency of each specified keyword. Conduct a ratio analysis on the usage frequency of each specified keyword within the time span from the release time of the specified teaching video to the current time and its reference usage frequency to obtain the year-on-year usage rate of each specified keyword within the time span from the release time of the specified teaching video to the current time. Calculate the average value to obtain the year-on-year usage rate of the high-frequency keyword set of the video text content of the specified teaching video 。

[0058] Integrate the year-on-year conversion rate and the year-on-year usage rate, and use the product of the difference between the year-on-year conversion rate of the high-frequency keyword set of the video text content of the specified teaching video and 1 and the difference between the year-on-year usage rate of the high-frequency keyword set of the video text content of the teaching video and 1 as the adjustment requirement index of the high-frequency keyword set of the video text content of the specified teaching video

[0059] Extract the preset trigger thresholds of the adjustment requirement index for the teaching grade stage and the high-frequency keyword set of the video text content corresponding to the adjustment requirement for the storage location of the teaching video stored in the cloud database. If both the teaching grade stage of the specified teaching video and the adjustment requirement index of the high-frequency keyword set of the video text content are less than their respective corresponding preset trigger thresholds, it is determined that there is no adjustment requirement for the storage location of the specified teaching video; otherwise, it is determined that there is

[0060] It should be noted that if it is determined that there is an adjustment requirement for the storage location of the specified teaching video, the corresponding adjustment operation execution process is as follows: If the adjustment requirement index of the teaching grade stage of the specified teaching video is greater than or equal to its corresponding preset trigger threshold, it means that there is an adjustment requirement for the secondary label of the specified teaching video. Extract the adjustment requirement factors of each potential adapted grade and the specified teaching video, and include each potential adapted grade that meets the conditions into the teaching grade stage of the specified teaching video

[0061] If the adjustment requirement index of the high-frequency keyword set of the video text content of the specified teaching video is greater than or equal to its corresponding preset trigger threshold, it means that there is an adjustment requirement for the four-level label of the specified teaching video. If ..., then include each indirect keyword whose ranking position in the proportion of the number of user retrieval behaviors that cause the specified teaching video to appear in the search results is before the preset quantity into the high-frequency keyword set of the video text content of the specified teaching video. If , keywords with a year-on-year usage rate of less than 1 within the time span from the specified release time of the teaching video to the current time are replaced with semantically similar keywords, and the keywords participating in the replacement are the keywords with the highest usage frequency within the time span from the specified release time of the teaching video to the current time.

[0062] The video clearing module is used to clear the specified teaching video from the target education platform.

[0063] In the embodiment of the present invention, by analyzing the teaching grade stage of the specified teaching video and the adjustment requirement index of the high-frequency keyword set of the video text content, it is judged whether there is an adjustment requirement for the storage location of the specified teaching video, so that the storage structure of the target education platform is more reasonable and orderly, and the efficiency of users retrieving videos is further improved while optimizing the resource allocation of the target education platform.

[0064] The cloud database is used to store the preset compliance thresholds corresponding to the playback function integrity, reference material timeliness, and teaching competitiveness index of the teaching videos with relative teaching value in the target education platform, store the knowledge graphs formulated for each teaching subject in the target education platform, and store the preset trigger thresholds of the adjustment requirement index corresponding to the teaching grade stage and the high-frequency keyword set of the video text content when there is an adjustment requirement for the storage location of the teaching videos in the target education platform.

[0065] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to obtain a formula that is closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0066] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0067] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0068] In addition, in each embodiment of the present application, the functional modules can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

[0069] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the said claims.

[0070] Finally, the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An educational information management and maintenance system based on an educational platform, characterized in that, The system includes: A source data extraction module, which is used to extract the specified teaching video source data on the regular data maintenance day of the target education platform, including the author, teaching subject, teaching grade stage, video title name, reference teaching material version, release time, and high-frequency keyword set of the video text content; A teaching value judgment module, which is used to conduct a playback test on the specified teaching video, and combine the source data of the specified teaching video to analyze the current playback function integrity, reference material timeliness, and teaching competitiveness index of the specified teaching video, so as to judge whether the specified teaching video currently has relative teaching value. If not, the video deletion module is executed; if so, the video storage adjustment module is executed; A video storage adjustment module, which is used to extract each storage location allocated for the specified teaching video by the target education platform according to the hierarchical label storage method, and judge whether there is a need to adjust the storage location of the specified teaching video. If it is judged that there is a need, the corresponding adjustment operation is executed; A video deletion module, which is used to delete the specified teaching video from the target education platform.

2. The educational information management and maintenance system based on an educational platform according to claim 1, wherein: The analysis of the current playback function integrity of the specified teaching video includes: performing data verification processing on the specified teaching video during the playback test of the specified teaching video to obtain its verification hash value, comparing it with the preset verification hash value recorded when the specified teaching video was initially stored, and outputting the current data integrity index of the specified teaching video; Performing a preset number of playback processes on the specified teaching video during the playback test of the specified teaching video, collecting the complete playback times of the specified teaching video, the interruption times of each playback process, and the interruption duration of each time, calculating the playback success rate and playback interruption rate of the specified teaching video, and outputting the current playback integrity index of the specified teaching video; Multiplying the current data integrity index and playback integrity index of the specified teaching video to obtain the current playback function integrity of the specified teaching video.

3. An educational information management and maintenance system based on an educational platform according to claim 2, characterized in that: The calculation and analysis method of the current playback integrity index of the specified teaching video includes: Comparing the playback success rate with the preset reasonable playback success rate threshold. If the playback success rate exceeds the preset reasonable playback success rate threshold, take the difference between the playback success rate and the preset reasonable playback success rate threshold; otherwise, take 0; Comparing the preset permitted playback interruption rate threshold with the actual playback interruption rate. If the actual playback interruption rate is less than the preset permitted playback interruption rate threshold, take the difference between the preset permitted playback interruption rate threshold and the actual playback interruption rate for the exceeded part; otherwise, take 0; Adding the above two obtained values as the independent variable of the natural exponential function, and taking the difference between the calculated value and 1 as the final playback integrity index.

4. An education information management and maintenance system based on an education platform according to claim 1, characterized in that: The above analyzes the timeliness degree of the reference materials of the specified teaching video, including: retrieving whether the version of the reference teaching materials of the specified teaching video belongs to the currently authorized and trusted teaching materials version of the target education platform. If not, set the timeliness degree of the reference materials of the specified teaching video currently as , if so, further retrieve whether there is updated key content corresponding to the content of the specified teaching video within the time span from the release time of the specified teaching video to the current time. If there is, set the timeliness degree of the reference materials of the specified teaching video currently as , if not, set the timeliness degree of the reference materials of the specified teaching video currently as , where .

5. An educational information management and maintenance system based on an educational platform according to claim 1, characterized in that: Analyzing the current teaching competitiveness index of the specified teaching video includes: extracting other teaching videos within the target educational platform that have the same teaching subject and the same version of the reference teaching materials as the specified teaching video, and recording them as each comparison teaching video. Comparing the video title names in the source data of each comparison teaching video with the video title name of the specified teaching video to obtain the theme similarity between each comparison teaching video and the specified teaching video. Comparing the high-frequency keyword sets of the video text content in the source data of each comparison teaching video with the high-frequency keyword set of the video text content of the specified teaching video to obtain the content coverage of each comparison teaching video and the specified teaching video; Based on the comprehensive theme similarity and content coverage, screen out each comparison teaching video that has a high degree of redundancy possibility with the specified teaching video and count their numbers.

6. An educational information management and maintenance system based on an educational platform according to claim 5, characterized in that: Analyzing the current teaching competitiveness index of the specified teaching video also includes: collecting the learning interaction data of the specified teaching video on the target educational platform, including the viewing behavior indicators, interaction behavior indicators, and test behavior indicators of each participating interactive student user. Accumulating the products of the viewing behavior indicators, interaction behavior indicators, and test behavior indicators and their corresponding preset weights respectively to obtain the comprehensive evaluation behavior indicators of each participating interactive student user of the specified teaching video, and further obtaining the teaching effectiveness index of the specified teaching video through mean calculation; Similarly, collect the learning interaction data of each comparison teaching video that has a high degree of redundancy possibility with the specified teaching video on the target educational platform, analyze the teaching effectiveness index of each comparison teaching video that has a high degree of redundancy possibility with the specified teaching video, and record each comparison teaching video whose teaching effectiveness index is greater than or equal to the teaching effectiveness index of the specified teaching video as each replaceable teaching video, count the number of replaceable teaching videos, and then analyze the current teaching competitiveness index of the specified teaching video based on the number of each comparison teaching video with a high degree of redundancy possibility of the specified teaching video, the number of replaceable teaching videos, and the total number of comparison teaching videos and using index fusion calculation.

7. An education information management and maintenance system based on an education platform according to claim 1, characterized in that: Judging whether the specified teaching video currently has relative teaching value includes: extracting the preset compliance thresholds corresponding to the playback function integrity, reference material timeliness, and teaching competitiveness index of the teaching videos with relative teaching value in the target educational platform stored in the cloud database. If any one of the current playback function integrity, reference material timeliness, and teaching competitiveness index of the specified teaching video is less than its corresponding preset compliance threshold, it is judged that the specified teaching video currently does not have relative teaching value. On the contrary, if the current playback function integrity, reference material timeliness, and teaching competitiveness index of the specified teaching video are all greater than or equal to their corresponding preset compliance thresholds, it is judged that the specified teaching video currently has relative teaching value.

8. An educational information management and maintenance system based on an educational platform according to claim 1, characterized in that: The specific method of hierarchical label storage includes: using the teaching subject of the teaching video as the first-level label, the teaching grade stage as the second-level label, extracting the keyword set from the video title name as the third-level label, and the high-frequency keyword set of the video text content as the fourth-level label. Randomly match them according to the label order to obtain each hierarchical label group of the teaching video, and the storage sub-library corresponding to the hierarchical label group on the target teaching platform, so as to allocate the storage locations of each teaching video.

9. An educational information management and maintenance system based on an educational platform according to claim 6, characterized in that: Judging whether there is a need to adjust the storage location of a specified teaching video includes: obtaining the current grades of each participating interactive student user of the specified teaching video through the user registration information of the target education platform, counting the proportion of the number of participating interactive student users in each grade outside the teaching grade stage of the specified teaching video, screening out the grades with the proportion of the number of participating interactive student users greater than the preset value as potential adaptation grades, and extracting and retrieving the knowledge graph formulated for the teaching subject corresponding to the specified teaching video according to the knowledge graph formulated for each teaching subject of the target education platform stored in the cloud database, so as to obtain the content correlation degree between each potential adaptation grade and the specified teaching video; Extract the comprehensive evaluation behavior indicators of each participating interactive student user corresponding to each potential adaptation grade of the specified teaching video, and obtain the interactive feedback depth between each potential adaptation grade and the specified teaching video through average calculation; Comprehensively analyze the content correlation degree and interactive feedback depth between each potential adaptation grade and the specified teaching video, and analyze the adjustment demand index of the teaching grade stage of the specified teaching video.

10. An educational information management and maintenance system based on an educational platform according to claim 9, characterized in that: Judging whether there is a need to adjust the storage location of a specified teaching video also includes: according to the retrieval log of the target education platform, collecting each keyword used in each user retrieval behavior that causes the specified teaching video to appear in the search results during the time span from the release time of the specified teaching video to the current time, and further screening them into direct keywords and indirect keywords according to the rule of whether they belong to the high-frequency keyword set of the video text content of the specified teaching video, calculating the proportion of the number of user retrieval behaviors in which the direct keywords and indirect keywords cause the specified teaching video to appear in the search results, and analyzing the year-on-year conversion rate of the high-frequency keyword set of the video text content of the specified teaching video; Mark each keyword in the high-frequency keyword set of the video text content of the specified teaching video as each specified keyword, and according to the retrieval log of the target education platform, collect the usage frequencies of each specified keyword and the keywords with semantic similarity relationships during the time span from the release time of the specified teaching video to the current time, and analyze the year-on-year usage rate of the high-frequency keyword set of the video text content of the specified teaching video; Comprehensively analyze the year-on-year conversion rate and year-on-year usage rate, and analyze the adjustment demand index of the high-frequency keyword set of the video text content of the specified teaching video; Extract the preset trigger threshold of the adjustment demand index for the teaching grade stage and the high-frequency keyword set of the video text content corresponding to the adjustment requirement for the storage location of the target education platform teaching video stored in the cloud database. If the adjustment demand indices of the teaching grade stage of the specified teaching video and the high-frequency keyword set of the video text content are both less than their respective preset trigger thresholds, it is determined that there is no adjustment requirement for the storage location of the specified teaching video; otherwise, it is determined that there is an adjustment requirement.

Images