Ideological and political content real-time upgrading system based on big data environment

Abstract

The invention discloses an ideological and political content real-time upgrading system based on a big data environment, which belongs to the technical field of ideological and political technologies and comprises a registration module, a data storage platform, an acquisition module, an analysis and evaluation module and a resource optimization module. The registration module is responsible for registration of student information and classified storage according to grades; the collection module collects current political information, learning condition information and ideological and political public opinion information; the analysis and evaluation module obtains a current political value, a learning condition popularity value and a public opinion comprehensive value by calculating parameters such as time efficiency, attention values and the like; the resource optimization module combines factors such as the number of people of grades, the average duration of ideological and political teaching per week and weekly test scores to determine the recommendation number of various types of information, and screens out high-quality content to update ideological and political teaching; the system effectively solves the problem of low interest of students, realizes optimal configuration of educational resources, and improves the teaching effect.

Description

Technical Field

[0001] The present invention belongs to the field of ideological and political technology, and specifically relates to a real-time ideological and political content upgrade system based on a big data environment. Background Art

[0002] In the era of big data, information dissemination is characterized by massiveness, speed and variability; the rapid development of the Internet has caused information to emerge like a torrent, and people's efficiency in obtaining information has been greatly improved; in this environment, ideological and political education has both opportunities for rich resources and severe challenges.

[0003] At present, the problems of ideological and political education are more prominent. The teaching content lacks pertinence, ignores the differences between students of different majors, and adopts a unified teaching model. However, students are in the information age and are full of expectations for fresh and relevant knowledge. The existing ideological and political education content is difficult to meet their needs, resulting in low enthusiasm and participation in learning. This greatly reduces the teaching effect of ideological and political education. For this reason, a real-time upgrade system for ideological and political content based on big data environment is proposed. Summary of the Invention

[0004] The purpose of the present invention is to provide a real-time ideological and political content upgrade system based on a big data environment to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a real-time ideological and political content upgrade system based on a big data environment, comprising a registration module, a collection module, a data storage platform, an analysis and evaluation module, and a resource optimization module; The registration module is used to register student information, including name, student ID number, and grade. After students complete registration, they are divided into different grade groups based on the grade information entered and stored in the data storage platform. The collection module sends the collected ideological and political data to the data storage platform for storage; the collection module includes: current affairs collection unit, academic situation collection unit, and public opinion collection unit; ideological and political data includes: current affairs information, academic situation information, and ideological and political public opinion information; The data storage platform uses grade as the basis for classification and creates ideological and political update libraries for each grade. Each grade's ideological and political update library includes a current affairs information resource library, a student information resource library, and an ideological and political public opinion information resource library. The analysis and evaluation module analyzes the ideological and political data collected by the current affairs collection unit, the academic situation collection unit, and the public opinion collection unit in the database to obtain the current affairs value, the academic situation heat value, and the public opinion comprehensive value; The resource optimization module analyzes the number of students in each grade and the average weekly duration of ideological and political teaching, obtains the number of weekly recommended articles, and analyzes the proportion of scores, average scores, score values in the test papers, and the number of weekly recommended articles in the weekly test of current affairs information, learning situation information, and ideological and political public opinion information to obtain the number of recommended articles for current affairs information, learning situation information, and ideological and political public opinion information. For each article of current affairs information, learning situation information, and ideological and political public opinion information, a corresponding number of articles are selected in descending order according to their respective current affairs values, learning situation heat values, and public opinion comprehensive values for the update of weekly ideological and political content.

[0006] Preferably, the specific process of the acquisition module for collecting ideological and political data is as follows: The current affairs acquisition unit uses web crawler technology to collect current affairs information on news websites; The learning situation acquisition unit interfaces with intelligent learning terminals through a distributed sensor network to collect learning situation information; The public opinion acquisition unit uses web crawler technology to collect ideological and political public opinion information on network platforms.

[0007] Preferably, the process of the analysis and evaluation module for processing the ideological and political data collected by the current affairs acquisition unit to obtain the current affairs value is as follows: For each piece of current affairs information, the duration from the release time to the current time is recorded as the timeliness duration ST. Obtain the reading volume yd, comment volume pl, and reposting volume zf of the current affairs information on the news website, and after normalization processing, use the formula GZ = yd×a1 + pl×a2 + zf×a3 to obtain the attention value GZ, where a1, a2, and a3 are preset weight coefficients; Use natural language processing technology to extract the core keywords of the current affairs information, obtain the core keyword library of the current affairs information, and convert the core keyword library of the current affairs information into set A; Extract keywords from the ideological and political curriculum outlines of each grade to form the outline keyword library of each grade, and convert the outline keyword library of each grade into a set, denoted as set Bi, i = 1, 2,..., n, where n is the total number of grades; Calculate the number of intersection elements between set A and set Bi, denoted as the intersection element value, and calculate the number of union elements between set A and set Bi, denoted as the union element value. By dividing the intersection element value by the union element value, obtain the timeliness and thinking matching value SP; For each grade, after normalizing the timeliness duration ST, attention value GZ, and timeliness and thinking matching value SP corresponding to each piece of current affairs information, use the formula: to obtain the current affairs value SGZ, where w1, w2, and w3 are preset weight coefficients.

[0008] Preferably, the process of the analysis and evaluation module processing the ideological and political data collected by the learning situation collection unit to obtain the learning situation heat value is as follows: For each type of learning situation information corresponding to different grades, respectively count the average learning duration of all students in that grade for this learning situation information within the most recent week, denoted as the actual average duration. Preset the ideal learning duration. By dividing the actual average duration by the preset ideal learning duration, obtain the learning hour rate XL. The larger the learning hour rate, the more interested the students are in the resource content, and the stronger their learning willingness and internal driving force; Obtain the number of posts FY and the number of likes DZ in the learning situation information discussion area within the most recent week; after normalizing the learning hour rate XL, the number of posts FY, and the number of likes DZ, use the formula: XRD = XL × k1 + FY × k2 + DZ × k3 to obtain the learning situation heat value XRD, where k1, k2, and k3 are preset weight coefficients.

[0009] Preferably, the process of the analysis and evaluation module processing the ideological and political data collected by the public opinion collection unit to obtain the comprehensive public opinion value is as follows: For each piece of ideological and political public opinion information, use natural language processing technology to extract keywords, obtain the ideological and political public opinion keyword library, and convert the ideological and political public opinion keyword library into a set C; by calculating the number of intersection elements between the set C and the set Bi, obtain the public opinion intersection value; For each grade, preset the public opinion intersection threshold, and compare the public opinion intersection value of each piece of ideological and political public opinion information with the corresponding threshold. If the public opinion intersection value of the ideological and political public opinion information is greater than the corresponding threshold, mark this piece of ideological and political public opinion information as the public opinion material of that grade; For the ideological and political public opinion information marked as public opinion material within each grade, use sentiment analysis technology to analyze each sentence of the public opinion material text, and assign corresponding scores according to the sentiment intensity of the words used. The sentiment intensity assignment method is: very positive is +2, positive is +1, neutral is 0, negative is -1, very negative is -2; calculate the average sentiment score of the public opinion material to obtain the sentiment tendency value QZ; Use natural language processing technology to judge the sentiment tendency of each comment in the comment area of the online platform for the public opinion material within the most recent week, and divide the comments into positive, negative, and neutral; use the same method to judge the sentiment tendency of the public opinion material itself, compare the sentiment tendency of each comment with the sentiment tendency of the material, count the number of comments consistent with the sentiment tendency of the material to obtain the sentiment resonance number, and record the total number of comments at the same time. By dividing the sentiment resonance number by the total number of comments, obtain the sentiment resonance degree QG; Statistically analyze the reading volume, reposting volume, and like volume of public opinion materials on the online platform in the most recent week. Multiply the reading volume by the coefficient b1, add the reposting volume multiplied by the coefficient b2, and add the like volume multiplied by the coefficient b3 to obtain the communication heat value CB, where b1, b2, and b3 are preset coefficient factors and b1 + b2 + b3 = 1; After normalizing the sentiment tendency value QZ, the sentiment resonance degree QG, and the communication heat value CB, use the formula: YQZ = QZ×r1 + QG×r2 + CB×r3 to obtain the comprehensive public opinion value YQZ, where r1, r2, and r3 are preset weight coefficients.

[0010] Preferably, the specific process of the resource optimization module analyzing the recommended number of current affairs information articles, the recommended number of learning situation information articles, and the recommended number of ideological and political public opinion information articles for each grade is as follows: For each grade, taking one week as the ideological and political content update cycle, count the number of students in the grade, denoted as the student number XR of the grade level. At the same time, count the average weekly ideological and political teaching duration of the grade, denoted as the ideological and political teaching duration SC; use the formula: ZTS = XR×c1 + SC×c2 to obtain the total resource recommendation value ZTS, where c1 and c2 are preset weight coefficients; preset multiple total resource recommendation value intervals, and each total resource recommendation value interval corresponds to a total number of weekly resource recommendation articles. By matching the total resource recommendation value with the preset multiple total resource recommendation value intervals, output the total number of weekly resource recommendation articles corresponding to the grade, and denote it as the weekly recommended article number; Obtain the score proportion SB of current affairs information in the most recent weekly test, the average score SJ of grade students in current affairs information, and the score value SZ of current affairs information in the test paper. Use the formula: G1 = SB×d1 + SJ / SZ×d2 to obtain the current affairs efficacy value G1, where d1 and d2 are preset weight coefficients; mark the calculation method of calculating the current affairs efficacy value as the efficacy calculation method. Similarly, use the efficacy calculation method to conduct efficacy analysis on learning situation information and ideological and political public opinion information to obtain the learning situation efficacy value G2 and the public opinion efficacy value G3; Use the formula: to obtain the recommended number of current affairs information articles VG1, the recommended number of learning situation information articles VG2, and the recommended number of ideological and political public opinion information articles VG3.

[0011] Preferably, for each current affairs information article, learning situation information article, and ideological and political public opinion information article, respectively screen the corresponding number of articles from high to low according to their respective current affairs values, learning situation heat values, and comprehensive public opinion values for the update of weekly ideological and political content. The specific process is as follows: Sort each current affairs information article, learning situation information article, and ideological and political public opinion information article from high to low according to their respective current affairs values, learning situation heat values, and comprehensive public opinion values; For each current affairs information article, according to the sorting result, select the top VG1 current affairs information articles with higher current affairs values from the current affairs information resource library as the content for the update of this week's ideological and political content; For each piece of learning situation information, according to the sorting result, select the top VG2 pieces of learning situation information with higher learning situation heat values from the learning situation information resource library as the content for updating this week's ideological and political content; For each piece of ideological and political public opinion information, according to the sorting result, select the top VG3 pieces of ideological and political public opinion information with higher comprehensive public opinion values from the ideological and political public opinion information resource library as the content for updating this week's ideological and political content.

[0012] Compared with the prior art, the beneficial effects of the present invention are: (1). The real-time upgrade system for ideological and political content based on the big data environment determines the current affairs value SGZ by using the analysis and evaluation module to calculate the timeliness duration, attention value, and timeliness-thinking matching value of current affairs information; it takes into account the release time and popularity of current affairs information.

[0013] (2). The real-time upgrade system for ideological and political content based on the big data environment obtains the learning hour rate by counting the average learning duration of students, and calculates the learning situation heat value in combination with the number of speeches and likes in the discussion area; this process accurately reflects the students' interest degree and learning willingness for different learning situation information, effectively solves the problem of lack of pertinence in teaching content, and stimulates the students' learning enthusiasm.

[0014] (3). When processing ideological and political public opinion information, the real-time upgrade system for ideological and political content based on the big data environment calculates the emotional tendency value, emotional resonance degree, and communication heat value, and then obtains the comprehensive public opinion value; this not only ensures the positive guidance of ideological and political education content, but also meets the students' needs for fresh and relevant knowledge, and improves the teaching effect of ideological and political education.

[0015] (4). The real-time upgrade system for ideological and political content based on the big data environment, the resource optimization module, through multi-dimensional data collection and analysis and evaluation, determines the current affairs value by using parameters such as timeliness duration, attention value, and timeliness-thinking matching value, calculates the learning situation heat value based on the average learning duration and speech like data, obtains the comprehensive public opinion value by means of emotional tendency, resonance degree, and communication heat, and combines factors such as the number of students in each grade, teaching duration, and weekly test scores to accurately calculate the recommended number of pieces of various types of information, and screen out ideological and political content that meets the needs of students in each grade from a large amount of information, effectively solving the problem of difficult to stimulate students' interest and improving the teaching effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is the flow chart of the present invention; DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] Embodiment 1

[0019] Please refer to Figure 1 , the present invention provides a real-time upgrade system for ideological and political content based on the big data environment, including a registration module, a data storage platform, a collection module, an analysis and evaluation module, and a resource optimization module; The registration module is communicatively connected to the data storage platform and is used for registering student information, where the student information includes: name, student ID number, and grade; after the student completes information registration, according to the entered grade information, the students are divided into different grade groups and stored in the data storage platform; The collection module is communicatively connected to the data storage platform and sends the collected ideological and political data to the data storage platform; the collection module includes: a current affairs collection unit, a learning situation collection unit, and a public opinion collection unit; the ideological and political data includes: current affairs information, learning situation information, and ideological and political public opinion information; The current affairs collection unit uses web crawler technology to collect current affairs information on news websites; The learning situation collection unit docks with intelligent learning terminals through a distributed sensor network to collect learning situation information; the intelligent learning terminals include: intelligent tablets, intelligent notebooks, intelligent watches, and classroom interactive answering devices; The public opinion collection unit uses web crawler technology to collect ideological and political public opinion information on network platforms, and the network platforms include: Weibo, WeChat, and Douyin; The data storage platform creates ideological and political update libraries for each grade based on the grade as the classification basis. For each grade's ideological and political update library, there are independent storage resource libraries for current affairs information, learning situation information, and ideological and political public opinion information, namely: current affairs information resource library, learning situation information resource library, and ideological and political public opinion information resource library; The analysis and evaluation module analyzes the ideological and political data collected by the current affairs collection unit, the learning situation collection unit, and the public opinion collection unit stored in the database to obtain a current affairs value, a learning situation heat value, and a comprehensive public opinion value. The operation process is as follows: The process of obtaining the current affairs value by processing the ideological and political data collected by the current affairs collection unit is as follows: For each piece of current affairs information, the time duration from its release moment to the current moment is recorded as the timeliness duration ST, Obtain the reading volume yd, comment volume pl, and forwarding volume zf of current affairs information on news websites, normalize them, and use the formula GZ = yd × a1 + pl × a2 + zf × a3 to obtain the attention value GZ, where a1, a2, and a3 are preset weight coefficients; Using natural language processing technology, we extract the core keywords of current affairs information to obtain a core keyword library of current affairs information, and then transform the core keyword library of current affairs information into set A; the core keywords mainly include socialist core values, patriotism, and the spirit of the rule of law; Keywords are extracted from the ideological and political course syllabus of each grade to form a keyword library of each grade syllabus. For each grade, the syllabus keyword library is converted into a set, recorded as set Bi, i = 1, 2, ..., n, where n is the total number of grades; Calculate the number of intersection elements between set A and set Bi, record it as the intersection element value, record the number of union elements between set A and set Bi as the union element value, and obtain the time-thinking matching value SP by dividing the intersection element value by the union element value; For each grade, after normalizing the timeliness duration ST, attention value GZ, and current thinking matching value SP corresponding to each piece of current affairs information, the formula is used: , get the current affairs value SGZ, where w1, w2, and w3 are preset weight coefficients. The larger the current affairs value SGZ, the more suitable the current affairs information is for updating the ideological and political content of the grade; The process of processing the ideological and political data collected by the learning situation collection unit to obtain the learning situation heat value is as follows: For each type of learning information corresponding to different grades, calculate the average learning time of all students in that grade for that learning information in the past week, record it as the actual average learning time, and preset the ideal learning time. By dividing the actual average learning time by the preset ideal learning time, we get the learning time ratio XL. A larger learning time ratio indicates that students are more interested in the resource content and have a stronger willingness and internal motivation to learn. Obtain the number of speeches FY and the number of likes DZ in the academic information discussion area within the past week; normalize the study hour rate XL, the number of speeches FY, and the number of likes DZ, and use the formula: XRD=XL×k1+FY×k2+DZ×k3 to obtain the academic information heat value XRD, where k1, k2, and k3 are preset weight coefficients. The larger the academic information heat value, the more suitable it is for updating the ideological and political content of the grade; The ideological and political data collected by the public opinion collection unit are processed to obtain the comprehensive value of public opinion as follows: For each piece of ideological and political public opinion information, natural language processing technology is used to extract keywords, obtaining an ideological and political public opinion keyword library, and converting the ideological and political public opinion keyword library into set C; by calculating the number of intersection elements between set C and set Bi, the public opinion intersection value is obtained; For each grade, a public opinion intersection threshold is preset, and the public opinion intersection value of each piece of ideological and political public opinion information is compared with the corresponding threshold. If the public opinion intersection value of the ideological and political public opinion information is greater than the corresponding threshold, then this piece of ideological and political public opinion information is marked as the public opinion material of that grade; For the ideological and political public opinion information marked as public opinion material within each grade, sentiment analysis technology is used to analyze each sentence of the public opinion material text, and corresponding scores are assigned according to the sentiment intensity of the words used. The sentiment intensity assignment method is as follows: very positive is +2, positive is +1, neutral is 0, negative is -1, and very negative is -2; calculate the average sentiment score of the public opinion material to obtain the sentiment tendency value QZ; the larger the sentiment tendency value, the more it indicates that the public opinion material has a positive and upward value and attitude fit, and is more conducive to transmitting positive energy and guiding correct ideological concepts; Using natural language processing technology, judge the sentiment tendency of each comment in the comment area of the network platform for the public opinion material within the most recent week, and classify the comments into positive, negative, and neutral; use the same method to judge the sentiment tendency of the public opinion material itself, compare the sentiment tendency of each comment with the sentiment tendency of the material, count the number of comments consistent with the sentiment tendency of the material to obtain the sentiment resonance number, and record the total number of comments at the same time. By dividing the sentiment resonance number by the total number of comments, the sentiment resonance degree QG is obtained; Statistically analyze the reading volume, forwarding volume, and like volume of the public opinion material on the network platform within the most recent week, multiply the reading volume by coefficient b1, add the forwarding volume multiplied by coefficient b2, and add the like volume multiplied by coefficient b3 to obtain the communication heat value CB, where b1, b2, and b3 are preset coefficient factors, and b1 + b2 + b3 = 1; After normalizing the sentiment tendency value QZ, sentiment resonance degree QG, and communication heat value CB, use the formula: YQZ = QZ × r1 + QG × r2 + CB × r3 to obtain the public opinion comprehensive value YQZ, where r1, r2, and r3 are preset weight coefficients; The resource optimization module analyzes the number of students in each grade and the average weekly ideological and political teaching duration to obtain the number of recommended articles per week. Based on the proportion of scores, average scores, score values in the test paper, and the number of recommended articles per week in the current political information, learning situation information, and ideological and political public opinion information weekly test, analyze to obtain the number of recommended articles for current political information, learning situation information, and ideological and political public opinion information. For each piece of current political information, learning situation information, and ideological and political public opinion information, screen the corresponding number of articles from high to low according to their respective corresponding current political values, learning situation heat values, and public opinion comprehensive values for the weekly update of ideological and political content. The specific process is as follows: For each grade, taking one week as the ideological and political content update cycle, count the number of students in the grade, denoted as the student number XR of the grade level. At the same time, count the average weekly teaching duration of ideological and political education in the grade, denoted as the teaching duration SC of ideological and political education; use the formula: ZTS = XR × c1 + SC × c2 to obtain the total resource promotion value ZTS, where c1 and c2 are preset weight coefficients; preset multiple total resource promotion value intervals, and each total resource promotion value interval corresponds to a total number of recommended resources per week. By matching the total resource promotion value with the preset multiple total resource promotion value intervals, output the total number of recommended resources per week corresponding to the grade, and denote it as the weekly recommended article count; Obtain the score proportion SB of current affairs information in the last weekly test, the average score SJ of the grade students in current affairs information, and the score value SZ of current affairs information in the test paper. Use the formula: G1 = SB × d1 + SJ / SZ × d2 to obtain the current affairs effectiveness value G1, where d1 and d2 are preset weight coefficients; mark the calculation method of calculating the current affairs effectiveness value as the effectiveness calculation method. Similarly, use the effectiveness calculation method to conduct effectiveness analysis on the learning situation information and ideological and political public opinion information to obtain the learning situation effectiveness value G2 and the public opinion effectiveness value G3; Use the formula: to obtain the recommended article count VG1 of current affairs information, the recommended article count VG2 of learning situation information, and the recommended article count VG3 of ideological and political public opinion information; Sort each piece of current affairs information, learning situation information, and ideological and political public opinion information from high to low according to their respective corresponding current affairs values, learning situation heat values, and public opinion comprehensive values; For each piece of current affairs information, according to the sorting result, select the top VG1 pieces of current affairs information with higher current affairs values from the current affairs information resource library as the content for this week's ideological and political content update; For each piece of learning situation information, according to the sorting result, select the top VG2 pieces of learning situation information with higher learning situation heat values from the learning situation information resource library as the content for this week's ideological and political content update; For each piece of ideological and political public opinion information, according to the sorting result, select the top VG3 pieces of ideological and political public opinion information with higher public opinion comprehensive values from the ideological and political public opinion information resource library as the content for this week's ideological and political content update.

[0020] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The ideological and political content real-time upgrade system based on the big data environment includes a registration module, a data storage platform, a collection module, an analysis and evaluation module, and a resource optimization module, and is characterized in that: The registration module is used for registering students' information, and the students' information includes: name, student ID number, and grade; after the students complete the information registration, they are divided into different grade groups according to the entered grade information and stored in the data storage platform; The collection module sends the collected ideological and political data to the data storage platform for storage; the collection module includes: a current affairs collection unit, a learning situation collection unit, and a public opinion collection unit; the ideological and political data includes: current affairs information, learning situation information, and ideological and political public opinion information; The data storage platform creates ideological and political update libraries for each grade based on the grade as the classification basis. For each grade's ideological and political update library, there are a current affairs information resource library, a learning situation information resource library, and an ideological and political public opinion information resource library; The analysis and evaluation module analyzes the ideological and political data collected by the current affairs collection unit, the learning situation collection unit, and the public opinion collection unit in the database to obtain a current affairs value, a learning situation heat value, and a public opinion comprehensive value; The resource optimization module analyzes the number of students in each grade and the average weekly ideological and political teaching duration to obtain the number of recommended articles per week. According to the current affairs information, learning situation information, and the score ratios, average scores, score values in the test papers, and the number of recommended articles per week in the ideological and political public opinion information weekly test, it analyzes to obtain the number of recommended articles for current affairs information, the number of recommended articles for learning situation information, and the number of recommended articles for ideological and political public opinion information. For each article of current affairs information, learning situation information, and ideological and political public opinion information, it screens the corresponding number of articles from high to low according to their respective current affairs values, learning situation heat values, and public opinion comprehensive values for the weekly update of ideological and political content.

2. The real-time upgrade system for ideological and political content based on the big data environment according to claim 1, characterized in that: The specific process of the collection module for collecting ideological and political data is as follows: The current affairs collection unit uses web crawler technology to collect current affairs information on news websites; The learning situation collection unit docks with intelligent learning terminals through a distributed sensor network to collect learning situation information; The public opinion collection unit uses web crawler technology to collect ideological and political public opinion information on network platforms.

3. The real-time upgrade system for ideological and political content based on the big data environment according to claim 2, characterized in that: The process of the analysis and evaluation module processing the ideological and political data collected by the current affairs collection unit to obtain the current affairs value is as follows: For each piece of current affairs information, the duration from the release time to the current time is recorded as the timeliness duration ST; Obtain the reading volume yd, comment volume pl, and repost volume zf of the current affairs information on the news website. After normalization processing, use the formula GZ = yd×a1 + pl×a2 + zf×a3 to obtain the attention value GZ, where a1, a2, and a3 are preset weight coefficients; Use natural language processing technology to extract the core keywords of the current affairs information to obtain the core keyword library of the current affairs information, and convert the core keyword library of the current affairs information into a set A; Extract keywords from the ideological and political curriculum outlines of each grade to form the outline keyword libraries of each grade. For each grade, convert its outline keyword library into a set, denoted as set Bi, i = 1, 2,..., n, and n is the total number of grades; Calculate the number of intersection elements between set A and set Bi, denoted as the intersection element value. Denote the number of union elements between set A and set Bi as the union element value. By dividing the intersection element value by the union element value, the time-thought matching value SP is obtained. For each grade, after normalizing the timeliness duration ST, attention value GZ, and timeliness thinking matching value SP corresponding to each current affairs information, the formula: is used to obtain the current affairs value SGZ, where w1, w2, and w3 are preset weight coefficients.

4. The real-time upgrade system of ideological and political content based on the big data environment according to claim 3, characterized in that: The process of the analysis and evaluation module processing the ideological and political data collected by the learning situation collection unit to obtain the learning situation heat value is as follows: For each type of learning situation information corresponding to different grades, respectively count the average learning duration of all students in this grade for this learning situation information in the recent week, denoted as the actual average duration. Preset the ideal learning duration. By dividing the actual average duration by the preset ideal learning duration, the learning hour rate XL is obtained. The larger the learning hour rate, the more interested the students are in the resource content, and the stronger the learning willingness and internal driving force. Obtain the number of speeches FY and the number of likes DZ in the learning situation information discussion area in the recent week. After normalizing the learning hour rate XL, the number of speeches FY, and the number of likes DZ, use the formula: XRD = XL×k1 + FY×k2 + DZ×k3 to obtain the learning situation heat value XRD, where k1, k2, and k3 are preset weight coefficients.

5. The real-time upgrade system of ideological and political content based on the big data environment according to claim 4, characterized in that: The process of the analysis and evaluation module processing the ideological and political data collected by the public opinion collection unit to obtain the comprehensive public opinion value is as follows: For each piece of ideological and political public opinion information, use natural language processing technology to extract keywords to obtain the ideological and political public opinion keyword library, and convert the ideological and political public opinion keyword library into set C. By calculating the number of intersection elements between set C and set Bi, the public opinion intersection value is obtained. For each grade, preset the public opinion intersection threshold. Compare the public opinion intersection value of each piece of ideological and political public opinion information with the corresponding threshold. If the public opinion intersection value of the ideological and political public opinion information is greater than the corresponding threshold, mark this piece of ideological and political public opinion information as the public opinion material of this grade. For the ideological and political public opinion information marked as public opinion material within each grade, use sentiment analysis technology to analyze each sentence of the public opinion material text, and assign corresponding scores according to the sentiment intensity of the words used. The sentiment intensity assignment method is: very positive is +2, positive is +1, neutral is 0, negative is -1, very negative is -2. Calculate the average sentiment score of the public opinion material to obtain the sentiment tendency value QZ. Use natural language processing technology to judge the sentiment tendency of each comment in the comment area of the network platform for the public opinion material in the recent week, and divide the comments into positive, negative, and neutral. Use the same method to judge the sentiment tendency of the public opinion material itself. Compare the sentiment tendency of each comment with the sentiment tendency of the material, count the number of comments consistent with the sentiment tendency of the material to obtain the sentiment resonance number, and record the total number of comments at the same time. By dividing the sentiment resonance number by the total number of comments, the sentiment resonance degree QG is obtained. Count the reading volume, reposting volume, and number of likes of the public opinion material on the network platform in the recent week. Multiply the reading volume by the coefficient b1, add the reposting volume multiplied by the coefficient b2, and add the number of likes multiplied by the coefficient b3 to obtain the communication heat value CB, where b1, b2, and b3 are preset coefficient factors, and b1 + b2 + b3 = 1. After normalizing the sentiment tendency value QZ, the emotional resonance degree QG, and the dissemination heat value CB, the formula: YQZ = QZ×r1 + QG×r2 + CB×r3 is used to obtain the comprehensive public opinion value YQZ, where r1, r2, and r3 are preset weight coefficients.

6. The real-time upgrade system for ideological and political content based on the big data environment according to claim 5, characterized in that: The specific process of the resource optimization module analyzing the recommended number of current affairs information articles, the recommended number of learning situation information articles, and the recommended number of ideological and political public opinion information articles for each grade is as follows: For each grade, taking one week as the ideological and political content update cycle, the number of students in the grade is counted and denoted as the student number XR of the grade. At the same time, the average weekly ideological and political teaching duration of the grade is counted and denoted as the ideological and political teaching duration SC; the formula: ZTS = XR×c1 + SC×c2 is used to obtain the total resource recommendation value ZTS, where c1 and c2 are preset weight coefficients; Multiple total resource recommendation value intervals are preset, and each total resource recommendation value interval corresponds to a total number of weekly resource recommendation articles. By matching the total resource recommendation value with the preset multiple total resource recommendation value intervals, the total number of weekly resource recommendations corresponding to the grade is output and denoted as the weekly recommended number of articles; Obtain the score proportion SB of current affairs information in the most recent weekly test, the average score SJ of the grade students in current affairs information, and the score value SZ of current affairs information in the test paper. Use the formula: G1 = SB×d1 + SJ / SZ×d2 to obtain the current affairs efficiency value G1, where d1 and d2 are preset weight coefficients; mark the calculation method of calculating the current affairs efficiency value as the efficiency calculation method. Similarly, use the efficiency calculation method to conduct efficiency analysis on the learning situation information and the ideological and political public opinion information to obtain the learning situation efficiency value G2 and the public opinion efficiency value G3; Using the formula: , the number of recommended current affairs information articles VG1, the number of recommended learning situation information articles VG2, and the number of recommended ideological and political public opinion information articles VG3 are obtained.

7. The real-time upgrade system for ideological and political content based on the big data environment according to claim 6, characterized in that: For each current affairs information article, learning situation information article, and ideological and political public opinion information article, screen the corresponding number of articles from high to low according to their respective current affairs values, learning situation heat values, and comprehensive public opinion values for the update of weekly ideological and political content. The specific process is as follows: Sort each current affairs information article, learning situation information article, and ideological and political public opinion information article from high to low according to their respective current affairs values, learning situation heat values, and comprehensive public opinion values; For each current affairs information article, according to the sorting result, select the top VG1 current affairs information articles with higher current affairs values from the current affairs information resource library as the content for the update of this week's ideological and political content; For each learning situation information article, according to the sorting result, select the top VG2 learning situation information articles with higher learning situation heat values from the learning situation information resource library as the content for the update of this week's ideological and political content; For each ideological and political public opinion information article, according to the sorting result, select the top VG3 ideological and political public opinion information articles with higher comprehensive public opinion values from the ideological and political public opinion information resource library as the content for the update of this week's ideological and political content.

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