Education resource sharing system and method based on cloud platform

Abstract

The invention belongs to the field of educational resource sharing, relates to a data analysis technology, is used for solving the problem that retrieval features of resources cannot be analyzed in the prior art, and particularly relates to an educational resource sharing system and method based on a cloud platform, and the system comprises a retrieval statistics module, a sharing processing module and a sharing evaluation module. The retrieval statistics module, the sharing processing module and the sharing evaluation module are in communication connection in sequence; the retrieval statistical module is used for performing statistical analysis on the educational resource retrieval data of the cloud platform: classifying the educational resources of the cloud platform to obtain a plurality of resource types, generating a statistical period, and marking a statistical data set of the resource types at the end moment of the statistical period; when the retrieval task is executed in the processing period, the processing output sequence is generated in combination with the keyword input by the user and the statistical data set of the corresponding processing type, the processing output sequence is composed of the conventional sub-sequence and the associated sub-sequence, and the retrieval efficiency of the user is improved.

Description

Technical Field

[0001] The present invention belongs to the field of educational resource sharing and relates to data analysis technology, and specifically is an educational resource sharing system and method based on a cloud platform. Background Art

[0002] Educational resource sharing refers to the effective integration and sharing of various educational resources to improve resource utilization efficiency and achieve optimal resource allocation. These educational resources may include but are not limited to course materials, teaching cases, teaching tools, etc. By sharing these resources, educators can obtain more educational knowledge and information, improve teaching quality, and promote educational development.

[0003] The invention patent with announcement number CN116701771B discloses a digital library retrieval and resource sharing system based on cloud computing. The resource sharing system monitors and counts cloud computing network traffic in real time through a network anomaly model and handles network anomaly traffic or attacks. It processes large-scale library archive resource retrieval data through a distributed acceleration algorithm, thereby improving the efficiency of data processing and calculation, weakening the information islanding effect of a single library resource, and reducing the risk of information leakage. However, the resource sharing system cannot analyze the retrieval characteristics of resources. When a user performs multiple searches in succession, it is impossible to output multiple items of information to the user at one time based on the retrieval characteristics, thereby reducing the number of searches and resulting in low retrieval efficiency.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a cloud platform-based educational resource sharing system and method, which is used to solve the problem that the existing technology cannot analyze the retrieval characteristics of resources; The technical problem to be solved by the present invention is: how to provide an educational resource sharing system and method based on a cloud platform that can analyze the retrieval characteristics of resources.

[0006] The purpose of the present invention can be achieved by the following technical solutions: An educational resource sharing system based on a cloud platform comprises a retrieval statistics module, a sharing processing module and a sharing evaluation module, wherein the retrieval statistics module, the sharing processing module and the sharing evaluation module are sequentially connected in communication, and the retrieval statistics module is also connected in communication with the sharing evaluation module; The retrieval statistics module is used to perform statistical analysis on the educational resource retrieval data of the cloud platform: classify the educational resources of the cloud platform to obtain a number of resource types, generate a statistical cycle, and mark the statistical data set of the resource type at the end of the statistical cycle; The sharing processing module is used to process and analyze the sharing needs of the cloud platform: generate a processing cycle, and within the processing cycle, when a user searches for educational resources, retrieve the resource type of the search vocabulary corresponding to the user input keyword and mark it as the processing type, retrieve the statistical data set of the processing type, generate a processing output sequence through the keywords and the statistical data set, and send the processing output sequence to the user's client; The shared evaluation module is used to evaluate and analyze the shared processing data of the cloud platform: at the end of the processing cycle, the conventional optimization data CG, the associated optimization data GL and the bidirectional optimization data SX are obtained and numerical calculations are performed to obtain the optimization coefficient YH of the processing cycle; the optimization coefficient YH is used to determine whether the educational resource sharing processing status within the processing cycle meets the requirements.

[0007] Furthermore, the specific process of marking the statistical data set of resource types includes: within the statistical period, after the user enters the keyword, the keyword is searched to generate a regular resource sequence with a resource quantity of L1, the educational resources that the user finally chooses to download in the regular resource sequence are marked as selected objects, and the serial number of the selected object in the regular resource sequence is marked as the selected value, the keyword corresponding to the resource type when all educational resources are marked as selected objects constitutes a search vocabulary of the resource type, the selected values ​​corresponding to all selected objects of the resource type constitute a selection set, and the selection set is cleaned to obtain a retained value; then, the continuous search behavior performed by the same user within L2 minutes is marked as a continuous process, and the selected objects corresponding to the search behavior other than the first search behavior in the continuous process are marked as associated objects, and the search vocabulary of the resource type, the one-time retained value and the associated object constitute the statistical data set of the resource type.

[0008] Furthermore, the specific process of cleaning the selected set includes: performing variance calculation on the selected set to obtain a selected set value, and comparing the selected set value with a preset selected set threshold: if the selected set value is less than the selected set threshold, the maximum element in the selected set is marked as a one-time retention value of the resource type; if the selected set value is greater than or equal to the selected set threshold, the minimum element and the maximum element in the selected set are eliminated, and then the selected set value is recalculated, and so on, until the selected set value is less than the selected set threshold.

[0009] Furthermore, the process of generating the processing output sequence includes: arranging the associated objects in order of the number of marking times from most to least to obtain an associated sequence; after the user inputs a keyword, searching according to the keyword to generate a regular resource sequence with a resource quantity of L1, and respectively extracting a regular subsequence and an associated subsequence from the regular resource sequence and the associated sequence, the number of educational resources of the regular subsequence is equal to the one-time retention value, and the number of educational resources of the associated subsequence is the difference between L1 and the one-time retention value; generating a processing output sequence with the regular subsequence + the associated subsequence.

[0010] Furthermore, the acquisition process of the conventional optimization data CG, the associated optimization data GL and the bidirectional optimization data SX includes: marking the retrieval process within the processing cycle as the analysis process, marking the analysis process that the user did not choose to download in the conventional subsequence as the conventional optimization process, marking the analysis process that the user did not choose to download in the associated subsequence as the associated optimization process, and marking the analysis process that the user did not choose to download in the processing output sequence as the bidirectional optimization process; at the end of the processing cycle, the marking times of the conventional optimization process, the associated optimization process and the bidirectional optimization process are respectively marked as the conventional optimization data CG, the associated optimization data GL and the bidirectional optimization data SX.

[0011] Furthermore, the specific process of determining whether the educational resource sharing processing status within the processing cycle meets the requirements includes: comparing the optimization coefficient YH of the processing cycle with the preset optimization threshold YHmax: if the optimization coefficient YH is less than the optimization threshold YHmax, then it is determined that the educational resource sharing processing status within the processing cycle meets the requirements; if the optimization coefficient YH is greater than or equal to the optimization threshold YHmax, then it is determined that the educational resource sharing processing status within the processing cycle does not meet the requirements.

[0012] Furthermore, when the educational resource sharing processing status of the processing cycle meets the requirements, a processing continuation signal is generated through the sharing evaluation module and sent to the sharing processing module. The sharing processing module generates a processing cycle after receiving the processing signal, and continues to perform sharing demand processing analysis in a new processing cycle. When the educational resource sharing processing status of the processing cycle does not meet the requirements, a statistical update signal is generated by the shared evaluation module and sent to the retrieval statistics module. After receiving the statistical update signal, the retrieval statistics module regenerates the statistical cycle and updates the statistical data set of the resource type in the new statistical cycle.

[0013] A method for sharing educational resources based on a cloud platform, comprising the following steps: Step 1: Statistically analyze the educational resource retrieval data on the cloud platform and label the statistical data set of resource types; Step 2: Process and analyze the sharing needs of the cloud platform: When users search for educational resources, a processing output sequence is generated based on the once-retained value of the processing type and the associated objects; Step 3: Evaluate and analyze the shared processing data of the cloud platform and obtain the optimization coefficient YH. Use the optimization coefficient YH to determine whether the shared processing status of educational resources within the processing cycle meets the requirements.

[0014] The present invention has the following beneficial effects: The retrieval statistics module can be used to conduct statistical analysis on the educational resource retrieval data of the cloud platform, count the keywords and selected objects of each retrieval behavior within the statistical period, and then generate a statistical data set of resource types based on continuous retrieval behaviors. Feedback on the retrieval characteristics of resource types is provided based on the statistical data set to provide data support for the shared processing and analysis process. The shared processing module can process and analyze the shared needs of the cloud platform. When executing the retrieval task within the processing cycle, the processing output sequence is generated by combining the keywords input by the user and the statistical data set of the corresponding processing type. The processing output sequence consists of a regular subsequence and an associated subsequence, and the number of resources in the regular subsequence is the same as the one-time reservation value, which improves the user's retrieval efficiency. The shared evaluation module can be used to evaluate and analyze the shared processing data of the cloud platform. At the end of the processing cycle, multiple evaluation parameters are collected and comprehensively calculated to obtain the optimization coefficient. The shared processing status within the processing cycle is evaluated using the optimization coefficient, and different feedback signals are generated based on the evaluation results for differentiated processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0017] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0018] Embodiment 1: Figure 1 As shown, a cloud platform-based educational resource sharing system includes a retrieval statistics module, a sharing processing module and a sharing evaluation module. The retrieval statistics module, the sharing processing module and the sharing evaluation module are communicatively connected in sequence, and the retrieval statistics module is also communicatively connected to the sharing evaluation module.

[0019] The retrieval statistics module is used to perform statistical analysis on the educational resource retrieval data of the cloud platform: the educational resources of the cloud platform are classified into several resource types, and a statistical period is generated. Within the statistical period, the user enters keywords and searches according to the keywords to generate a regular resource sequence with a resource quantity of L1. The educational resources that the user finally chooses to download in the regular resource sequence are marked as selected objects, and the serial number of the selected object in the regular resource sequence is marked as the selected value. The keyword corresponding to the resource type when all educational resources are marked as selected objects constitutes a retrieval vocabulary of the resource type, and the selection values ​​corresponding to all selected objects of the resource type constitute a selection set.

[0020] The selected set is cleaned: the variance of the selected set is calculated to obtain the selected concentration value, and the selected concentration value is compared with the preset selected concentration threshold: if the selected concentration value is less than the selected concentration threshold, the maximum element in the selected set is marked as the one-time retention value of the resource type; if the selected concentration value is greater than or equal to the selected concentration threshold, the minimum element and the maximum element in the selected set are eliminated, and then the selected concentration value is recalculated, and so on, until the selected concentration value is less than the selected concentration threshold; then the continuous search behavior performed by the same user within L2 minutes is marked as a continuous process, and the selected objects corresponding to the search behavior other than the first search behavior in the continuous process are marked as associated objects. The resource type's search vocabulary, one-time retention value and associated objects constitute a statistical data set of the resource type; the keywords and selected objects of each search behavior within the statistical period are counted, and then the statistical data set of the resource type is generated in combination with the continuous search behavior, and the search characteristics of the resource type are fed back according to the statistical data set to provide data support for the shared processing and analysis process.

[0021] The sharing processing module is used to process and analyze the sharing needs of the cloud platform: generate a processing cycle. Within the processing cycle, when the user searches for educational resources, the resource type of the search vocabulary corresponding to the user's input keyword is retrieved and marked as the processing type, and the statistical data set of the processing type is retrieved, and the associated objects are arranged in order of the number of markings from most to least to obtain an associated sequence; after the user enters the keyword, the keyword is searched to generate a regular resource sequence with a resource quantity of L1, and a regular subsequence and an associated subsequence are respectively intercepted from the regular resource sequence and the associated sequence. The number of educational resources in the regular subsequence is equal to the one-time retention value, and the number of educational resources in the associated subsequence is the difference between L1 and the one-time retention value; the processing output sequence is generated by the regular subsequence + the associated subsequence, and the processing output sequence is sent to the user's client; when executing the retrieval task within the processing cycle, the processing output sequence is generated by combining the keyword input by the user with the statistical data set of the corresponding processing type. The processing output sequence consists of a regular subsequence and an associated subsequence, and the number of resources in the regular subsequence is the same as the one-time retention value, thereby improving the user's retrieval efficiency.

[0022] The shared evaluation module is used to evaluate and analyze the shared processing data of the cloud platform: marking the retrieval process within the processing cycle as the analysis process, marking the analysis process that the user did not choose to download in the regular subsequence as the regular optimization process, marking the analysis process that the user did not choose to download in the associated subsequence as the associated optimization process, and marking the analysis process that the user did not choose to download in the processing output sequence as the bidirectional optimization process; at the end of the processing cycle, the marking times of the regular optimization process, the associated optimization process and the bidirectional optimization process are marked as regular optimization data CG, associated optimization data GL and bidirectional optimization data SX respectively.

[0023] The optimization coefficient YH of the processing cycle is obtained by the formula YH=k1×SX+k2×CG+k3×GL, where k1, k2 and k3 are all proportional coefficients, and k1>k2>k3>1; the optimization coefficient YH of the processing cycle is compared with the preset optimization threshold value YHmax: If the optimization coefficient YH is less than the optimization threshold value YHmax, it is determined that the educational resource sharing processing status within the processing cycle meets the requirements, a processing continuation signal is generated and sent to the sharing processing module, and the sharing processing module generates a processing cycle after receiving the processing signal, and continues to perform sharing demand processing analysis in the new processing cycle; If the optimization coefficient YH is greater than or equal to the optimization threshold value YHmax, it is determined that the educational resource sharing processing status within the processing cycle does not meet the requirements, and a statistical update signal is generated and sent to the retrieval statistics module. After receiving the statistical update signal, the retrieval statistics module regenerates the statistical cycle and updates the statistical data set of the resource type in the new statistical cycle; at the end of the processing cycle, multiple evaluation parameters are collected and comprehensively calculated to obtain the optimization coefficient, and the shared processing status within the processing cycle is evaluated by the optimization coefficient, and then different feedback signals are generated according to the evaluation results for differentiated processing.

[0024] Embodiment 2: Figure 2 As shown, a method for sharing educational resources based on a cloud platform includes the following steps: Step 1: Statistical analysis of the educational resource search data of the cloud platform: Classify the educational resources of the cloud platform into several resource types, generate a statistical period, and mark the search word library, one-time retention value, and associated objects of the resource type at the end of the statistical period; Step 2: Process and analyze the sharing needs of the cloud platform: Generate a processing cycle. Within the processing cycle, when a user searches for educational resources, retrieve the resource type of the search vocabulary corresponding to the user's input keyword and mark it as the processing type. Generate a processing output sequence based on the one-time reserved value of the processing type and the associated object; Step 3: Evaluate and analyze the shared processing data of the cloud platform: At the end of the processing cycle, obtain the conventional optimization data CG, the associated optimization data GL, and the bidirectional optimization data SX and perform numerical calculations to obtain the optimization coefficient YH. The optimization coefficient YH is used to determine whether the educational resource sharing processing status within the processing cycle meets the requirements.

[0025] A cloud platform-based educational resource sharing system and method, when working, classifies the educational resources of the cloud platform to obtain several resource types, generates a statistical cycle, and marks the search word library, one-time retention value and associated objects of the resource type at the end of the statistical cycle; generates a processing cycle, within the processing cycle, when a user searches for educational resources, retrieves the resource type of the search word library corresponding to the user input keyword and marks it as the processing type, and generates a processing output sequence according to the one-time retention value and associated object of the processing type; at the end of the processing cycle, obtains conventional optimization data CG, associated optimization data GL and bidirectional optimization data SX and performs numerical calculation to obtain the optimization coefficient YH, and judges whether the educational resource sharing processing status within the processing cycle meets the requirements through the optimization coefficient YH.

[0026] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0027] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula YH=k1×SX+k2×CG+k3×GL; technicians in this field collect multiple groups of sample data and set corresponding optimization coefficients for each group of sample data; substitute the set optimization coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation group, screen the calculated coefficients and take the average, and obtain the values ​​of k1, k2 and k3 as 3.25, 2.62 and 2.17 respectively; The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the initial setting of the corresponding optimization coefficient for each group of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value, such as the optimization coefficient is proportional to the value of the bidirectional optimization data.

[0028] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0029] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An educational resource sharing system based on a cloud platform, characterized in that: It includes a retrieval statistics module, a shared processing module and a shared evaluation module, wherein the retrieval statistics module, the shared processing module and the shared evaluation module are sequentially connected in communication, and the retrieval statistics module is also connected in communication with the shared evaluation module; The retrieval statistics module is used to perform statistical analysis on the educational resource retrieval data of the cloud platform: classify the educational resources of the cloud platform to obtain a number of resource types, generate a statistical cycle, and mark the statistical data set of the resource type at the end of the statistical cycle; The sharing processing module is used to process and analyze the sharing needs of the cloud platform: generate a processing cycle, and within the processing cycle, when a user searches for educational resources, retrieve the resource type of the search vocabulary corresponding to the user input keyword and mark it as the processing type, retrieve the statistical data set of the processing type, generate a processing output sequence through the keywords and the statistical data set, and send the processing output sequence to the user's client; The shared evaluation module is used to evaluate and analyze the shared processing data of the cloud platform: at the end of the processing cycle, the conventional optimization data CG, the associated optimization data GL and the bidirectional optimization data SX are obtained and numerical calculations are performed to obtain the optimization coefficient YH of the processing cycle; the optimization coefficient YH is used to determine whether the educational resource sharing processing status within the processing cycle meets the requirements.

2. According to claim 1, a cloud platform-based educational resource sharing system is characterized in that: The specific process of marking the statistical data set of resource types includes: within the statistical period, after the user enters the keyword, the keyword is searched to generate a regular resource sequence with a resource quantity of L1, the educational resources that the user finally chooses to download in the regular resource sequence are marked as selected objects, and the serial number of the selected object in the regular resource sequence is marked as the selected value. The keywords corresponding to the resource type when all educational resources are marked as selected objects constitute the search vocabulary of the resource type, and the selected values ​​corresponding to all selected objects of the resource type constitute a selection set, and the selection set is cleaned to obtain a retention value; then, the continuous search behavior performed by the same user within L2 minutes is marked as a continuous process, and the selected objects corresponding to the search behavior other than the first search behavior in the continuous process are marked as associated objects. The statistical data set of the resource type is composed of the search vocabulary of the resource type, the one-time retention value and the associated object.

3. According to claim 2, a cloud platform-based educational resource sharing system is characterized in that: The specific process of cleaning the selected set includes: calculating the variance of the selected set to obtain the selected set value, and comparing the selected set value with the preset selected set threshold: if the selected set value is less than the selected set threshold, the maximum element in the selected set is marked as a one-time retention value of the resource type; if the selected set value is greater than or equal to the selected set threshold, the minimum element and the maximum element in the selected set are eliminated, and then the selected set value is recalculated, and so on, until the selected set value is less than the selected set threshold.

4. According to claim 3, the educational resource sharing system based on the cloud platform is characterized in that: The process of generating the processing output sequence includes: arranging the associated objects in order of the number of marking times from most to least to obtain an associated sequence; after the user enters a keyword, searching according to the keyword to generate a regular resource sequence with a resource quantity of L1, and respectively extracting a regular subsequence and an associated subsequence from the regular resource sequence and the associated sequence, the number of educational resources of the regular subsequence is equal to the one-time retention value, and the number of educational resources of the associated subsequence is the difference between L1 and the one-time retention value; generating a processing output sequence with the regular subsequence + the associated subsequence.

5. According to claim 4, a cloud platform-based educational resource sharing system is characterized in that: The acquisition process of the conventional optimization data CG, the associated optimization data GL and the bidirectional optimization data SX includes: marking the retrieval process within the processing cycle as the analysis process, marking the analysis process that the user did not choose to download in the conventional subsequence as the conventional optimization process, marking the analysis process that the user did not choose to download in the associated subsequence as the associated optimization process, and marking the analysis process that the user did not choose to download in the processing output sequence as the bidirectional optimization process; at the end of the processing cycle, the marking times of the conventional optimization process, the associated optimization process and the bidirectional optimization process are marked as the conventional optimization data CG, the associated optimization data GL and the bidirectional optimization data SX respectively.

6. The educational resource sharing system based on a cloud platform according to claim 5, characterized in that: The specific process of determining whether the educational resource sharing processing status within the processing cycle meets the requirements includes: comparing the optimization coefficient YH of the processing cycle with the preset optimization threshold YHmax: if the optimization coefficient YH is less than the optimization threshold YHmax, then it is determined that the educational resource sharing processing status within the processing cycle meets the requirements; if the optimization coefficient YH is greater than or equal to the optimization threshold YHmax, then it is determined that the educational resource sharing processing status within the processing cycle does not meet the requirements.

7. The cloud platform-based educational resource sharing system according to claim 6, characterized in that: When the educational resource sharing processing status of the processing cycle meets the requirements, a processing continuation signal is generated through the shared evaluation module and sent to the shared processing module. The shared processing module generates a processing cycle after receiving the processing signal and continues to perform shared demand processing analysis in the new processing cycle. When the educational resource sharing processing status of the processing cycle does not meet the requirements, a statistical update signal is generated by the shared evaluation module and sent to the retrieval statistics module. After receiving the statistical update signal, the retrieval statistics module regenerates the statistical cycle and updates the statistical data set of the resource type in the new statistical cycle.

8. A method for sharing educational resources based on a cloud platform, characterized in that: The following steps are involved: Step 1: Statistically analyze the educational resource retrieval data on the cloud platform and label the statistical data set of resource types; Step 2: Process and analyze the sharing needs of the cloud platform: When users search for educational resources, a processing output sequence is generated based on the once-retained value of the processing type and the associated objects; Step 3: Evaluate and analyze the shared processing data of the cloud platform and obtain the optimization coefficient YH. Use the optimization coefficient YH to determine whether the shared processing status of educational resources within the processing cycle meets the requirements.

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