Distributed teaching resource sharing service system and method

Abstract

The invention belongs to the technical field of teaching resource sharing, and particularly relates to a distributed teaching resource sharing service system and method. According to the method, the teaching resource information is subjected to correlation sorting, so that the teaching resource closest to the user demand can be preferentially displayed to the user, the accuracy of the retrieval result is improved, in addition, a dynamic popularity value evaluation mechanism of the teaching resource information is introduced, and the accuracy of the retrieval result is improved. According to the method, the effective retrieval times and the effective retrieval duration of the teaching resources are comprehensively considered to comprehensively reflect the popularity degree of the teaching resources, the popularity trend of the teaching resources can be more accurately grasped through comprehensive evaluation of the long-term popularity value and the short-term popularity value, meanwhile, a semantic quality scoring mechanism is introduced, and the quality of the teaching resources is improved. According to the mechanism, the text quality, the content accuracy and the integrity of the teaching resource information are evaluated in detail, so that the pushed teaching resources are ensured to be high in popularity and high in content, and the user experience is further improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of teaching resource sharing, and particularly relates to a distributed teaching resource sharing service system and method. Background Art

[0002] The sharing of teaching resources is of great significance in the current education field. With the rapid development of information technology, the forms of teaching resources are becoming increasingly rich, including but not limited to video tutorials, e-books, online courses, etc. And the online sharing of teaching resources has become an important trend in the education field. Therefore, how to efficiently manage and share these teaching resources has become an urgent problem to be solved in the current education field.

[0003] In the prior art, a centralized sharing method is usually adopted, that is, all teaching resources are centrally stored in a server, and users obtain the required teaching resources by accessing this server. However, this method has many deficiencies, such as overloaded server, slow access speed, untimely resource update, etc. At the same time, at present, when the teaching resource platform pushes resources, it generally adjusts the priority based on data such as the access volume of the resources. However, in the actual use process, there are various types of teaching resources and the resource quality is uneven. Relying solely on intuitive data such as access volume to perform recommendation sorting is likely to cause inaccurate recommendations. For example, some resource publishers may conduct artificial intervention in order to obtain a resource share, resulting in false access volume, thus making it difficult to control the quality of the actual recommended content. To solve these problems, the present invention proposes a distributed teaching resource sharing service method. Summary of the Invention

[0004] The purpose of the present invention is to provide a distributed teaching resource sharing service system and method, which can perform intelligent management and push according to the dynamic heat value of teaching resource information, so as to improve the sharing efficiency of teaching resources and the user experience.

[0005] The technical solutions adopted by the present invention are specifically as follows:

[0006] A distributed teaching resource sharing service method includes:

[0007] Obtain teaching resource information and distribute and store the teaching resource information in multiple server nodes, wherein each server node corresponds to a teaching area;

[0008] Obtain user requirements and retrieve and call relevant teaching resource information from multiple server nodes according to the user requirements;

[0009] Count the effective access times and effective access durations of each teaching resource information, and determine the dynamic heat value of each teaching resource information according to the effective access times and effective access durations;

[0010] Perform a comprehensive sorting process on the teaching resource information according to the dynamic heat value and semantic quality score, and optimize the push priority of each teaching resource information according to the comprehensive sorting result;

[0011] Intelligently select a server node to push the teaching resource information according to the push priority of each teaching resource information and the distribution location of the server nodes.

[0012] In a preferred solution, when obtaining the teaching resource information, preprocess the teaching resource information synchronously. The steps of the preprocessing include:

[0013] Denoise the teaching resource information to remove redundant information and irrelevant content;

[0014] Perform format unification processing on the denoised teaching resource information to eliminate format differences between different teaching resource information;

[0015] Extract keywords from the teaching resource information with unified format, and add classification labels to the teaching resource information according to the keywords to determine the retrieval conditions of the teaching resource information.

[0016] In a preferred solution, the steps of retrieving and calling relevant teaching resource information from the multiple server nodes according to user needs include:

[0017] Obtain user needs and extract key retrieval terms from the user needs;

[0018] Match the key retrieval terms with the classification labels of each teaching resource information, screen out the teaching resource information containing classification labels matching the key retrieval terms from multiple server nodes, and record them as associated teaching resource information;

[0019] Obtain an association measurement function, calculate the association degree between the associated teaching resource information and user needs in combination with the key retrieval terms and classification labels, and then sort the associated teaching resource information according to the association degree.

[0020] Among them, the greater the association degree, the higher the sorting position of the corresponding associated teaching resource information in the retrieval result.

[0021] In a preferred solution, after the key retrieval terms and classification labels are determined, they are both vectorized to obtain a retrieval vector corresponding to the key retrieval terms and a reference vector corresponding to the classification labels;

[0022] Input the retrieval vector and the reference vector into the correlation calculation function together, and record the calculation result of the correlation calculation function as the correlation degree between the associated teaching resource information and the user requirements;

[0023] Among them, both the retrieval vector and the reference vector are numerical vectors.

[0024] In a preferred solution, the step of determining the dynamic heat value of each teaching resource information according to the effective access times and the effective access duration includes:

[0025] Obtain the effective access times and the effective access duration of the teaching resource information;

[0026] Perform normalization processing on the effective access times and the effective access duration to obtain a first conditional parameter corresponding to the effective access times and a second conditional parameter corresponding to the effective access duration;

[0027] Obtain a comprehensive evaluation function, input the first conditional parameter and the second conditional parameter into the comprehensive evaluation function together, and record the output result of the comprehensive evaluation function as the dynamic heat value of the teaching resource information.

[0028] In a preferred solution, the dynamic heat value of the teaching resource information includes a long-term heat value and a short-term heat value;

[0029] When determining the long-term heat value, use the total length of the upload time of the teaching resource information as the first sampling period, and calculate based on the effective access times and the effective access duration of the teaching resource information within the first sampling period;

[0030] When determining the short-term heat value, perform reverse offset processing based on the current access node of the teaching resource information, and output a second sampling period according to the offset result, and calculate based on the effective access times and the effective access duration of the teaching resource information within the second sampling period;

[0031] Among them, the time length of the second sampling period is less than the time length of the first sampling period.

[0032] In a preferred solution, the step of comprehensively sorting the teaching resource information according to the dynamic heat value and the semantic quality score, and optimizing the push priority of each teaching resource information according to the comprehensive sorting result includes:

[0033] Obtain the long-term heat value and the short-term heat value of each teaching resource information, and assign corresponding weight factors to the long-term heat value and the short-term heat value;

[0034] Obtain a scoring function, input the long-term popularity value, short-term popularity value, and the weight factors of the long-term popularity value and short-term popularity value into the scoring function together, and record the output result of the evaluation function as the initial priority score;

[0035] Obtain the semantic quality score of the teaching resource information, and the semantic quality score is evaluated according to the text quality, content accuracy and integrity of the teaching resource information;

[0036] Perform a non-linear combination of the initial priority score and the semantic quality score to obtain the comprehensive ranking score of the teaching resource information;

[0037] Arrange the comprehensive ranking scores in descending order, and assign the push priority of the corresponding teaching resource information according to the arrangement result.

[0038] In a preferred solution, the step of intelligently selecting a server node to push the teaching resource information according to the push priority of each teaching resource information and the distribution location of the server nodes includes:

[0039] Obtain the geographical location information of the user, and according to the geographical location information of the user, determine the distance between the user and the server node, and record it as the first push condition parameter;

[0040] Obtain the push priority of the teaching resource information and record it as the second push condition parameter;

[0041] Perform a comprehensive analysis of the first push condition parameter and the second push condition parameter to determine the server node that best matches the user's needs;

[0042] Among them, the comprehensive analysis includes weighted summation of the first push condition parameter and the second push condition parameter, and selection of the server node based on the result of the weighted summation.

[0043] The present invention also provides a distributed teaching resource sharing service system, which uses the above-mentioned distributed teaching resource sharing service method, including:

[0044] A resource acquisition module, which is used to acquire teaching resource information and distribute and store the teaching resource information in multiple server nodes, where each server node corresponds to a teaching area;

[0045] A resource retrieval module, which is used to obtain user needs and retrieve and call relevant teaching resource information from multiple server nodes according to user needs;

[0046] A heat evaluation module, which is used to count the effective access times and effective access durations of each piece of teaching resource information, and determine the dynamic heat value of each piece of teaching resource information according to the effective access times and effective access durations;

[0047] An optimization module, which is used to perform comprehensive sorting processing on the teaching resource information according to the dynamic heat value and semantic quality score, and optimize the push priority of each piece of teaching resource information according to the comprehensive sorting result;

[0048] An intelligent push module, which is used to intelligently select a server node to push the teaching resource information according to the push priority of each piece of teaching resource information and the distribution location of the server nodes.

[0049] And, an electronic device, which includes:

[0050] At least one processor;

[0051] And a memory communicatively connected to the at least one processor;

[0052] Wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned distributed teaching resource sharing service method.

[0053] The technical effects achieved by the present invention are:

[0054] By performing intelligent retrieval, evaluation, sorting, and pushing on the teaching resource information, the present invention can effectively improve the usage efficiency of teaching resources and user satisfaction. Through the correlation calculation function, the correlation degree sorting of the selected teaching resource information is carried out, so that the teaching resources closest to the user's needs can be preferentially displayed to the user, thereby improving the accuracy of the retrieval results. In addition, a dynamic heat value evaluation mechanism for teaching resource information is introduced, which comprehensively considers the effective access times and effective access durations of teaching resources to comprehensively reflect the popularity of teaching resources. Through the comprehensive evaluation of the long-term heat value and short-term heat value, the popular trend of teaching resources can be grasped more accurately, providing a strong basis for optimizing the push priority. At the same time, a semantic quality scoring mechanism is introduced. By carefully evaluating the text quality, content accuracy, and integrity of the teaching resource information, it ensures that the pushed teaching resources not only have a high popularity but also high-quality content, further improving the user experience. In the push strategy, according to the push priority of the teaching resource information and the distribution location of the server nodes, the server nodes are intelligently selected to push the teaching resource information, which not only ensures that users can quickly receive the required teaching resources but also realizes the reasonable allocation and efficient utilization of teaching resources. Description of the Drawings

[0055] Figure 1 is the schematic diagram of the method flow of the present invention;

[0056] Figure 2 is the schematic diagram of the system module of the present invention;

[0057] Figure 3 is the schematic diagram of the structure of the electronic device of the present invention. Detailed implementation manners

[0058] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe the detailed implementation manners of the present invention in conjunction with the accompanying drawings of the specification.

[0059] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may be implemented in other ways different from those described herein. Those skilled in the art can make similar extensions without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0060] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation manner of the present invention. The "in a preferred embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that excludes other embodiments.

[0061] Please refer to Figure 1 As shown, the present invention provides a distributed teaching resource sharing service method, including:

[0062] S1. Obtain teaching resource information and distribute and store the teaching resource information in multiple server nodes, where each server node corresponds to a teaching area;

[0063] In step S1, when performing a sharing service on the teaching resource information, various types of teaching resource information will first be comprehensively obtained and distributed and stored in multiple different server nodes. In this process, each server node corresponds to a specific teaching area, so as to ensure the efficient management and rapid access of resources. Among them, when obtaining the teaching resource information, the teaching resource information is preprocessed synchronously. The steps of the preprocessing include:

[0064] Perform noise reduction processing on the teaching resource information to remove redundant information and irrelevant content;

[0065] Perform format unification processing on the noise-reduced teaching resource information to eliminate the format differences between different teaching resource information;

[0066] Extract keywords from the teaching resource information after unified format processing, add classification labels to the teaching resource information based on the keywords, and determine the retrieval conditions for the teaching resource information;

[0067] Specifically, during the process of obtaining teaching resource information, preprocessing of the teaching resource information is carried out synchronously. First, noise reduction processing is performed on the obtained teaching resource information to effectively eliminate redundant information and content unrelated to teaching, ensuring the purity and relevance of the information. Second, on the basis of noise reduction processing, unified format processing is performed on the screened teaching resource information to eliminate format differences existing between different teaching resource information, making all teaching resource information consistent in format for subsequent integration and analysis. Finally, for the teaching resource information that has completed unified format, keyword extraction operations are carried out, and corresponding classification labels are added to the teaching resource information according to the extracted keywords, thereby clarifying the retrieval conditions for the teaching resource information and providing a convenient and accurate basis for subsequent retrieval and use.

[0068] S2. Obtain user requirements, and retrieve and call relevant teaching resource information from multiple server nodes according to the user requirements;

[0069] In step S2, after the distributed storage of teaching resource information is completed, the actual requirements of the user can be obtained, and according to the specific requirements of the user, relevant teaching resource information can be accurately retrieved and called from multiple distributed server nodes to ensure that the user can quickly obtain the required teaching resources. Among them, the steps of retrieving and calling relevant teaching resource information from multiple server nodes according to the user requirements include:

[0070] Obtain user requirements, and extract key retrieval terms from the user requirements;

[0071] Match the key retrieval terms with the classification labels of each teaching resource information, screen out the teaching resource information containing classification labels that match the key retrieval terms from multiple server nodes, and record them as associated teaching resource information;

[0072] Obtain the association measurement function, calculate the association degree between the associated teaching resource information and the user requirements by combining the key retrieval terms and the classification labels, and then sort the associated teaching resource information according to the association degree.

[0073] Among them, the greater the association degree, the higher the ranking position of the corresponding associated teaching resource information in the retrieval results;

[0074] Specifically, when efficiently retrieving and invoking relevant teaching resource information from numerous teaching resource information distributed across different server nodes according to the specific needs of users, it is first necessary to accurately obtain the actual needs of users. On this basis, key retrieval terms are extracted. Then, the key retrieval terms are used to perform a detailed matching operation with the classification tags attached to each teaching resource information, so as to carefully screen out those teaching resource information containing classification tags that match the key retrieval terms among multiple server nodes and record them as associated teaching resource information related to the user's needs. After that, a preset association calculation function can be introduced. Based on the already extracted key retrieval terms and the classification tags of the teaching resource information, the association degree between the associated teaching resource information and the user's actual retrieval needs is comprehensively calculated. After the key retrieval terms and classification tags are determined, they are both vectorized to obtain a retrieval vector corresponding to the key retrieval term and a reference vector corresponding to the classification tag. Both the retrieval vector and the reference vector are numerical vectors. By inputting the retrieval vector and the reference vector into the association calculation function together, the association degree between the associated teaching resource information and the user's needs can be calculated; among them, the expression of the association calculation function is: In the formula, R represents the association degree between the associated teaching resource information and the user's needs, n represents the number of feature points in the retrieval vector and the reference vector, a i and b i respectively represent the retrieval vector and the reference vector. Then, according to the calculated association degree, the selected associated teaching resource information is sorted in an orderly manner. The larger the value of the association degree, the higher the matching degree between the corresponding associated teaching resource information and the actual needs of the user. Therefore, in the final retrieval result, the higher the association degree of the associated teaching resource information, the higher its sorting position, so as to ensure that users can preferentially obtain the teaching resource information that best meets their own needs.

[0075] S3. Count the effective access times and effective access durations of each teaching resource information, and determine the dynamic popularity value of each teaching resource information according to the effective access times and effective access durations;

[0076] In step S3, during the sharing service process of teaching resource information, the effective access times and effective access durations of each piece of teaching resource information are carefully counted, and the dynamic popularity value of each piece of teaching resource information is determined based on the already counted effective access times and effective access durations, so as to more accurately reflect the popularity of each piece of teaching resource information. The determination methods of the effective access times and effective access durations can be judged through the specific usage behaviors of users. For example, when a user views or downloads a piece of teaching resource information, it is regarded as an effective access behavior. At the same time, the duration from when the user starts accessing the teaching resource information until the access ends is recorded as the effective access duration. The determination of the effective access times and effective access durations can avoid the interference of some invalid or false access data on the calculation of the popularity value, and improve the accuracy and credibility of the dynamic popularity value. Among them, the dynamic popularity value of the teaching resource information includes the long-term popularity value and the short-term popularity value, and the time length of the second sampling period is less than that of the first sampling period;

[0077] When determining the long-term popularity value, the total length of the upload time of the teaching resource information is used as the first sampling period, and the calculation is based on the effective access times and effective access durations of the teaching resource information within the first sampling period;

[0078] When determining the short-term popularity value, a reverse offset process is carried out based on the current access node of the teaching resource information, and the second sampling period is output according to the offset result, and the calculation is based on the effective access times and effective access durations of the teaching resource information within the second sampling period;

[0079] Specifically, the dynamic popularity value of the teaching resource information covers two main aspects, namely the long-term popularity value and the short-term popularity value. In the process of determining the long-term popularity value, first, a time period with a relatively long time span needs to be selected as the first sampling period. The specific length of the first sampling period is based on the total length of the upload time of the teaching resource information. Within this first sampling period, through comprehensive statistics and analysis of the effective access times and effective access durations of the teaching resource information, the long-term popularity value of this teaching resource is calculated based on this. When determining the short-term popularity value, first, the current access node of the teaching resource information is used as the reference point for reverse offset processing. The specific offset duration can be set according to actual needs. Through this offset processing method, a relatively short time period, that is, the second sampling period, is determined. Then, within this second sampling period, through detailed statistics and analysis of the effective access times and effective access durations of the teaching resource information, the short-term popularity value of this teaching resource is calculated based on this, so as to reflect the short-term popularity change of the teaching resource.

[0080] In addition, the steps for determining the dynamic heat value of each teaching resource information according to the effective access times and the effective access duration include:

[0081] Obtain the effective access times and the effective access duration of the teaching resource information;

[0082] Perform normalization processing on the effective access times and the effective access duration to obtain a first conditional parameter corresponding to the effective access times and a second conditional parameter corresponding to the effective access duration;

[0083] Obtain a comprehensive evaluation function, input the first conditional parameter and the second conditional parameter into the comprehensive evaluation function together, and record the output result of the comprehensive evaluation function as the dynamic heat value of the teaching resource information;

[0084] When determining the dynamic heat value of each teaching resource information according to the effective access times and the effective access duration, first, it is necessary to obtain the effective access times and the effective access duration of each teaching resource information. Secondly, it is also necessary to perform corresponding normalization processing on the effective access times and the effective access duration so that the effective access times and the effective access duration can be compared and analyzed under a unified evaluation standard. The specific method of normalization processing can be to divide the effective access times and the effective access duration by their respective maximum possible values to obtain a value between 0 and 1, and then the first conditional parameter corresponding to the effective access times and the second conditional parameter corresponding to the effective access duration can be obtained, so as to ensure that data with different dimensions can be compared on the same scale. Then, it is necessary to obtain a preset comprehensive evaluation function, and then input the first conditional parameter and the second conditional parameter into the comprehensive evaluation function together. Through the calculation of the comprehensive evaluation function, a comprehensive evaluation result is obtained. Finally, record the output result of the comprehensive evaluation function as the dynamic heat value (both the long-term heat value and the short-term heat value use this comprehensive evaluation function) of the corresponding teaching resource information, so as to perform resource sorting and recommendation for subsequent use. Among them, the expression of the comprehensive evaluation function is: P z = αC1 + βC2, where P z represents the dynamic heat value of the teaching resource information, α and β respectively represent the weight coefficients of the first conditional parameter and the second conditional parameter, C1 and C2 respectively represent the first conditional parameter and the second conditional parameter. Through the above method, the heat of each teaching resource can be scientifically and reasonably evaluated, and more valuable resource recommendations can be provided for users.

[0085] S4. Perform comprehensive sorting processing on the teaching resource information according to the dynamic heat value and the semantic quality score, and optimize the push priority of each teaching resource information according to the comprehensive sorting result;

[0086] In step S4, after the dynamic heat value of the teaching resource information is output, the teaching resource information is sorted accordingly based on its dynamic heat value, and based on the sorting result, the push priority of each teaching resource information is optimized to ensure that users can obtain popular and practical resources first. Among them, the steps of comprehensively sorting the teaching resource information according to the dynamic heat value and semantic quality score and optimizing the push priority of each teaching resource information according to the comprehensive sorting result include:

[0087] Obtain the long-term heat value and short-term heat value of each teaching resource information, and assign corresponding weight factors to the long-term heat value and short-term heat value;

[0088] Obtain the scoring function, input the long-term heat value, short-term heat value, and the weight factors of the long-term heat value and short-term heat value into the scoring function together, and record the output result of the evaluation function as the initial priority score;

[0089] Obtain the semantic quality score of the teaching resource information, and the semantic quality score is evaluated according to the text quality, content accuracy and integrity of the teaching resource information;

[0090] Perform a non-linear combination of the initial priority score and the semantic quality score to obtain the comprehensive sorting score of the teaching resource information;

[0091] Arrange the comprehensive sorting scores in descending order, and assign the push priority of the corresponding teaching resource information according to the arrangement result;

[0092] Specifically, when optimizing the push priorities of various teaching resource information according to the sorting results, first, comprehensively obtain the long-term popularity value and short-term popularity value of each teaching resource information. The long-term popularity value reflects the popularity of the teaching resource information over a relatively long period of time, while the short-term popularity value reflects the attention of the teaching resource information in the near future. At the same time, it is also necessary to determine the weight factors of the long-term popularity value and the short-term popularity value. Here, the weight factor of the short-term popularity value is higher than that of the long-term popularity value to better reflect the impact of the short-term popularity change of the teaching resource information on users. Then, obtain the preset scoring function, and input the collected long-term popularity value, short-term popularity value, and the corresponding weight factors into the scoring function, and the comprehensive score of each teaching resource information can be calculated. Among them, the expression of the scoring function is: H = xT + yt, where H represents the initial priority score of the teaching resource information, x and y respectively represent the weight factors of the long-term popularity value and the short-term popularity value, T and t respectively represent the long-term popularity value and the short-term popularity value. Subsequently, the semantic quality score of the teaching resource information will also be collected. The semantic quality score is obtained based on the comprehensive consideration of the text quality, content accuracy, and integrity of the teaching resource information. In terms of text quality, analyze grammar correctness, structural clarity, readability, etc. through natural language processing technology. For example, use the BERT model to calculate the text quality score. In terms of content accuracy, the correctness of the teaching resource content can be verified by comparing with authoritative databases or expert review results to output the content accuracy score. The lower the error rate, the higher the score. Content integrity mainly evaluates whether the core knowledge points are covered, and the missing ratio can be matched through the knowledge graph. The calculation formula is: In the formula, Q completeness represents the content integrity score, M q represents the number of missing knowledge points, M z represents the total number of knowledge points. After that, directly perform weighted summation on the text quality score, content accuracy score, and content integrity score to obtain the final semantic quality score. Then, perform non-linear combination on the semantic quality score and the initial priority score. Among them, the first combination formula is: S = H·Q, where S represents the comprehensive sorting score and Q represents the semantic quality score. This method emphasizes the balance between the initial priority score and the semantic quality score. A low score in any index will significantly reduce the total score. The second combination formula is: In the formula, Q minRepresents the lower limit value (minimum quality threshold) of the semantic quality score. This method emphasizes that the semantic quality meets the standard, otherwise, it will be directly filtered. In practical applications, different combination methods can be selected according to specific requirements to flexibly adjust the push strategy of teaching resource information. Finally, the priority scores of all teaching resource information are arranged in descending order. According to this arrangement result, the push priorities of the corresponding teaching resource information are assigned one by one. Teaching resources with higher priorities will be pushed to users first, so as to ensure that users can first access high-quality and popular teaching content.

[0093] S5. According to the push priorities of each teaching resource information and the distribution locations of server nodes, intelligently select server nodes to push teaching resource information.

[0094] In step S5, after the push priorities of teaching resource information are determined, the most suitable server nodes can be intelligently selected to push teaching resource information according to the push priorities of each teaching resource information and the specific distribution locations of each server node, so as to achieve fast and efficient transmission of resources and improve the user experience. Among them, the step of intelligently selecting server nodes to push teaching resource information according to the push priorities of each teaching resource information and the distribution locations of server nodes includes:

[0095] Obtain the geographical location information of the user, and according to the geographical location information of the user, determine the distance between the user and the server node, and record it as the first push condition parameter;

[0096] Obtain the push priority of the teaching resource information, and record it as the second push condition parameter;

[0097] Comprehensively analyze the first push condition parameter and the second push condition parameter to determine the server node that best matches the user's needs;

[0098] Among them, the comprehensive analysis includes weighted summation of the first push condition parameter and the second push condition parameter, and selection of server nodes based on the result of the weighted summation;

[0099] Specifically, when pushing teaching resource information, the geographical location information of the user will be obtained first. This can be achieved through the device positioning of the user or other location services. After obtaining the geographical location information of the user, the actual distance between the user and each server node will be further calculated and determined, and this distance data will be recorded as the first push condition parameter for subsequent analysis and decision-making. Secondly, the push priority of the teaching resource information also needs to be obtained and recorded as the second push condition parameter for use in subsequent comprehensive analysis. Next, a comprehensive analysis of the first push condition parameter and the second push condition parameter will be carried out. The process of comprehensive analysis includes weighted summation of the first push condition parameter and the second push condition parameter, that is, different weights are assigned according to the importance and influence degree of the first push condition parameter and the second push condition parameter, and then the weighted results are summed. Based on the result of the weighted summation, the selection of the server node will be further carried out, and finally the server node that best matches the user's needs will be determined to ensure that the teaching resource information can be pushed to the user efficiently and accurately.

[0100] Please refer to Figure 2 , a distributed teaching resource sharing service system, using the above-mentioned distributed teaching resource sharing service method, includes:

[0101] A resource acquisition module, which is used to acquire teaching resource information and distribute and store the teaching resource information in multiple server nodes. Among them, each server node corresponds to a teaching area;

[0102] A resource retrieval module, which is used to obtain the user's needs and retrieve and call relevant teaching resource information from multiple server nodes according to the user's needs;

[0103] A heat evaluation module, which is used to count the effective access times and effective access durations of each teaching resource information, and determine the dynamic heat value of each teaching resource information according to the effective access times and effective access durations;

[0104] An optimization module, which is used to perform comprehensive sorting processing on the teaching resource information according to the dynamic heat value and semantic quality score, and optimize the push priority of each teaching resource information according to the comprehensive sorting result;

[0105] An intelligent push module, which is used to intelligently select a server node to push the teaching resource information according to the push priority of each teaching resource information and the distribution location of the server nodes.

[0106] In the above, the system includes a resource acquisition module, a resource retrieval module, a popularity evaluation module, an optimization module, and an intelligent push module. Each module works collaboratively to achieve the sharing and intelligent push of teaching resources. The main responsibility of the resource acquisition module is to obtain rich teaching resource information from various channels and store the teaching resource information in multiple server nodes according to specific strategies. Specifically, each server node is set to correspond to a specific teaching area, thereby realizing the regional management and efficient utilization of teaching resources. The function of the resource retrieval module is to accurately obtain the specific needs of users and efficiently retrieve and call teaching resource information distributed in different server nodes according to user needs. In this way, users can quickly obtain teaching resources that match their needs, greatly improving the efficiency and accuracy of resource retrieval. The popularity evaluation module is used to count and analyze the effective access times and effective access durations of each teaching resource information. Based on the effective access times and effective access durations, the dynamic popularity value of each teaching resource information can be scientifically determined, providing important data support for subsequent resource optimization and push. The role of the optimization module is to perform an orderly sorting process on the teaching resource information according to the dynamic popularity value determined by the popularity evaluation module. On this basis, the push priority of each teaching resource information will be further optimized according to the sorting results to ensure that users can preferentially obtain the most popular and practical teaching resources. The intelligent push module is reflected in its ability to intelligently select the most suitable server node for pushing teaching resource information based on the push priority of each teaching resource information and in combination with the distribution location of the server nodes. This not only improves the accuracy of resource push but also significantly enhances the user experience and the overall operation efficiency of the system.

[0107] Please refer to Figure 3 , an electronic device, the electronic device includes:

[0108] At least one processor;

[0109] And a memory communicatively connected to the at least one processor;

[0110] Wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned distributed teaching resource sharing service method.

[0111] The processor of the above-mentioned electronic device can be a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), etc. These processors have powerful computing capabilities and data processing capabilities, and can efficiently execute computer programs stored in the memory, thereby implementing a distributed teaching resource sharing service method. In addition, the electronic device may further include an input device, such as a keyboard, a mouse, or a touch screen, etc., for receiving user operation instructions and input information; and an output device, such as a display or a speaker, etc., for presenting processing results and feedback information to the user. Through the collaborative work of these components, the electronic device can provide users with an efficient and convenient teaching resource sharing service experience.

[0112] It should be noted that in this article, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, apparatus, article or method including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, apparatus, article or method. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, apparatus, article or method including the element.

[0113] The above are only the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention. The structures, devices and operation methods not specifically described and explained in the present invention are implemented according to the conventional means in the art without special description and limitation.

Claims

1. A distributed teaching resource sharing service method, characterized in that: Including: Obtain teaching resource information and distribute and store the teaching resource information in multiple server nodes, where each server node corresponds to a teaching area; Obtain user requirements and retrieve and call relevant teaching resource information from multiple server nodes according to the user requirements; Count the effective access times and effective access durations of each teaching resource information, and determine the dynamic popularity value of each teaching resource information according to the effective access times and effective access durations; Perform comprehensive sorting processing on the teaching resource information according to the dynamic popularity value and semantic quality score, and optimize the push priority of each teaching resource information according to the comprehensive sorting result; Intelligently select a server node to push the teaching resource information according to the push priority of each teaching resource information and the distribution location of the server node.

2. The distributed teaching resource sharing service method according to claim 1, characterized in that: When obtaining the teaching resource information, preprocess the teaching resource information synchronously. The steps of the preprocessing include: Perform denoising processing on the teaching resource information to remove redundant information and irrelevant content; Perform format unification processing on the denoised teaching resource information to eliminate format differences between different teaching resource information; Extract keywords from the teaching resource information after format unification processing, and add classification labels to the teaching resource information according to the keywords to determine the retrieval conditions of the teaching resource information.

3. The distributed teaching resource sharing service method according to claim 2, wherein: The step of retrieving and calling relevant teaching resource information from the multiple server nodes according to the user requirements includes: Obtain user requirements and extract key retrieval terms from the user requirements; Match the key retrieval terms with the classification labels of each teaching resource information, screen out the teaching resource information containing classification labels matching the key retrieval terms from multiple server nodes, and record it as associated teaching resource information; Obtain an association measurement function, calculate the association degree between the associated teaching resource information and the user requirements by combining the key retrieval terms and classification labels, and then sort the associated teaching resource information according to the association degree; Among them, the greater the association degree, the higher the sorting position of the corresponding associated teaching resource information in the retrieval result.

4. A distributed teaching resource sharing service method according to claim 3, characterized in that: After the key retrieval terms and classification labels are determined, they are both vectorized to obtain a retrieval vector corresponding to the key retrieval terms and a reference vector corresponding to the classification labels; Input the retrieval vector and the reference vector into the association measurement function together, and record the measurement result of the association measurement function as the association degree between the associated teaching resource information and the user requirements; Among them, both the retrieval vector and the reference vector are numerical vectors.

5. A distributed teaching resource sharing service method according to claim 1, characterized in that: The step of determining the dynamic popularity value of each teaching resource information according to the effective access times and effective access durations includes: Obtain the effective access times and effective access durations of the teaching resource information; Perform normalization processing on the effective access times and effective access durations to obtain a first conditional parameter corresponding to the effective access times and a second conditional parameter corresponding to the effective access duration; Obtain a comprehensive evaluation function, input the first conditional parameter and the second conditional parameter into the comprehensive evaluation function together, and record the output result of the comprehensive evaluation function as the dynamic heat value of the teaching resource information.

6. A distributed teaching resource sharing service method according to claim 5, characterized in that: The dynamic heat value of the teaching resource information includes a long-term heat value and a short-term heat value; When determining the long-term heat value, use the total length of the upload time of the teaching resource information as the first sampling period, and calculate based on the effective access times and effective access duration of the teaching resource information within the first sampling period; When determining the short-term heat value, perform a reverse offset process based on the current access node of the teaching resource information, output a second sampling period according to the offset result, and calculate based on the effective access times and effective access duration of the teaching resource information within the second sampling period; Among them, the time length of the second sampling period is less than the time length of the first sampling period.

7. A distributed teaching resource sharing service method according to claim 6, characterized in that: The step of comprehensively sorting the teaching resource information according to the dynamic heat value and the semantic quality score, and optimizing the push priority of each teaching resource information according to the comprehensive sorting result includes: Obtain the long-term heat value and short-term heat value of each teaching resource information, and assign corresponding weight factors to the long-term heat value and short-term heat value; Obtain a scoring function, input the long-term heat value, short-term heat value, and the weight factors of the long-term heat value and short-term heat value into the scoring function together, and record the output result of the evaluation function as the initial priority score; Obtain the semantic quality score of the teaching resource information, and the semantic quality score is evaluated according to the text quality, content accuracy, and integrity of the teaching resource information; Perform a non-linear combination of the initial priority score and the semantic quality score to obtain the comprehensive sorting score of the teaching resource information; Arrange the comprehensive sorting scores in descending order, and assign the push priority of the corresponding teaching resource information according to the arrangement result.

8. A distributed teaching resource sharing service method according to claim 1, characterized in that: The step of intelligently selecting a server node to push the teaching resource information according to the push priority of each teaching resource information and the distribution location of the server nodes includes: Obtain the geographical location information of the user, and according to the geographical location information of the user, determine the distance between the user and the server node, and record it as the first push conditional parameter; Obtain the push priority of the teaching resource information, and record it as the second push conditional parameter; Perform a comprehensive analysis of the first push conditional parameter and the second push conditional parameter to determine the server node that best matches the user's needs; Among them, the comprehensive analysis includes a weighted sum of the first push conditional parameter and the second push conditional parameter, and the selection of the server node based on the result of the weighted sum.

9. A distributed teaching resource sharing service system, characterized in that: The distributed teaching resource sharing service method using any one of claims 1 to 8 includes: A resource acquisition module, which is used to acquire teaching resource information and distribute and store the teaching resource information in multiple server nodes, where each server node corresponds to a teaching area; A resource retrieval module, which is used to obtain user requirements and retrieve and call relevant teaching resource information from multiple server nodes according to the user requirements; A popularity evaluation module, which is used to count the effective access times and effective access durations of each piece of teaching resource information, and determine the dynamic popularity value of each piece of teaching resource information according to the effective access times and effective access durations; An optimization module, which is used to perform comprehensive sorting processing on the teaching resource information according to the dynamic popularity value and semantic quality score, and optimize the push priority of each piece of teaching resource information according to the comprehensive sorting result; An intelligent push module, which is used to intelligently select a server node to push the teaching resource information according to the push priority of each piece of teaching resource information and the distribution location of the server nodes.

10. An electronic device, characterized in that: The electronic device includes: At least one processor; And a memory communicatively connected to the at least one processor; Wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can execute the distributed teaching resource sharing service method according to any one of claims 1 to 8.

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