Background Of Big Data Research Articles

Exploration of Practical Teaching of Economics Major in Chinese Universities Under the Background of Big Data

Exploration of Practical Teaching of Economics Major in Chinese Universities Under the Background of Big Data

Industrialization and innovation strategy of event resources in ice and snow sports under the background of big data

This article examines the industrialization and innovative strategy of event resources in ice and snow sports in the context of big data. Based on this analysis, the article proposes a path and development strategy for the Chinese sports industry, which includes encouraging the industrialization of the nation’s ice and snow sports industry. It is important to evaluate ice and snow sports in order to improve competitive results and optimize training techniques using big data technologies. Despite using a variety of techniques to evaluate performance, their inability to fully capture the complex patterns found in ice and snow sports events presents difficulties. In order to assess and enhance sports talents, therefore we proposed a new method using ISSE-Apriori algorithms. The pre-processed data gathered before extracting the most important and relevant features. The experiment results section analyzes the resources of ice and snow sports cities. The results examine sports event strategies, taking into account predictions and actual accuracy results, the GDP growth rate, the efficiency of industrial development, and a comparison of Apriori before and after enhancement. The experimental result is validating using measures like recall, accuracy, and precision. In addition, we conducted a comparative analysis with the current approaches to confirm the efficiency and robustness of the proposed methodology. The Suggested approach is implemented with Python Software. The Suggested Approach’s performance is measured in terms of RMSE (0.3524), MAE (0.1832), MAPE (4.24) with large dataset. The results stated that the proposed methodology has provided an accuracy of 98.42%.

Research on the Path of Transition from Financial Accounting to Management Accounting Under the Background of Big Data

Driven by the wave of big data, the traditional financial accounting model faces an urgent need for transformation, as it struggles to adapt to the complex requirements of modern enterprise management. This paper aims to explore the feasible path for transitioning enterprise financial accounting to management accounting in the context of big data. It first analyzes the limitations of financial accounting in the era of big data, then highlights the necessity of transitioning to management accounting. Following this, the paper outlines the various challenges that may arise during this transition and, based on the analysis, proposes a series of corresponding transition strategies. These strategies aim to provide theoretical support and practical guidance for enterprises seeking a smooth transition from financial accounting to management accounting.

Research on Blended Teaching of College English Writing Based on 'POA' Theory Under the Background of Big Data

This paper discusses the application value of the writing teaching mode combined with the mixed teaching mode in college English writing teaching against the background of big data. Focusing on production-oriented approach (POA) theory, this paper proposes a mixed learning writing model for English teaching and applies the POA mixed learning English writing teaching model to practical teaching by using the cloud classroom platform, collecting students' big data, and analyzing students' seriousness, classroom participation, satisfaction, and English writing performance. Although the overall student engagement is not high, their classroom satisfaction is very high. Research shows that after the teacher adjusted the lesson plan and encouraged students to participate more in class interactions, their scores improved in the second exam but declined in the third exam . The levels of engagement, participation, and satisfaction have significantly decreased across all grades. The POA combined with the blended learning mode has a great application value in practical teaching in the era of big data.

Analysis of Accounting and Finance Teaching Reform Based on the Big Data Background

Under the push of the big data tide, the finance and accounting field is undergoing an unprecedented transformation. The reform of big data and accounting professional talent cultivation urgently needs to be accelerated, and vocational colleges, as an important platform for cultivating high-level skilled talents, are particularly important. This paper aims to explore the current situation, challenges and reform strategies of big data and accounting professional talent cultivation in vocational colleges in the era of big data, with the hope of providing useful reference for relevant educational practices.

Teaching Reform of International Course on Seismic Data Interpretation in Universities under the Background of Big Data

Teaching Reform of International Course on Seismic Data Interpretation in Universities under the Background of Big Data

Research on Innovation Strategy of Supply Chain Management of Agricultural Enterprises Under the Background of Big Data

With the rapid development and widespread application of Big Data technology, the supply chain management of agricultural products enterprises is facing unprecedented reform and challenges. This study takes the perspective of Big Data technology and collects relevant information on the application of supply chain management in 100 agricultural product enterprises through a survey questionnaire. The study found that the use of Big Data can effectively improve the accuracy of demand forecasting, inventory management efficiency, optimize logistics costs, improve supplier management efficiency, enhance the overall level of supply chain management of enterprises, and propose innovative strategies for supply chain management of agricultural products enterprises based on this. Big Data technology brings a new solution for agricultural products enterprises to enhance their supply chain management level, making the supply chain smarter and more efficient.

Research on Optimization of Internal Audit Process under the Background of Big Data

In the era of big data, it is especially vital to optimize the internal audit process. Traditional methods are increasingly inadequate to handle the burgeoning volume of data and intricate environments. Consequently, leveraging big data technology to enhance audit processes has become essential. The role of internal audit should evolve from mere supervision to a service-oriented function, aiming to bolster governance, uncover issues, and enhance value. Nevertheless, challenges such as inadequate audit independence and feeble rectification mechanisms persist. The integration of big data technology with internal audit practices can markedly elevate the quality and efficiency of audits, and foster innovation in audit methodologies. To optimize the audit process, it is imperative to define clear objectives, propose practical and viable solutions, and further refine the quality and sophistication of audit work through techniques like data preprocessing and analysis.

Research on privacy protection in the context of healthcare data based on knowledge map.

With the rapid development of emerging information technologies such as artificial intelligence, cloud computing, and the Internet of Things, the world has entered the era of big data. In the face of growing medical big data, research on the privacy protection of personal information has attracted more and more attention, but few studies have analyzed and forecasted the research hotspots and future development trends on the privacy protection. Presently, to systematically and comprehensively summarize the relevant privacy protection literature in the context of big healthcare data, a bibliometric analysis was conducted to clarify the spatial and temporal distribution and research hotspots of privacy protection using the information visualization software CiteSpace. The literature papers related to privacy protection in the Web of Science were collected from 2012 to 2023. Through analysis of the time, author and countries distribution of relevant publications, we found that after 2013, research on the privacy protection has received increasing attention and the core institution of privacy protection research is the university, but the countries show weak cooperation. Additionally, keywords like privacy, big data, internet, challenge, care, and information have high centralities and frequency, indicating the research hotspots and research trends in the field of the privacy protection. All the findings will provide a comprehensive privacy protection research knowledge structure for scholars in the field of privacy protection research under the background of health big data, which can help them quickly grasp the research hotspots and choose future research projects.

Construction of Urban Spatial Intelligent Planning and Design System Under the Background of Big Data

Based on the induction of potentially utilisable micro-spaces in typical old residential communities, this study selects the communities located at 19 and 22 Yuhe Street, Taiyuan City, Shanxi Province, as typical research objects. By employing space syntax analysis, the spatial properties of these micro-spaces are examined and matched with the activity needs of various age groups within the community. By leveraging the characteristics of activity periods for all age groups, the study also proposes a composite design for less disruptive activity spaces. Consequently, optimisation suggestions for the renovation of public spaces in these two communities are presented, aiming to specifically meet the activity needs of residents of all ages within the limited space of the community. This research provides an analytical framework and methodological approach for the renovation strategies of old residential communities.

Research on countermeasures for safety prevention of muscle injury in sports under the background of big data and smart medicine

With the deepening of quality-oriented education and the implementation of new curriculum standards, the forms and contents of school sports activities are increasingly diversified. In this regard, special attention must be paid to sports safety. Sports is a sport to improve physical and mental health, but it is easy to cause physical injury in sports. Big data can effectively monitor the normalization of movement in the process of exercise, so as to take timely safety precautions and reduce the probability of muscle injury. Therefore, by analyzing the causes and influencing factors of muscle injury in sports, this paper puts forward some safety precautions to avoid muscle injury accidents during sports. Through the neural network algorithm, it can be seen that with the increase of time, the function width and prevention index of security are constantly rising, and the average value of function width is about 0.83. The seventh day is 0.15 higher than the first day, the average value of prevention index is 1.31, and the seventh day is 0.19 higher than the first day. The effect of the optimized safety prevention strategy is better than that of the traditional safety prevention strategy, and the probability of muscle injury of athletes is also greatly reduced by 11% compared with the traditional one; However, the rehabilitation effect has improved a lot, 9% higher than the traditional one.

Thoughts and Countermeasures on the Development of Digital Economy

With the rapid development of information technology and the deepening of globalization, big data technology and digital economy, as the most important form of technological and economic change, are having a far-reaching impact on China's economic and social development. In view of the problems faced by the development of digital economy in China under the current background of big data, such as lagging institutional construction, lack of human resources, inadequate core technology and unbalanced development of related industries caused by the digital divide, this paper puts forward measures to strengthen the relevant institutional construction, attach importance to the training and introduction of talents, and promote technological innovation. In the past, it provided strategic suggestions for the healthy and stable development of China's digital economy, and also provided some reference for the development of China's digital economy.

Exploration on Innovation Path of Precise Ideological and Political Work in Colleges and Universities Under the Background of Big Data Driving

However, although existing models for evaluating the effectiveness of universities provide a large number of modeling solutions, it is difficult to objectively evaluate dynamic coefficients based on the differences in precision ideological and political work systems of different types of universities in the evaluation process of innovative paths for precision ideological and political work. In this context, this article proposes an innovative path for the precision of ideological and political work in universities under the background of big data driving, and constructs a complex system discrete dynamic modeling technology. This model quantitatively describes the consistency between different precise ideological and political work models, the similarity of research strategies for precise ideological and political work, and expected evaluation indicators using multiple transformation dynamic coefficients. This study provides new ideas and methods for innovative research in the field of ideological and political work in universities.

Research on the Establishment of Poverty Identification System for College Students under the Background of Big Data

The work of college student financial aid is an important part of talent cultivation in higher education. Combining big data with the identification of impoverished college students and constructing an evaluation system for the identification of impoverished college students based on big data can accurately identify impoverished college students. Based on the concept of financial aid under the background of big data, this paper analyzes the feasibility and necessity of constructing an evaluation system for the identification of impoverished college students, constructs an index system for the identification of impoverished students based on big data, builds a dynamic information support system with the help of big data technology, and constructs the guarantee conditions for accurate identification of impoverished students. It gives full play to the synergy between financial aid and big data information technology, and continuously improves the effectiveness of financial aid in colleges and universities.

Research on Risk Management in Internet Finance under the Big Data Background

Research on Risk Management in Internet Finance under the Big Data Background

Research on Personalized English Teaching in Universities under the Background of Big Data

Research on Personalized English Teaching in Universities under the Background of Big Data

Research on the Integration and Application of College English Teaching and Artificial Intelligence Technology in the Context of Big Data

In the era of big data and artificial intelligence, the traditional college English teaching mode has been difficult to meet the personalized learning needs of students. The integration of big data analysis and artificial intelligence technology into college English teaching can realize intelligent push of teaching resources, accurate monitoring of learning process, and immediate feedback of learning effects, etc., which is helpful to build an intelligent English learning ecology and improve teaching quality and learning efficiency. This paper analyzes the significance of the integration of college English teaching and artificial intelligence technology under the background of big data, analyzes the problems existing in the current integration application, and puts forward countermeasures and suggestions such as optimizing course design, innovating teaching mode and strengthening the construction of teachers, in order to provide reference for the reform of college English teaching in the new era.

The Use of Big Data Analysis in Digital Empowerment of Sustainable Technological Innovation Management of Ecological Enterprises.

With the social economy's rapid progress and the popularization of environmental awareness, ecological enterprises have gradually become a crucial trend in the development of modern enterprises. This work intends to promote the development of ecological enterprises to a higher level. This work first analyzes the management mode of ecological enterprises in the context of big data in China. Then, it establishes various indicators to analyze the role of sustainable technological innovation in enterprise development and the impact of digital empowerment on enterprise development. Finally, this work takes China's manufacturing industry and ecological enterprises in Hubei Province as examples to summarize the digital empowerment of sustainable technological innovation management of ecological enterprises under the background of big data. The final result indicates that sustainable technological innovation significantly reduces ecological enterprises' resource consumption and waste emissions. Additionally, it has a significant positive effect on improving enterprise output value and economic benefits. The digital empowerment of enterprises has a significant driving effect on sustainable technological innovation, with a digital driving coefficient of 26. This work provides a feasible scheme for the specific application of big data analysis in the technology innovation management of ecological enterprises, including market demand analysis, environmental monitoring and governance, technology assessment and risk management. This work expounds the role of big data analysis technology in improving decision-making efficiency, optimizing resource allocation and enhancing the competitiveness of enterprises in the digital empowerment of ecological enterprises.

Reform and Development of College Music Teaching under the Background of Big Data

With the progress of the times, big data has gradually influenced the daily lives of people and is gradually changing the ways people learn. Big data plays a role in the field of college music education, changing college music education methods significantly. The use of big data technology can make teaching resources more abundant and teaching methods more diversified, which improves the efficiency and quality of college music education. The application of big data has long been the norm in the field of education. As an innovative educational means, colleges should make full use of the advantages of big data to promote college music education and to cultivate the growth of students.

Methods of Improving and Optimizing English Education Level in Higher Vocational Colleges Under the Background of Big Data

At present, the English skills of Chinese university graduates cannot meet the needs of social development. Therefore, in recent years, the reform of college English teaching has received unprecedented attention. This article proposes methods for improving vocational English education in the context of big data, including teacher development, curriculum design, teaching modes, teaching resources, and learning evaluation. It also explores and analyzes new models and means of vocational English teaching that are conducive to big data analysis. We adopted a blended learning model that combines large-scale online open courses and SPOC to reform traditional English teaching methods and plans, and studied the teaching effectiveness and feasibility of the blended learning model. The results indicate that it can improve the online course experience and teaching effectiveness. This study promotes the modernization and reform of vocational English education, which helps to enhance students' independent English learning ability and practical work ability.