Service platform integrating multi-platform digital course resources

Abstract

The invention discloses a service platform for integrating multi-platform digital course resources, which belongs to the technical field of resource integration and comprises a resource interaction simulation module, a trust evaluation model construction module, a resource retrieval module, a retrieval resource optimization module and a resource display module. According to the method, a user is simulated to search required mathematical course resources on a service platform so as to simulate digital course resource interaction between the service platform and a resource interaction platform, digital course resources generated by interaction are obtained, and a trust evaluation model between the service platform and the resource interaction platform is constructed based on the digital course resources; when a user searches for digital course resources on the service platform, the digital course resources on the service platform are searched preferentially, then the digital course resources on the resource interaction platform are searched based on the trust evaluation model, and the digital course resources are displayed after integration. The problem that the response speed of a service platform is low due to the fact that many digital course resources are gathered on the service platform can be avoided while the multi-platform digital course resources are integrated.

Description

Technical Field

[0001] The present invention belongs to the technical field of resource integration, and in particular relates to a service platform integrating multi-platform digital course resources. Background Art

[0002] With the rapid development of Internet technology and the continuous advancement of educational informatization, the application of digital course resources in education and teaching is becoming more and more extensive.

[0003] However, the current digital course resources among various platforms are relatively scattered, lacking a unified management and integration mechanism, which has brought many inconveniences to teachers and students in obtaining and using teaching resources.

[0004] In view of this, a service platform integrating multi-platform digital course resources is designed to solve the above problems. Summary of the invention

[0005] To solve the problems raised in the above background technology, the present invention provides a service platform integrating digital course resources from multiple platforms, which has the characteristics of being able to integrate digital course resources from multiple platforms while avoiding the problem of slow response speed of the service platform caused by too many digital course resources being gathered on the service platform.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solution: a service platform integrating multi-platform digital course resources, comprising:

[0007] The resource interaction simulation module simulates the user searching for digital course resources on the service platform to simulate the digital course resource interaction between the service platform and the resource interaction platform;

[0008] The trust evaluation model building module builds a trust evaluation model between the service platform and the resource interaction platform based on the digital course resources generated by the interaction between the service platform and the resource interaction platform;

[0009] Resource search module: users search for the required digital course resources on the service platform, set the focus during the search, and search for digital course resources on the service platform first, and then search for digital course resources on the resource interaction platform based on the focus through the trust evaluation model;

[0010] The retrieval resource optimization module integrates the retrieved digital course resources that meet the needs of users, determines the duplication among all digital course resources, and removes the mathematics course resources with high duplication in order to optimize the digital course resources;

[0011] The resource display module displays optimized digital course resources for search users to view.

[0012] Furthermore, the trust evaluation model in the trust evaluation model construction module includes an integrated time trust unit, an integrated content trust unit and an integrated quality trust unit, wherein:

[0013] The objective function of the integrated time trust unit is:

[0014] U1=α1(T BR -T BE )+α2(T FR -T FE )

[0015] Where: α1 and α2 represent weight factors, T BR and T FR Indicated as the actual integration start and end time, T BE and T FE Expressed as the expected integration start and end times;

[0016] The objective function of the integrated content trust unit is:

[0017]

[0018] Where: n represents all integrated digital course resources, D i Denotes the evaluation dataset of the integrated i-th digital course resource, C i Indicates whether the resource interaction platform can provide digital course resources. If it can, then C i =1, otherwise, C i =0;

[0019] The objective function of the integrated quality trust unit is:

[0020] U3=M R -M E

[0021] Where: M R It is expressed as the actual quality of digital course resources, M E expressed as the desired quality of digital course resources;

[0022] The objective function of the trust evaluation model is:

[0023] U=β1U1+β2U2+β3U3

[0024] Where: β1, β2 and β3 are weight factors.

[0025] Furthermore, the numerical value of each weight factor β1, β2 and β3 is preset to three values, including a maximum value, a middle value and a minimum value, and the selection of the numerical value changes based on the change of the emphasis set in the resource retrieval module.

[0026] Furthermore, the specific steps of determining the duplication among all digital course resources in the retrieval resource optimization module include:

[0027] Comparing the repetitiveness between two digital course resources in sequence until all digital course resources are compared, wherein the specific steps of comparing the repetitiveness between two digital course resources in sequence include:

[0028] Two continuous video frame sequences are extracted from two digital course resources respectively;

[0029] Extract two key frame sequences respectively from two consecutive video frame sequences;

[0030] quantizing the feature descriptors of two key-frame sequences into two vocabularies;

[0031] Count the frequency of occurrence of each descriptor in the two vocabularies to form a fixed-length feature vector x = (x1, x2, ..., x n ) and y=(y1,y2,…,y n );

[0032] Calculate the distance between two eigenvectors. The smaller the value, the higher the repeatability. The expression is:

[0033]

[0034] Furthermore, the removal of mathematics course resources with high duplication of digital course resources in the retrieval resource optimization module is based on the comparison between the characteristic vector distance value between two digital course resources and a preset threshold value to obtain the removal items of the digital course resources. When the characteristic vector distance value exceeds the preset threshold value, one of the two digital course resources is retained, otherwise, both digital course resources are retained.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. The present invention first simulates a user searching for required mathematics course resources on a service platform to simulate the interaction of digital course resources between the service platform and the resource interaction platform, obtains the digital course resources generated by the interaction, and then builds a trust evaluation model between the service platform and the resource interaction platform based on the digital course resources generated by the interaction. Later, when the user searches for digital course resources on the service platform, the digital course resources on the service platform are searched first, and then the digital course resources on the resource interaction platform are searched based on the trust evaluation model. The digital course resources are displayed after integration. Compared with the prior art, it can integrate digital course resources from multiple platforms while avoiding the problem of slow response speed of the service platform caused by a large number of digital course resources being concentrated on the service platform.

[0037] 2. The present invention integrates multi-platform digital course resources based on a trust evaluation model. The trust evaluation model includes an integration time trust unit, an integration content trust unit and an integration quality trust unit, which can ensure the integration speed, content and quality of the integrated digital course resources. At the same time, the weight factor of the trust evaluation model changes with the focus set by the user, which can make the integrated digital course resources more in line with user needs.

[0038] 3. After integrating digital course resources from multiple platforms, the present invention determines the repeatability of the integrated digital course resources based on the Euclidean distance, removes digital course resources with high repeatability, avoids the repeatability of the integrated digital course resources, and ensures the effectiveness of the integrated and displayed digital course resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A framework diagram of a service platform for integrating multi-platform digital course resources of the present invention;

[0040] In the figure: 1. Resource interaction simulation module; 2. Trust evaluation model construction module; 3. Resource retrieval module; 4. Retrieval resource optimization module; 5. Resource display module. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] See also Figure 1 The present invention provides the following technical solution: a service platform integrating multi-platform digital course resources, comprising:

[0043] The resource interaction simulation module 1 simulates a user searching for digital course resources on the service platform to simulate the digital course resource interaction between the service platform and the resource interaction platform;

[0044] A resource interaction license agreement has been signed between the service platform and the resource interaction platform. At the same time, a resource interaction license agreement has also been signed between the resource interaction platform and the digital course resource uploader to avoid the problem of unclear ownership of digital course resource copyrights.

[0045] The number of resource interaction platforms is not fixed. All platforms that sign a resource interaction agreement can become resource interaction platforms with the service platform.

[0046] As a user, the tester searches for the required digital course resources on the service platform, wherein the required digital course resources searched need to be constantly changed to generate enough digital course resources reduced by the service platform and the resource interaction platform;

[0047] Trust evaluation model construction module 2, based on the digital course resources generated by the interaction between the service platform and the resource interaction platform, constructs a trust evaluation model between the service platform and the resource interaction platform;

[0048] The trust evaluation model is rebuilt as the resource interaction platforms of the service platform increase or decrease. That is, every time a resource interaction platform is added to the service platform, it needs to be re-simulated to obtain the digital course resources generated by the interaction between the service platform and the resource interaction platform to rebuild the trust evaluation model. Every time a resource interaction platform is reduced, the relevant items about the resource interaction platform in the trust evaluation model can be deleted.

[0049] Resource search module 3, users search for the required digital course resources on the service platform, set the focus during the search, and first search for digital course resources on the service platform, and then search for digital course resources on the resource interaction platform based on the focus through the trust evaluation model;

[0050] Emphasis includes fastest speed, most content, and best quality. You can choose one, two, or three, or select and sort them at the same time.

[0051] The search resource optimization module 4 integrates the retrieved digital course resources that meet the needs of the user, determines the duplication among all digital course resources, and removes the mathematics course resources with high duplication of digital course resources to optimize the digital course resources;

[0052] Digital course resources with high repetitiveness require users to spend more time to identify and provide almost no help to users. Therefore, digital course resources with high repetitiveness will reduce users' experience with the service platform and need to be removed.

[0053] The resource display module 5 displays the optimized digital course resources for the searching users to view.

[0054] Specifically, the trust evaluation model in the trust evaluation model construction module 2 includes an integrated time trust unit, an integrated content trust unit and an integrated quality trust unit, wherein:

[0055] The objective function of the integrated time trust unit is:

[0056] U1=α1(T BR -T BE )+α2(T FR -T FE )

[0057] Where: α1 and α2 represent weight factors, T BR and T FR Indicated as the actual integration start and end time, T BE and T FE Expressed as the expected integration start and end times;

[0058] The objective function of the integrated content trust unit is:

[0059]

[0060] Where: n represents all integrated digital course resources, D i Denotes the evaluation dataset of the integrated i-th digital course resource, C i Indicates whether the resource interaction platform can provide digital course resources. If it can, then C i =1, otherwise, C i =0;

[0061] The objective function of the integrated quality trust unit is:

[0062] U3=M R -M E

[0063] Where: M R It is expressed as the actual quality of digital course resources, M E expressed as the desired quality of digital course resources;

[0064] The objective function of the trust evaluation model is:

[0065] U=β1U1+β2U2+β3U3

[0066] Where: β1, β2 and β3 are weight factors.

[0067] Specifically, the numerical value of each weight factor β1, β2 and β3 is preset to three values, including a maximum value, a middle value and a minimum value, and the selection of the numerical value changes based on the change of the emphasis set in the resource retrieval module 3.

[0068] Specifically, the specific steps of determining the duplication among all digital course resources in the search resource optimization module 4 include:

[0069] Comparing the repetitiveness between two digital course resources in sequence until all digital course resources are compared, wherein the specific steps of comparing the repetitiveness between two digital course resources in sequence include:

[0070] Two continuous video frame sequences are extracted from two digital course resources respectively;

[0071] Extracting continuous video frame sequences from digital course resources is based on video parsing, which is an existing technology;

[0072] Extract two key frame sequences respectively from two consecutive video frame sequences;

[0073] Extracting key frame sequences from continuous video frame sequences is based on existing technologies, including: a shot boundary-based method, a frame image average information-based method, and a motion analysis-based method;

[0074] quantizing the feature descriptors of two key-frame sequences into two vocabularies;

[0075] The specific steps of quantizing the key frame sequence feature descriptors into a vocabulary include:

[0076] The corner points or edge points of the key frame are used as feature points, and the area around the feature points is divided into 4×4 sub-areas;

[0077] Calculate the gradient direction histogram of each sub-region;

[0078] Concatenate the gradient direction histograms of all sub-regions to form a 128-dimensional feature descriptor vector, i.e., the feature descriptor;

[0079] Map feature descriptors to vocabulary through hash tables, i.e. quantize them into vocabulary;

[0080] Count the frequency of occurrence of each descriptor in the two vocabularies to form a fixed-length feature vector x = (x1, x2, ..., x n ) and y=(y1,y2,…,y n );

[0081] Calculate the distance between two eigenvectors. The smaller the value, the higher the repeatability. The expression is:

[0082]

[0083] Specifically, the removal of mathematics course resources with high duplication in the retrieval resource optimization module 4 is based on the comparison between the characteristic vector distance value between two digital course resources and the preset threshold value to obtain the removal items of the digital course resources. When the characteristic vector distance value exceeds the preset threshold value, one of the two digital course resources is retained, otherwise, both digital course resources are retained.

[0084] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A service platform integrating multi-platform digital course resources, characterized in that: include: A resource interaction simulation module (1) simulates a user searching for digital course resources on the service platform to simulate the digital course resource interaction between the service platform and the resource interaction platform; A trust evaluation model building module (2) builds a trust evaluation model between the service platform and the resource interaction platform based on the digital course resources generated by the interaction between the service platform and the resource interaction platform; Resource search module (3), the user searches for the required digital course resources on the service platform, sets the focus during the search, and first searches for digital course resources on the service platform, and then searches for digital course resources on the resource interaction platform based on the focus through the trust evaluation model; A search resource optimization module (4) integrates the retrieved digital course resources that meet the needs of the user, determines the duplication among all digital course resources, and removes the mathematics course resources with high duplication of digital course resources to optimize the digital course resources; The resource display module (5) displays the optimized digital course resources for the searching users to view.

2. A service platform integrating multi-platform digital course resources according to claim 1, characterized in that: The trust evaluation model in the trust evaluation model construction module (2) includes an integrated time trust unit, an integrated content trust unit and an integrated quality trust unit, wherein: The objective function of the integrated time trust unit is: U1=α1(T BR -T BE )+α2(T FR -T FE ) Where: α1 and α2 represent weight factors, T BR and T FR Indicated as the actual integration start and end time, T BE and T FE Expressed as the expected integration start and end times; The objective function of the integrated content trust unit is: Where: n represents all integrated digital course resources, D i Denotes the evaluation dataset of the integrated i-th digital course resource, C i Indicates whether the resource interaction platform can provide digital course resources. If it can, then C i =1, otherwise, C i =0; The objective function of the integrated quality trust unit is: U3=M R -M E Where: M R It is expressed as the actual quality of digital course resources, M E expressed as the desired quality of digital course resources; The objective function of the trust evaluation model is: U=β1U1+β2U2+β3U3 Where: β1, β2 and β3 are weight factors.

3. A service platform integrating multi-platform digital course resources according to claim 2, characterized in that: The numerical value of each weight factor β1, β2 and β3 is preset to three values, including a maximum value, a middle value and a minimum value, and the selection of the numerical value changes based on the change of the emphasis set in the resource search module (3).

4. A service platform integrating multi-platform digital course resources according to claim 1, characterized in that: The specific steps of determining the duplication among all digital course resources in the search resource optimization module (4) include: Comparing the repetitiveness between two digital course resources in sequence until all digital course resources are compared, wherein the specific steps of comparing the repetitiveness between two digital course resources in sequence include: Two continuous video frame sequences are extracted from two digital course resources respectively; Extract two key frame sequences respectively from two consecutive video frame sequences; quantizing the feature descriptors of two key-frame sequences into two vocabularies; Count the frequency of occurrence of each descriptor in the two vocabularies to form a fixed-length feature vector x = (x1, x2, ..., x n ) and y=(y1,y2,…,y n ); Calculate the distance between two eigenvectors. The smaller the value, the higher the repeatability. The expression is:

5. A service platform integrating multi-platform digital course resources according to claim 4, characterized in that: The removal of mathematical course resources with high repetitiveness in the retrieval resource optimization module (4) is based on the comparison between the characteristic vector distance value between two digital course resources and a preset threshold value to obtain the removal items of the digital course resources. When the characteristic vector distance value exceeds the preset threshold value, one of the two digital course resources is retained, otherwise, both digital course resources are retained.

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