Search

This paper focuses on the feasible path to enhance the traditional cultural literacy of college students and analyzes the role of teachers’ teaching ability to enhance students’ cultural literacy in college cultural literacy education. Based on the enhancement of college students’ cultural literacy ideologically, morally, behaviorally and psychologically by college cultural literacy education, the primary evaluation indexes of teachers’ teaching ability are set, including basic ability, teaching method, teaching content, teaching attitude and teaching effect. Using the fuzzy C-mean clustering algorithm, we preprocess the teachers’ basic information data, select the evaluation indexes for teachers’ teaching, and complete the clustering optimization. According to the FCM clustering results, teachers’ teaching was classified into three categories, among which the first category T1 = 0.885, T3 = 0.923, T4 = 0.742, indicating that teachers in this category should adjust their working status to achieve the optimal teaching effect and effectively improve students’ cultural literacy.

This paper proposes a model of photography teaching literacy based on cross-cultural teaching by designing and implementing a photography curriculum based on “recording the fading colors of Suzhou” and combining it with cross-cultural teaching. Then, we set the gray correlation factor series, transformed the gray correlation factor series into a dimensionless pure quantity through mathematical transformation, calculated the correlation coefficients between the comparison series and the reference series, and applied the gray correlation analysis to analyze the intercultural photography teaching literacy index system. The results showed that teachers of different genders showed significant differences in intercultural photography teaching ability (F=2.774, p=0007

The digitization inheritance of national sports culture is an inevitable requirement of the new era, so studying its communication characteristics in the digital age is necessary. In this paper, the cognitive semantics of its cultural imagery is obtained based on the analysis of the connotation of national sports culture, and the informational imagery is extracted based on the cultural semantic analysis. The fast gradient descent algorithm optimizes the sampling and dissemination process of information during establishing the SIRI communication network for cultural imagery. Changes in the state and popularity of the dissemination nodes were explored by changing the external social environment and the input of the information carrier. When the probability of social environment increases from 0.15 to 0.95, the node with state S transforms into an information dissemination node faster and finally tends to a stable value of 0. In terms of information carriers, the degree of the flow of video dissemination will be graded higher than other carriers, and the popularity of video dissemination is 2.45%, 3.14%, and 5.21% higher than audio, image, and text, respectively, when the dissemination reaches the 4th generation. The information dissemination model optimized using a gradient descent algorithm can accurately capture the dissemination characteristics of national sports culture, thus proposing a better information transmission path.

By exploring the characteristics of Marxism’s Chineseization, an innovative path for cultural construction development is proposed. Based on the composition of cultural carriers of Marxist Chineseization, this paper constructs the social cognitive network of Marxist Chineseization. The structural characteristics of the network are studied based on node influence, proximity centrality, etc., thus proposing a scale-free model in the social network and adopting Pearson coefficients to characterize the relevance of the nodes. Accordingly, the process of cultural identity and the evolution of cultural carriers in the Chineseization of Marxism are analyzed, and the characteristics of cultural viewpoints are analyzed. In the construction of institutional culture, the cultural identity increased from 0.44 in 1980 to 0.832 in 2019. In constructing spiritual culture, the cultural identity increased from 0.389 in 1980 to 0.822 in 2019. With the dissemination and localization of Marxist theories in China, cultural identity is a process of zigzagging.

This paper explores ways to preserve the intangible cultural heritage of Korean sports inherited by colleges and universities through digital technology and RBM neurons. The non-heritage information and images collected through the method of data collection and data storage are presented in 3D with the help of a neural network. The protection of intangible cultural heritage is achieved by using data restoration technology to trace the past and break the limitations of time and space. Using artificial intelligence technology, a database of intangible cultural heritage can be built, and different types of intangible cultural heritage can be divided using a neural network. The characteristics of Korean sports culture are summarized by analyzing intangible cultural items related to Korean sports. The results show that the feature extraction method incorporating RBM has the highest extraction rate of strong and healthy in sports, with an extraction rate of 0.8, the extraction rate of mighty features is 0.75, and the extraction rate of strength degree of sports is 0.75. The intangible culture of Korean sports is promoted and developed through this paper’s research to a certain extent.

This paper aims to explore the correlation and influencing factors between cultural identity and historical development using the historiometric method. Meanwhile, a genetic algorithm is used to collect historical data and quantitative indicators of cultural identity, which is then combined to construct a mathematical model of historical development and cultural identity. The optimization of the model involves using genetic algorithms to find the best match and optimal solution. The historical measures score up to 9.5 due to the significant impact of cultural identity on historical development. This study provides new methods and perspectives for a deeper understanding of the interaction between cultural identity and historical development and is of great significance in promoting the development of historical research and cultural identity research.

This paper first explores the revitalization of national traditional sports and cultural innovation and identifies the key to the definition of national traditional sports. Secondly, it explores the operation mechanism of sports and cultural co-innovation and proposes pathways for sports and cultural innovation. Then, the relationship between traditional ethnic sports and sports culture innovation was studied using the BERT model in the deep learning model. Finally, a controlled experiment was designed to test the comparison of students’ performance before and after learning about sports culture innovation, and the study showed that the performance was improved by 14.3506 and 13.6275, respectively, and that learning about sports culture innovation was effective in improving students’ deep learning ability. Testing the role of three different algorithms on the revitalization and cultural innovation of national traditional sports, the accuracy of the four indicators of BERT is 0.75, 0.78, 0.88 and 0.98, respectively, which is in the first place, and the accuracy of BERT is higher.

This paper proposes the design of the Zhejiang opera culture gene map using the Zhejiang opera culture gene and gene map. Secondly, it focuses on the application of data mining algorithms in managing opera culture resources, including indexing and querying of dissemination track data and mining Zhejiang opera culture data resources. Finally, the application effect of data mining in Zhejiang opera culture gene mapping is demonstrated through an example analysis. The results show that for the multi-valued attribute dataset of trajectory data of Zhejiang opera culture, the execution time of the optimized algorithm is reduced by 848 ms under a 1% support rate and 88 ms under a 10% support rate compared with the Apriori algorithm. This paper reveals the inner connections and characteristics of Zhejiang opera culture through a data mining algorithm for cultural gene mapping, providing a scientific basis.

This paper describes the dynamic propagation process of the influence of public service advertisements (PSAs) using the information dissemination model and proposes a click probability function by modeling the click rate of advertisements, which is solved by a heuristic method. The EPR advertisement recommendation algorithm is selected to simulate the push process of the advertisement, and the experimental performance is analyzed. Analyze the presentation of Shaanxi regional culture and the network mobilization mechanism model of enterprise public service advertisement, predict and analyze the click rate of public service advertisement broadcasting, and emphasize the trust analysis of the audience. Variables such as the number of effective viewing of advertisements, the number of link clicks, the number of likes, and the amount of placement are selected to carry out descriptive analysis and correlation analysis of the effect of PSAs on Shaanxi regional culture. From the correlation coefficient matrix, it can be seen that the correlation coefficients between the explanatory variables take smaller values and are at the level below 0.11, and the number of likes has significant positive correlation coefficients with the indicators of advertisement effect at each stage. Thus it can be verified that the social attributes of advertisements play a positive role in the effect of advertisements.

This paper describes the complexity and uncertainty of traditional culture and kindergarten drama and evaluates the impact on the integration by providing a reasonable measure of the degree of fuzziness of the fuzzy numerical analysis algorithm. Using the affiliation function for traditional culture and kindergarten theater for measurement, the fuzzy set affiliation function curve determines the corresponding element of the center of gravity of the theater, and that traditional culture element is used as the exact output value. It was found that the proportion of kindergarten drama education activities in appreciating drama works accounted for 56.75%, and the corresponding standard deviation in feeling traditional culture was the highest at 3.916. The importance of drama education activities with traditional culture as a carrier in the core literacy of young children cannot be ignored.

The digitization of intangible cultural heritage provides the basis for its protection and inheritance. In this paper, we extracted the classes and interrelationships corresponding to each element for the content of Yi Intangible Cultural Heritage, constructed the data model and accomplished the relationship abstraction of different classes. Based on the structure of different data classes, the correlation between spatial change and non-heritage status is explored. The data model is proposed to cluster non-heritage data based on SWC-WMD distance, which improves the similarity calculation based on WMD distance. The association analysis of non-heritage item classes was performed using Yi folk dance as an example, and the overall non-heritage data was analyzed by clustering. In Yi folk dance, the association formed a network correlation graph with N2, N3, and N12 as the three main centers, in which the dance class items associated with N2, N3, and N12 were 9, 9, and 8, respectively. Mining out the relationships among NH items helps to better the overall NH protection.

In this paper, firstly, we start from the imagery in the poem, excavate the resources of the ideology and politics in the university language poetry, and put forward the feasible path of the integration of the ideology and politics of the university language course and the poetry culture of the family training. The research on poetry culture in university language is conducted using a deep learning model. Based on the deep learning model, keywords in the poetry text are extracted and extended, taking into account the issue of word splitting and lexical annotation. The sequence coding of word vectors is needed so as to construct a poetry generation model based on RNNPG, and then the research and analysis on the concept of ideology and politics of the poetry culture in the university language are carried out. The results show that in terms of model performance, the RNNPG model is 1.17 overall, and the overall generation effect is more ideal compared to other single discriminator generation models. The acceptance level of sophomores is generally above 0.29, which is better than that of freshmen, and the teaching of ancient poems under the perspective of “curriculum politics” is especially necessary to improve their cultural taste and aesthetic interest. This study is conducive to the personalized development of students and the formation of correct concepts.

The development and use of digital mining technology provide new trends for product visual design. This paper identifies the product design system using the product appearance design framework. Digital technology is integrated into the product’s visual style, and the empathy design method is utilized to communicate the product’s culture. Apply fuzzy language summarization algorithm of digital mining technology to calculate user demand data, propose weight calculation method based on fuzzy language summarization results, and set objective weights of product user demand. The design of product visual culture is based on the results of acquiring and parameterizing product users’ perceptual demands, and the design results are evaluated in terms of three-party satisfaction. The average satisfaction values of industrial design experts, automobile appearance researchers, and mass consumers are 4.09, 4.23, and 4.53, respectively, indicating that the visual design results of automobile appearance have a high degree of user satisfaction, which is in line with the expectations of design practice.

A coupling degree model based on rural construction and the rural tourism and culture industry is constructed by analyzing the relationship between the two. The scope of application of the coupling degree is studied, and the framework of the coordination process of the interaction between rural construction and the tourism and culture industry is delineated. The method of dimensionless processing is applied to deal with the raw data to ensure the correctness of model calculations and system analysis. By combining the coupling degree division standard, the rural tourism and culture industry’s coupling degree is divided. The index system of rural tourism culture is constructed according to the principle of the evaluation index system. By analyzing the coupling degree of rural infrastructure and tourism culture industry, relevant development strategies are proposed. The results show that the coupling degree interval corresponding to the transportation facilities from poor to good is (0.2, 0.52), and the coupling degree corresponding to the transportation facilities when they are good is 0.51. The coupling interval corresponding to the dietary conditions from poor to good is (0.27, 0.73).

In this paper, a platform for digital leisure sports services is built using digital information technology in the context of the new economy. Plain Bayesian classification is used to classify sports information based on its features, and the target value is assigned based on the feature vector. The RBF algorithm is introduced to transform the information into measurable data, and the target weights are updated using the energy function. The results indicate that the villagers exercised for 5 hours each day on the platform, and the BMI pass rate of villagers of different age groups exceeded 70%. The digital innovation of leisure sports has a greater effect on the psychology and physiology of villagers and is a strong fit for the prosperity and revitalization of rural culture.

At present, with the strengthening of China’s economic and cultural strength, “Chinese culture” is widely sought after. Therefore, incorporating cultural elements into clothing design can promote the spread of Chinese clothing culture. This paper proposes a classical network model based on the Internet’s background. A modal communication model of the culturalization process is built on this basis to combine the Internet and the network model. The survey and analysis of the effects of clothing culture on comfort and aesthetics of clothing design are being conducted. Consumers have a positive and active attitude towards clothing culture, with 3625 out of 7563 sample comments supporting the communication of clothing culture in the communication effect. The comfort of clothing is a top priority for 139 people when it comes to clothing design. Therefore, the aspect of comfort should be emphasized in clothing design, and the dissemination of clothing culture should be strengthened at the same time.

The purpose of this paper is to analyze the dissemination effect of digital health concepts in dance culture by constructing a prediction model for dance culture information dissemination. It focuses on analyzing the main paths and forms of Internet+dance culture dissemination and constructing the cultural dissemination process of Internet+dance health. The LSTM method is used to extract the states in information dissemination, and the dissemination characteristics of digital health in dance culture are deduced by analyzing the characteristics of the information dissemination sequence. The association between digital health concepts and dance culture dissemination was determined through the trajectory characteristics of information dissemination. The results show that the spreading range of the four types of models rises in an upward trend and is faster when the spreading time round is in the interval of (0,125). The spread range in models in the (150,300) interval is generally higher than the SI model and SEI model. The factor value of whether the video is top or not affects the amount of playback is 0.771***, and the factor value of whether it carries a topic or not is 0.051.

In order to promote the integrated development of culture and the tourism industry, this paper explores the integration of traditional culture and the rural tourism industry. Firstly, a bottom-up knowledge graph construction method is designed based on the DGCN relational extraction model, Muhead-CU-FL-BE entity extraction model and Neo4j high-performance graph database. Then, based on the domain and characteristics of traditional culture and rural tourism industry integration, the knowledge graph of rural traditional culture and tourism industry integration is constructed from three aspects: line results, ontology model and description of this paper. Finally, the performance of the knowledge graph constructed in this paper is tested on the relevant dataset, and the visualization analysis of industrial integration is carried out through the constructed knowledge graph. The results show that the overall performance of the relationship extraction algorithm in this paper is around 0.7, the entity extraction algorithm has the best performance, and the overall performance is around 0.8, and the ratio of the public ancestor nodes of 5 times linking in the 5th and 6th layers is greater than 0.65. The centrality of culture and tourism industry, cultural and tourism fusion, high-quality development, culture and tourism, and industry fusion are 0.78, 0.60, 0.58, and 0.80. The centrality of the keywords is 0.78, 0.60, 0.58, and 0.80, respectively, 1.00, and the strength of the salient values of each keyword is concentrated around 1~3.

This paper constructs a Bayesian network text recognition model based on the Bayesian network and explores the role of Chinese language literature in the dissemination of traditional culture by analyzing the embodiment of traditional culture in Chinese language literature network texts. The collection process of Chinese language and literature data in network text is analyzed from the perspective of textual data interaction. The information of node variables in a Bayesian network is used to determine the mutual relationship between Chinese language literature and traditional culture. The degree of interdependence between Chinese literature and traditional culture can be measured by combining mutual information. The results show that the correct rate of text recognition of the Bayesian text recognition model decreases slightly when the training samples are (100-300), but the correct rate always stays around 0.85, thus reflecting the effectiveness of the network recognition model in this paper. Chinese language literature has a certain role in the dissemination of traditional culture, which proves that Chinese language literature, as a carrier of traditional culture, can improve the dissemination speed of traditional culture. This study focuses on the integration of Chinese literature and traditional communication to improve a new vision.

Silk has evolved a unique silk culture in its long history, and silk patterns have condensed the external aesthetics of silk culture and shown distinctive national characteristics. This paper firstly constructs the cultural communication network of the 17th-18th century Maritime Silk Road through big data technology and uses social network analysis to study the structural characteristics of the cultural and artistic communication network. The MPI multidimensional spatio-temporal communication evolution model is used to delineate the network’s layers further, and exploratory spatial data analysis is introduced to explore the spatio-temporal communication evolution pattern of the network. Finally, in the empirical analysis, 200 years of silk pattern data from 1600-1800 in China were selected to establish four dimensions and 11 indicators data for measurement. A comprehensive MPI multidimensional spatio-temporal propagation evolution model was derived by principal component analysis to derive the contribution of each indicator. The results show that the multidimensional cultural dissemination index of traditional silk pattern culture and art from 1600 to 1800 was 0.7461 and approximated to 0.8, and the dissemination influence was 0.2252, respectively, rising to 97%, indicating that the dissemination of silk pattern culture and art in the 17th-18th centuries was a flourishing trend. The MPI multidimensional spatial and temporal communication evolution model proposed in this paper effectively visualizes and analyzes the communication channels of silk pattern culture and art, which provides a guiding reference for the revival and communication of modern Chinese traditional culture.

First, this paper studies the derivation process of the plain Bayesian classification algorithm in big data technology, which is built based on statistics. Then to make up for the feature independence assumption of plain Bayes, the plain Bayesian classification algorithm based on feature weighting is proposed to be optimized mainly by the Laplace algorithm, which improves the classification accuracy to a certain extent. Finally, based on the connotation and characteristics of health culture in Shaanxi, the formation and development of health culture theory in Shaanxi are clarified, and policy suggestions are proposed for the development problems of health culture in Shaanxi and the development level of cultural industry in Shaanxi province. The analysis of the health culture industry in Shaanxi is based on the vegetative Bayesian classification algorithm. The results show that the cultural service industry in Shaanxi Province achieved an output value of 41.309 billion yuan, accounting for 63.9% of the added value of the cultural industry in the province. The cultural manufacturing industry in Shaanxi accounts for a large gap with the national level, with a difference of 19.3 percentage points. This study combines big data technology and the advantages of Shaanxi’s healthy cultural resources to provide reasonable countermeasure suggestions to promote the transformation of Shaanxi from a large cultural province to a strong cultural province.

The limited nature of logistics and distribution vehicles and the variability of customer acceptance service time limit the service efficiency and quality of logistics and distribution. To optimize a logistics distribution path under capacity and time window constraints, a mathematical model of the problem is first developed in this study, with the lowest cost as the model’s objective function. The logistics distribution issue with soft time windows is then addressed using an ant colony algorithm, and a logistics path optimization strategy based on the maximum minimal ant colony system is suggested. Then, the heuristic function is rebuilt to improve the ant colony algorithm’s solution speed, and the pheromone update approach is included. Finally, experimental approaches are used to test the model’s and optimization algorithm’s efficacy for customer sizes of 30, 50, and 100. The experimental results show that the optimized ant colony algorithm has the best value of 2 for α and 3 for β, which can converge earlier. The improved ant colony algorithm also finds the best solution faster than the conventional ant colony method in just 23 rounds. In the mathematical model of the logistics distribution path optimization issue, this study suggests that the optimized ant colony method has the optimization algorithm’s rationality, efficacy, and stability.

In the Internet era, sports have been given a good opportunity for development, and the increase in sports activities has also led to the continuous improvement of national physical quality. This paper uses a fuzzy algorithm to decompose test cases’ reusability into functionality and portability. Then, we use hierarchical analysis to stratify the required reusability metrics into sub-characteristics and different attributes under sub-characteristics to obtain the weight ratio of each layer of reusability attributes. Then the sub-characteristic metrics are reasonably quantified by numbers to realize the quantitative evaluation of test case functionality and portability and turn the abstract concepts into intuitive numbers to provide users with reference. Finally, with the core of promoting the development of ice and snow sports programs in Chinese colleges and universities, the construction of ice and snow sports on campuses is strengthened according to the advantageous conditions in the region to improve the physical and mental quality of youth and the simultaneous development of science and culture. Using the fuzzy algorithm to analyze the importance of ice and snow sports by school leaders, it is concluded that 68.8% of the base schools do not have relevant management methods, and 56.3% do not have relevant rules and regulations. This study further promotes the reform and development of ice and snow sports in colleges and universities nationwide and also provides a theoretical basis for strengthening the training of ice and snow sports talents nationwide.

With the implementation of a rural revitalization strategy, the management of the rural industrial economy urgently needs further innovation and optimization. In this paper, principal component analysis is used to identify the key factors of the problems of agricultural and industrial economic management in the context of rural revitalization, and potential indicator factors are uncovered through principal component analysis, and these potential factors are used instead of all indicators for more accurate analysis. Meanwhile, the PCA method was combined with a support vector machine to construct a PCA-SVM model, based on which the influence factors of agricultural economic efficiency were measured. The higher the degree of informationization of agricultural management, the greater the influence factor on agricultural economic benefits, and the correlation rate reached 26.85%. The higher the degree of the system construction of agricultural management, the greater the influence factor on agricultural economic efficiency, and the correlation rate reached 32.14%. The higher the degree of improvement of infrastructure construction, the higher the influence factor on agricultural economic efficiency, with a correlation rate of 35.68%. This study can precisely analyze the current problems in the economic management of the agricultural industry and provide effective references for promoting the economic development of rural areas in the context of rural revitalization.

Innovative ideological and political education for college students is to help better students improve their ideological quality and political literacy. In this paper, under the background of big data, the Civic and Political Cloud Education Platform is constructed using big data technology, which is mainly composed of four main parts: model layer, view layer, control layer, and basic services. Student behavior data is collected and analyzed through a collaborative filtering recommendation algorithm under big data collection and analysis technology, and performance simulation analysis is conducted for the Civic and Political Science Cloud Education Platform. From the performance analysis, when the number of concurrent users of the Civic Education Cloud Platform is 80-120, the average transaction processing per second is stable at 10.5 s. From the practicality, the Civic Education Cloud Platform built by big data can effectively explore the value of Civic Education teaching resources. This shows that the Civic and Political Science cloud education platform is an effective way to innovate and develop the ideological and political education of college students, and through this platform, the ideological quality and political literacy of college students can be effectively improved.

This paper first explores the mechanism of marathon information culture dissemination by first calculating the time required for each layer of receivers to obtain the information and further obtaining the upper bound of the time required for the information to travel throughout the dissemination. The maximum allowable number of transmissions is obtained according to the protocol, and the lower bound of the propagation time is further obtained to find the time range of information propagation. Then, the structure of marathon sports culture is studied, and the marathon sports culture is divided into surface, middle and bottom layers, and the marathon spirit is discussed in depth. Finally, the communication effect of marathon sports culture under new media is analyzed in terms of the ways of communication and the comparison of new media and traditional media content. In the comparison between new media and traditional media, for the content of sports material culture in terms of sports architecture or sports sculpture and sports logo or clothing introduction, traditional media accounted for 11.9% and 9.8%, while new media were 3% and 4% more than traditional media. Among the topics and effects, the top three average reads were the topics of event information, registration and recruitment and brand promotion, with 490,963, 91,563 and 773,243 reads, respectively. The rise of new media has promoted the spread and development of marathon sports culture.

Cultural awareness is a context in which the integration and development of traditional arts and crafts can be promoted by establishing an exchange platform. In this paper, the exchange platform is designed through the exploration of traditional handicraft art resources and the study of different classifications. The main points of the platform design and key operational processes are explored based on the analysis of the users’ needs for the traditional handicraft art platform. In response to the lack of accuracy of the traditional buddy recommendation algorithm, a buddy recommendation algorithm incorporating user interests was proposed based on big data to carve out different user preferences for traditional arts and crafts. The user interaction response rate of the platform was good, with TPS of 98.7, 137.4 and 75.6 on the sending side, service side and receiving side, respectively, in stable operation. The friend recommendation algorithm incorporating user interests can effectively dig out user groups with similar interests, which is optimized by 11.83% compared to the traditional friend recommendation algorithm. The exchange platform supported by big data, based on friend recommendations to strengthen user interaction, can effectively promote the exchange and integration of traditional handicraft arts.

Exploring the influence of good Chinese storytelling on the foreign communication of local culture in Shaanxi is to develop local culture better and expand the influence of the local cultural industry in Shaanxi. In this paper, starting from deep learning neural networks, the attention mechanism is introduced by using convolutional neural networks, and the attention mechanism-based detection model for cultural information dissemination is constructed by vectorizing the data of the pre-trained model. The performance of the CNN-ATT model constructed in this paper is experimentally analyzed on two data sets. The accuracy of this paper’s model on the Ma_Dataset and CED_Dataset datasets is 96.23% and 95.21%, respectively. The best results are obtained when the convolution size is 3,4,5, and the accuracy is improved by about 4.03% compared with the convolution size of 4,5. This shows that the model of this paper can effectively analyze the influence of cultural information dissemination and also provides a research basis for the detection of the influence of telling Chinese stories on expanding the foreign communication of local culture in Shaanxi.

This paper proposes an evolutionary model of information dissemination based on information exposure states and the underlying topology of social networks. Based on the definition of similarity, the K-means method is used to cluster the categories of information based on the activation of information at the network vertices and to model the “category-category” interactions. The evolution of information dissemination is then explored, and the EGT model is fitted to obtain a gain matrix that reveals the interaction of information, and the quantitative evolution of information is then analyzed. Finally, the information dissemination media of Chinese language and culture education are explored, and the analysis of the dissemination of Chinese language and culture education under various media, comparing the feedback effects of traditional and modern media as representatives of Chinese language and culture classes. Among the feedback results of each medium, the traditional medium’s positive and active feedback indices ranged from 5 to 17, while the modern medium ranged from 12 to 27. The traditional media’s negative and passive feedback indices ranged from 2-3, while the modern media ranged from 3-4. In the field research on the informatization of the Chinese language and culture, the total score for the informatization of the Chinese language and culture curriculum in Yucai Middle School was 0.45, and the total score for Guangming Middle School was 0.65. Modern media can facilitate the spread of the Chinese language and culture to a certain extent.

In this paper, by collecting a large number of 3D scenes with traditional cultural styles, after pre-processing, the style analysis task of 3D scenes is realized through two stages of model style element discovery and scene style pattern mining. In the style pattern mining stage, the maximum frequent pattern mining algorithm is used to get the style pattern of the final scene, and the part is visualized. To reduce the user’s selection time, a 3D interior layout recommendation system based on style rule mining is designed using collaborative filtering. Based on the previous work on scene style pattern mining, the style association rules are further mined, and the user is provided with candidate layouts and furniture dynamically and in real-time by introducing user interaction. Comparing the text-improved recommendation algorithm with the traditional recommendation algorithm, the accuracy rate of the traditional algorithm starts to saturate to 65% after TopN>20, while the algorithm in this paper is higher than 80%. In the analysis of traditional cultural contexts of interior art, in terms of the aesthetic acquisition, the highest proportion of aesthetic association is 63.7%. In terms of emotional expression, the proportion of symbolization of emotion is 73.1%. In terms of object comparison, the highest proportion of plurality and flexibility of combinations was 57.5%. Therefore, this paper provides good research ideas for how to better integrate traditional culture into interior design.

We study its expression in sculpture modeling by excavating traditional cultural imagery in sculpture art. In this paper, 20 students with design-related backgrounds were selected as subjects to view sculpture images for cultural imagery evaluation, and imagery selection, response duration, and eye-movement data were collected using Yulin Grottoes statue sculptures as eye-movement experiment samples. The collected data were then used to investigate various imagery expression methods and anticipate the traditional cultural imagery appearing in the sculptures using the DE-GWO model. With a mean square error of 0.275 for the typical user sample and the results of the DE-GWO analysis showing a p-value range of 0.446 to 0.05, with no significant differences, the degree of fit and predictive power between the predicted and actual values of the test set was generally good for subjects with relevant backgrounds. The presentation of sculpture art language under the multicultural viewpoint explores the expressive form of traditional cultural images, which has positive relevance to the development of sculpture art.

With the continuous deep integration of the Internet and education, soccer culture has been popularized in the field of physical education, and its influence on physical education in Chinese colleges and universities has been deepened. This paper firstly constructs the evaluation index system of soccer culture on the teaching ability of physical education in Chinese colleges and universities based on the linear regression model and logistic regression model in the context of the Internet, determines the final evaluation index system, calculates the weight coefficients of the indexes, and derives the relative importance of each index through comparison. Secondly, the relative scores of indicators are determined according to the weights of the evaluation index system of teaching ability of physical education, and the influence of football culture on physical education in Chinese colleges and universities is analyzed. The numerical values show that the mean scores of experts’ scores of teaching ability as well as the coefficient of variation, have changed, which obviously can show that the modified indicators of teaching innovation ability have a higher degree of expert recognition. The means of the four indicators were 4.86, 4.7, 4.7, and 4.65, with standard deviations of 0.34713, 0.5, 0.5, and 0.56721, and coefficients of variation of 7.34%, 6.25%, 6.25%, and 12.45%. Thus, it is feasible to analyze the influence of soccer culture on physical education in Chinese colleges and universities using linear regression models and logistic regression models based on Internet technology.

In this paper, we first obtain the most representative subset of learning behavior features from big data and evaluate each feature value using a genetic algorithm to obtain its weight parameter. Then a similar least squares method is used to establish behavioral performance indicators through temporality, and the loss function is used to classify the indicators to obtain accurate teaching parameters. Finally, the K-means algorithm is used to mine the spacing distance of different log data and obtain the corresponding temporal feature vector to the learning behavior data with similarity. The application effectiveness of this teaching platform was tested, and the results showed that the propagation time of the big data platform takes only 112ms, the start-up time is 158ms, and the highest access number ratio can reach 0.82. The passing rate of students using this platform is as high as 73% on average, and the average length of independent learning reaches 6.5 hours. It shows that the online German teaching platform built on the basis of big-number technology has cultivated students’ international vision and cross-cultural communication skills.

In this paper, the BOPPPS model is used to improve the curiosity of trainees, determine the learning objectives, adjust the depth and progress of the course, and achieve the innovative development of the complete teaching process. The data of textile industry and fine arts trainees are collected, the least squares estimator of variance vector is calculated, and the industry integration development path covariates are obtained by combining the principle of great likelihood ratio to determine the change of linear relationship between the two and achieve the optimal development path. The results show that after the teaching of BOPPPS model, the control P value of trainees’ performance is less than 0.05, which contributes to the cultivation of trainees’ innovative thinking, thus promoting the integrated development of Shandong folk art and contemporary textile industry and improving regional economic benefits.

In this paper, a tourism revitalization model of intangible cultural heritage is constructed, and firstly, feature factors are extracted and multivariate features are combined using methods such as kernel density estimation to provide support for reliable prediction. Then decompose the MLP network structure, i.e. multilayer perceptron, and use Sigmoid function as the activation function. The importance of the feature factors is calculated using the random forest algorithm, and the collected tourism data are mined for the relationship between intangible cultural heritage and tourism revitalization to obtain the residual mean square of out-of-bag data. Finally, the coupling coordination degree is used to derive the development of ICH and tourism revitalization. The experimental results showed that 78% of the tourists were moderately to highly involved in the interactive participation of ICH, and only 22% were not interested in it. Therefore, the combination of ICH tourism and new media may become a new way of communication, allowing more general public to have the opportunity to approach and know ICH tourism.

In order to increase regional economic benefits and attract more tourists for local economic development. This paper adopts different ways to evolve industrial integration, enrich and expand the theoretical system of the industrial economy, establish new tourism strategies to meet personalized and diversified needs and make the tourism sector achieve industrial integration. Useful data are selected to filter cultural and creative, and tourism industry information by mining hidden information of coding sequences and finding support data items. Using collaborative filtering recommendation method to obtain the preference degree of fused data items, populate the data according to behavioral speculation, calculate the utility matrix similarity, and clarify the development of industry fusion path in the context of big data. The results show that the average error rate after fusion does not exceed 4%, and the fusion path of cultural and creative industries and the tourism industry improve the regional economy and the overall local living conditions.

This paper constructs a model of cultural identity by combining the analysis of multimodal discourse in the media fusion perspective and explores how to better construct cultural identity. Firstly, we construct a multimodal cultural identity model in the media convergence perspective from three modalities: text, image, and video combined with cultural identity, so that we can analyze people’s cultural identity through emotion. Secondly, multimodal cross-sectional comparison experiments and dissimilarity experiments are conducted based on two widely used public datasets in the field, CMU-MOSI and CMU-MOSEI. The best experimental results were obtained in the baseline model, where Acc-2 reached 84.8%, F1 value reached 84.5, and MAE of the regression task dropped to 0.548. In the robustness study, when the missing rate reached 44%, Acc-2 was only 65.2%, and the gap between the results and the dichotomous classification accuracy of 76.5% achieved by the model in this paper reached 11.3 percentage points. Finally, through affective analysis, cultural identity is the affirmative embodiment of what is most meaningful to the nation formed by people living together in a national community for a long time, and its core is the identification with the basic values of a nation, which is the spiritual bond that unites this national community.

In order to make the traditional national sports can be inherited in a lasting way, this paper focuses on the study of national traditional sports culture inheritance from the perspective of moral education. Firstly, we add the teaching content of traditional ethnic sports in physical education courses; secondly, we use the weight update method and base classifier in the weighting function to improve it. And finally, we use the system to conduct experiments. The results show that the teaching experiment of pearl ball as the teaching content of public physical education courses can better improve students’ performance in 4 qualities, and the improved teaching mode can promote students’ learning attitude towards physical education. From the perspective of cultural inheritance, it is of practical significance to explore the new mode of national traditional sports education in colleges and universities under the new conditions of the times in order to inherit traditional national sports and enrich the cultural connotation of college students.

This paper firstly investigates the empirical modal decomposition image fusion technique, uses the empirical modal decomposition algorithm to calculate the instantaneous frequency to obtain the intrinsic modal function, and uses the two-dimensional implicit modal function to obtain the image features of intangible cultural heritage. Secondly, based on the digitization of paper-cutting art by image fusion technology, the pixel-level image fusion method is applied to fuse the paper-cutting paper with the designed Peking Opera face pattern, to maximize the original information of the paper-cutting paper, to realize the digital transmission of intangible culture by constructing an auxiliary paper-cutting design system, and to empirically analyze the research of paper-cutting intangible cultural heritage based on the empirical modal analysis method. The results show that in the analysis of the paper-cutting industry in Ui County, the ratio of time to 1917 exceeds 2.22 and reaches 3.00 by 1925 until 1943, when it reaches a peak of 3.25. The paper-cutting culture spread within the villages during this period, and the villagization characteristics of paper-cutting in Ui County are formed. This study digitizes intangible cultural heritage and contributes to the preservation and transmission of paper-cutting cultural heritage resources.

This paper firstly constructs the mutual mechanism between the characteristics of Confucian moral education thought, and college students’ Civic Education and the influence mechanism of college students’ psychological characteristics on the integration of Confucian moral education thought. Then a logistic regression model of the integration of Confucian moral education into Civic Education was established, and data collection, pre-processing, missing data processing and parameter estimation steps were carried out. Finally, the results of the application of Confucian moral education thought in Civic Education were analyzed, including the analysis of the factors influencing the integration effect and the analysis of the results of psycho-social cognitive factors on the optimization of moral education strategies. The results show that the interaction coefficients of the three regression models of the exposure to Confucian moral education ideas and the effect of ideological and political education dissemination among college students are 0.7325, 0.4817, and 0.3885, respectively, and the coefficients of the interaction terms are all significant at the level of 0.05. The research in this paper has some reference value for promoting the development of moral education and the transmission of cultural values.

This paper first constructs the logical architecture and implementation mechanism of cross-border e-commerce live streaming and local cultural communication and proposes a cultural communication influence model based on clustered ellipsoid and spatial cluster analysis. By using first-order linear approximation and PMA for non-probabilistic uncertainty cultural communication analysis, the optimal global solution of the system response is solved. Finally, the results of cross-border e-commerce live streaming and local cultural communication power are discussed by specifically analyzing the characteristic quantities of cultural communication structure and local cultural communication effect. The results show that the maximum value is 39.8034 in the TOP20 of local culture communication power, the mean value is 17.3431 in the communication effect dimension, and the mean value is 16.17 in the communication structure dimension. This paper provides a new model to explore for cross-border e-commerce live streaming and local culture communication.

This paper first investigates the coupling mechanism between intangible cultural heritage and the tourism industry and structurally couples intangible cultural heritage and study tours by constructing an evolutionary model. Then, by analyzing the situation of the study tour market and constructing an evaluation system for the development potential of the study tour market, we analyze data on the development of ICH-themed study tours using correlation coefficients and significance tests. The results showed that the seven variables showed a significant correlation (p

This paper uses convolutional neural networks to construct a deep learning-based teaching mechanism for question-and-answer on civic culture. The one-hot representation and the distributed representation of words in the distributed expression form of natural language are analyzed. Word2Vec, a word embedding training tool, is used to generate word embedding representations, and CNN is applied to store and classify word semantics so as to generate semantic matrices. The attention mechanism is combined to simplify the model processing steps and reduce the complexity of operations. The deep learning hierarchical semantic extraction model is tested by loss function and relative similarity to judge the accuracy and performance of the model’s operation. The results showed that the mean composite score of the experimental group was 5.2 points higher than that of the control group, and the t-test results P=0.003

In order to construct a knowledge graph of Hainan marine intangible cultural heritage, this paper designs the graph database by setting the annotation system and semantic structure of the intangible heritage metadata. For the named entity recognition of the knowledge graph, a model combining long and short-term memory neural networks and Bi-Lstm-CRF with conditional random field is established. The recognized entities are processed based on the Bert pre-training model, and the semantic relations are extracted by combining the cluster search method. Compared with other models, the accuracy rate of the Bs-Spert model for the extraction of semantic relations of the Hainan marine NRM dataset is improved by 0.64%, 0.85% and 0.98% compared with GCNRE, Match Blank and MTDS, respectively. Meanwhile, other metrics of the Bs-Spert model also performed well, with a recall rate of 82.26% and an F1-value of 74.01%. By constructing a knowledge map based on the graph database, we can analyze the current situation of Hainan’s marine NRM more comprehensively and thus propose corresponding countermeasures.

Firstly, according to the actual situation of some new undergraduate colleges and universities upgraded from teacher training colleges, whose science and technology disciplines are relatively weak but humanities disciplines have an excellent history of nearly one hundred years, the humanities disciplines with strong creativity, such as education, art and media, are closely related through the construction of cultural and creative industry professional clusters. Secondly, based on the clustering algorithm, we classify and quantify the professional relationships of undergraduate institutions, which need to satisfy the assignment rules and perform algebraic operations on the relationship matrix to realize the classification of professional relationships. Then we searched the Chinese literature with “professional cluster” as the keyword to obtain the initial data, and used the clustering algorithm to visualize and analyze the research on professional cluster construction in undergraduate colleges and universities. The results show that when the default values of α1/α0 = 3 and γ[0,1] = 0.6 are used, the seven keywords with the highest emergence intensity are: architecture cluster, transformation development, undergraduate, professional faculty, school, undergraduate school, and big data, and the keyword clustering reflects the research hotspots of professional clusters, which can promote the construction of professional clusters.

This paper firstly analyzes the problems of poor effect and translation recognition effect of cross-border communication of Chinese medicine culture. And countermeasures are proposed according to the current situation, and the LDA text model is introduced. Secondly, the LDA model is improved, the method of changing the rate according to the number of topic transfers is applied, and the topic distribution is updated according to the number. Then the functional and holistic framework of the platform is structured to build a cross-border communication platform for TCM culture. Finally, the recognition rate of the improved TD-LDA model is analyzed experimentally, and the recognition rate is improved from 67% to 84% when the number of test sets is below 1000. For the reliability test analysis of the TCM culture platform communication effect, the standard path coefficient SRW from ZYX to TEA is 0.642, t=12.763, p

The impact of changing Japanese language instruction in higher education institutions on students’ intercultural communication skills is examined in this paper using gray correlation. To create the gray correlation value matrix of the ideal response, a comparison study of the geometric relationships between the system data series and the geometry of the curves is done. The set of signals for the ideal response and the negative one is established by examining the specific steps of the ideal response approach. The multiplicative synthesis method was used to assign weights to the combinations of decision indicators, and the assignment formula was calculated. The results showed that 42% of the students wanted to learn everyday Japanese in Japanese language teaching, only 21% wanted to learn professional Japanese and industrial Japanese, and most of the learners preferred to improve their communicative ability through Japanese language teaching courses. The most desirable communicative ability of students should be 43% of expression and imagination.

The distance between sample sets is calculated in this paper using VR technology by combining the K-means clustering algorithm to select data objects. Continuous optimization of the objective function leads to optimal clustering, expressed as the clustering effect. The output is performed at the cluster center of each data point, and the density function of the target nodes is sorted based on the given parameters to calculate the neighborhood map of the data points and create the matrix. Based on the perception degree test before and after the innovation of landscape cultural heritage inheritance by VR technology, the overall perception degree of residents and tourists rose to 8 after the innovation. VR technology can help expand the protection and inheritance of minority landscapes and promote the sustainable development of traditional culture.

This paper introduces the BOPPPS teaching model integrated with flipped classrooms into the intercultural communication classroom by decomposing the BOPPPS teaching module and analyzing the differences with traditional teaching methods by combining social network analysis methods. The basic teaching model framework was built, and an effective blended teaching model was created by utilizing the third-order nonlinear expression of social networks introduced into the online platform. A 10-week teaching model experiment was conducted for two classes to explore English major students in a university. The overall average score of the experimental class improved by 23.6 points to 86.02, and the score improvement was significantly higher than that of the control class, proving that the hybrid teaching model is an effective way to cultivate talents for universities.

This paper aims to highlight the sustainable development level of European cultural and creative industries and their impact on national economic growth and establish a sustainable development assessment model based on the entropy weight method. The influence of different quantiles on the decision results is eliminated by standardizing the indicators. The objective evaluation method utilizes the entropy principle to avoid bias caused by human factors. The comprehensive evaluation method of sustainable development is utilized to gauge the trend and direction of enterprise development. It has been found that the annual added value of the cultural and creative service industry in Europe in 2022 is 226.976 billion yuan. It is an effective development strategy to promote economic growth in Europe, with an increase of 10.8% over the previous year.