In today’s big data era, China’s radio and television broadcast volume has reached an unprecedented height, and it is diversified in quality and content richness. The realization of big data model accelerates the transformation of radio and television and constantly reaches new movie-watching heights. In the era when TV dramas, movies, animation, radio stations, and We Media are prevalent, big data is being experimentally analyzed through professional digital technology and effective methods of media integration of radio and television. In order to make China’s radio and television industry present a strong industrialization development trend, it is necessary to have a suitable network system to form a pillar, so as to play a substantial role in the development of this industry. Choosing the appropriate evaluation system to evaluate the broadcast volume, ratings, box office volume, and profit income of the mass media is also a breakthrough stage of today’s technical ability. The experimental results of this paper show that (1) from the ratings of only 15% in 2010 to 75% today, the successful investment of radio and television in the market has been realized, and the efficient development of modern technology has benefited the people. (2) Department executives are mainly in charge of the economic lifeline of enterprises, and 70% of economic indicators is the embodiment of small workload and high voice of key tasks, which are the main roles in performance evaluation. (3) The accuracy of the old index is only 75 while the new index is 90, so selecting excellent performance indicators is also responsible for performance appraisal. (4) The development of radio and television from urban to rural areas, from 0% of the market to 12.23% of the rural areas, is a manifestation that the development of modern science and technology benefits the whole people. Only when performance evaluation is fed back to the market can it adapt to the next stage of reform and improve the enthusiasm of employees.

<abstract> <p>There are many schools of Chinese martial arts routines and complex movements; research on this topic is more geared toward Taijiquan (a kind of traditional Chinese shadow boxing), which is a more well-known type of martial arts. Therefore, the purpose of this paper is to visually analyze the research of Chinese martial arts routines based on the knowledge graph method and to propose a knowledge graph method based on the fuzzy set theory, which is called the transF model throughout this paper. The transF model used the fuzzy relational operation of vectors to not only reduce the computational complexity, but to also better integrate multi-dimensional data, especially when the training set is not particularly sufficient. For the visual analysis of Chinese martial arts routines, this paper selected the 16-year data from 2005 to 2020 as the analysis sample, analyzed high-yield institutions and high-yield authors, and conducted a centrality analysis of the whole dataset. From the structure of the knowledge graph, traditional martial arts are the core part of Chinese martial arts, with a centrality of 0.14. Competitive martial arts are the main branch of Chinese martial arts and the third core after Tai Chi and traditional martial arts, with a centrality of 0.41, which is higher than that of traditional martial arts. This shows its importance in martial arts research.</p> </abstract>

In recent years, my country’s cultural industry has developed vigorously and has become a new growth point of the national economy. With the introduction of a series of cultural reforms and policies to promote the development of the cultural industry, cultural enterprises have grown rapidly and are on the list. As the main carrier of a specific business format and cultural industry, cultural enterprises have made great contributions to optimizing the allocation of cultural resources, promoting employment, prospering culture, and meeting cultural and cultural needs by virtue of their unique cultural resources and talent virtues. Based on the structural equation model, this paper analyzes and optimizes the internal factors of cultural industry management. By establishing the internal factor index system that conforms to cultural industry management, the important internal factor index system is obtained, and then, it is optimized. From the reliability test results, it can be seen that the overall a coefficients of the outcome variables industrial resources (A), industrial management growth (C), and industrial development level (D) are all greater than 0.5. Except for the observation variable protection personnel (B4), the rest of the observations the coefficients of the deleted items of the variables are all smaller than the overall a coefficients, and the coefficients of each structural variable and the overall scale are all greater than 0.7, indicating that there is a strong correlation between the observed variables in each group, and the measurement results are very consistent and stable, which satisfies the structural comparison. The data requirements are reliable, scientific, and effective in theory; the weight calculation of the indicators shows that the weight of capacity growth is the largest, followed by resource development capacity, cultural resources, economic performance, social performance, and human resources; use all the data of the sample to conduct an overall analysis. In model fitting and verification, the results show that the chi-square value is 932.731, the degree of freedom is 307, and the chi-square degree of freedom ratio is 2.896, which is less than the critical value of 5, and the adaptation indicators meet the requirements. Sexuality (C) has the greatest impact on cultural industry management, followed by industrial resources (A) and resource allocation capability (B). From the parameter estimation of structural variables and various index variables, it is found that cultural industry management needs to improve the richness of material cultural resources. To start with, especially pay attention to the use of intangible cultural resources. In terms of resource allocation, development and protection must be carried out at the same time. In addition, the most important thing is to introduce talents. Financial support and preferential policy support also need to be paid attention to. In business operation, it is necessary to improve the innovation ability and operation ability, and at the same time, it is necessary to focus on the development of operation ability and industrial operation. In the operation of cultural enterprises, it is necessary to improve brand awareness and build a good reputation, so as to attract more people and go a long way.

Scientific and rational optimization of human resources allocation in media operation and management to maximize the economic and social benefits of enterprises is the top priority of the current media to strengthen human resources work. How to allocate human resources, adjust the structure of human resources, realize complementary advantages, and dynamically adapt to the needs of economic construction is a very important issue that must be carefully studied in the process of human resources development and management. In this article, a binary classification support vector machine method is proposed, which uses linear function calculation, and finally uses multi-skill model to solve performance experiments. The results show that the media operation management must reform the labor employment system, allocate the labor force scientifically and rationally, and make effective use of the media management labor resources; labor employment is a necessary means for the development and survival of enterprises. It is an important function of enterprise management to manage and utilize labor reasonably and effectively. Through optimal allocation and rational utilization, the human resource allocation in media operation management can reach a higher management level.

Combined with the development of the current educational environment, physical education will replace English as the third subject of education in the future. The breakthrough in physical education teaching is also gradually changing from the general education form to today’s smart education. In the era of big data, physical education can also apply this technology. In action scenarios based on big data, operations such as correction of detailed actions or monitoring and identification of key actions are common. Through the computer vision system, the rational judgment of the computer can be used to give follow-up training points. Also able to store personal data during training. The presentation of algorithms cannot be avoided through computer vision. Based on Action Bank as the basic algorithm, this paper proposes a template research method based on multispectral clustering and has been applied in Action Bank. The tedious manual template selection is eliminated. This method replaces it to facilitate its dissemination in different databases. In this method, due to the slow speed of extracting features, a fast algorithm of quantitative Action Bank is extracted. The experimental part of the article compares whether the algorithm has been optimized in terms of performance before and after optimization. The resolution, time consumption, and detection errors of the Action Bank model are carried out. The experimental exploration and data collection and comparison are carried out. After the experimental optimization, the performance has been improved. By comparing the meanshift detection method and spatiotemporal action detection method with the Action Bank model mentioned in this article, the experimental data of resolution, time consumption, and detection error are compared, and the Action Bank model is obtained in terms of resolution, time consumption, and error detection. The time consumption is better than the other two algorithm models, but there is room for improvement in detecting errors, but the experimental results also meet the current detection requirements, and in the current physical education teaching, it also occupies the forefront of this field, at the forefront. Ministry of Education. Instead of English, physical education has become the third subject! On April 21, the Ministry of Education released the “Compulsory Education Physical Education and Health Curriculum Standard (2022 Edition),” and the new curriculum standard will be officially implemented in the fall semester of 2022. Among them, the proportion of the total class hours of “Sports and Health” is 10-11%, surpassing foreign language to become the third major subject in the primary and early stages. Physical education has already started its journey. Traditional physical education can no longer meet the development of the current environment. The arrival of the information society has also brought about the development and progress of physical education. Only by better combining the current information technology can it be satisfied. The needs of physical education is in the future.