Background Of Big Data Research Articles

Research on the Practice Path of English Teaching in Colleges and Universities based on the Background of Big Data

Research on the Practice Path of English Teaching in Colleges and Universities based on the Background of Big Data

Application of computer aided audit system and innovation research of enterprise financial audit under the background of big data

In the rapid development of social economy and science and technology, in the face of the continuous increase of network information resources, the Internet, computer technology, information technology, etc., has changed the content form of daily life and social production, and brought great convenience for people's life and work. From the perspective of enterprise financial audit, the financial audit work with big data technology as the core is much higher than the traditional financial audit work in terms of work efficiency and work quality. Therefore, after understanding the development trend of enterprise financial audit work under the background of big data, this paper mainly studies the relationship between the current enterprise financial audit work and computer-aided audit system according to the emergence of computer-aided audit system in the new era, and defines the development direction of enterprise financial audit work in the future.

Under the background of big data - investigation and research on the learning effect of college students' dual-track system

The pneumonia epidemic caused by the new coronavirus is spreading around the world, and the national epidemic situation is complicated and severe. At the same time, in order to implement the guidance of the Ministry of Education during the period of prevention and control of the new coronavirus epidemic, "suspend classes without teaching, and without stopping learning". Computer technology has played a huge role in the absence of on-site and offline surveys. Our group generated electronic questionnaires through computer technology, successfully digitized paper surveys, and adopted rigorous survey methods. Through Sina Weibo, WeChat, Tencent QQ Share and complete the questionnaire with the students, strictly review the IP address, and eliminate the invalid answer sheet, there are 600 valid questionnaires in total. Finally, the computer data analysis software-spss is used to clean and analyze the data, and finally obtain the analysis results of the sample data, and also ensure the authenticity of the survey results. Prior to this, we adopted an exact proportion of single and double selection questions and subjective question types. Through comparative analysis and cross-analysis, the interference of huge data on the later survey results was greatly reduced, and the accuracy of the survey was ensured. Based on this, it is believed that the online teaching platform should establish a rich knowledge database to provide students with some resources outside the classroom, which can mobilize students' interest in learning, and at the same time, it should have a more complete evaluation system, so as not to increase students' inertia. Furthermore, since it is an efficient and fast teaching method, it should not be used by some people, but more or all teachers should be familiar with and adapt to this teaching mode as soon as possible.

Research on the innovation path of university library management and service under the background of big data

Abstract The college library is one of the three pillars of school operation, shouldering the important task of teaching and research services, and is the center of auxiliary teaching, information sharing, academic activities, and cultural inheritance in colleges and universities. The strengths and weaknesses of library construction reflect the level of education and research of the school from one side, and its role in the school construction is self-evident. Therefore, to improve the quality of borrowing by school teachers and students and enhance the utilization rate of library resources. This paper designs a hybrid optimization recommendation algorithm based on the UserCF algorithm and Doc2Vec algorithm in big data to improve the library management and recommendation service. Finally, by summarizing the experimental results, it is concluded that the system running based on this hybrid optimization recommendation algorithm can accurately mine the data of library users’ behavioral preferences, and at the same time can efficiently and precisely recommend the information for readers’ needs. The citation of this optimization algorithm is further demonstrated to achieve the expected results.

Research on the risk management of enterprise cloud accounting application under the background of big data

Under the background of big data era, cloud accounting as an important basis for enterprise construction and innovation development, can not only improve the efficiency of enterprise accounting work, but also improve the application mode of traditional accounting information. According to the analysis of the application of enterprise cloud accounting in recent years, although the new technology concept has improved the enterprise financial management mode, it also brings certain risks to the innovation and development of enterprises. Therefore, some scholars have increased the risk assessment of cloud accounting in the research, and built a cloud accounting system based on big data technology, so as to quickly explore and deal with the hidden security problems. After understanding the basic concept and functional characteristics of Yuan accounting, this paper mainly studies the structure of enterprise cloud accounting system under the background of big data, and determines effective measures of risk management from the perspective of long-term development, which is of great importance to the innovation and development of enterprises in the new era.

Innovative research on the construction of experimental teaching platform of economics and management in colleges and universities based on the background of big data

Abstract Under the wave of big data technology development, the traditional experimental teaching methods in colleges and universities are difficult to meet the requirements of the educational objectives of the times, and teaching innovation is the focus of teaching research in many colleges and universities, which has attracted the attention of the majority of educational researchers. This paper focuses on the innovation of the construction of experimental teaching platforms of economic management in colleges and universities based on the background of big data. This paper explains the necessity of innovation of economic management experimental teaching platform, proposes the basic framework of innovation of economic management experimental teaching platform (Kube storage cloud data, front-end design, collaborative filtering algorithm), and researches and discusses the innovation mode and operation mechanism of economic management experimental teaching platform based on experimental teaching construction, based on the similarity between the specified time point and other time points The impact of the time factor on the recommendation results of experimental resources is analyzed. The results of experimental teaching resources recommendation reflect the resource recommendation ability of this platform and compare with H5 technology experimental teaching platform and content analysis method experimental platform to analyze the changing trend of MAE of teaching resources recommendation; analyze the number of concurrent connections and clicks of this platform to verify the performance of this platform. The research results show that this paper platform’s experimental teaching resources recommendation effect with MAE value of 0.51 is better than other platforms. The reason is that this paper platform’s experimental teaching resources recommendation fully takes into account the time factor and co-rated experimental teaching resources, so the accuracy of experimental teaching resources recommendation is significantly improved. This study can improve the quality and teaching efficiency of universities and train more excellent economic management talents for the country, which is of great historical significance to the development of China’s economy and education.

Big Data Empower the Realistic Path of the Construction of the Rural Public Cultural Service System

The construction of the rural public cultural service system in the new era is an effective way to meet the needs of farmers' spiritual and cultural needs. In the context of the revitalization of rural culture, the construction of my country's rural public cultural service system mainly has outstanding problems such as lagging infrastructure, lack of cultural content, single service forms, lack of professional talents, and incomplete regulatory mechanisms. Under the background of big data empowering cultural production and services, big data can help achieve rural areas with accurate supply of cultural service products, continuous innovation in cultural services, convenient cultural services, scientific training of cultural services, and effective guarantee of cultural service management. The public cultural service system, realizing the vivid and lively rural culture of rural culture and the long -term development of rural cultural literacy, to promote the revitalization of rural culture and improve the overall level of rural public culture.

The dilemma and path of rural college students returning to their hometowns for employment and entrepreneurship in the post-epidemic period under the background of big data

Abstract The dilemma of exploring the children in institutions of higher learning to find jobs or start their own companies of rural origin and return to their hometown is paving the way for college students to find jobs of rural origin. In this paper, a decision tree optimized by a partial least squares regression algorithm is proposed to construct a DT-PLS data classification model in the case of cloud data, and the performance of the DT-PLS model is evaluated for the DT-PLS model. Using college students’ employment and entrepreneurship data from colleges and universities as examples, two factors that influence college students of rural origin to return to the registered permanent residence to find a job or start a company, namely subjective factors and contextual factors, are mined, and data analysis is carried out for the two influencing factors. From the 12 sub-indicators of subjective factors, the mean values of those considered very unconformable, unconformable, uncertain, conformable and very conformable were 17.87%, 15.38%, 10.82%, 16.09% and 39.84%, respectively. Regarding the 10 sub-indicators of contextual factors, the mean values of the percentages of those considered very non-conforming, non-conforming, uncertain, conforming, and very conforming were 6.56%, 20.95%, 13.69%, 26.13%, and 32.67%, respectively. The DT-PLS classification, the main method here, analyzes the current dilemmas of returning college students of rural origin to entrepreneurship and employment and prompts more college students to invest in the grassroots to provide fresh talent blood for rural revitalization.

Research on performance evaluation and optimization of college budget management under the background of big data

Abstract At present, due to the limitations of technology and resources, the comprehensive budget management generally has problems such as imperfect foundation of establishment, weak binding force of execution, and lack of performance appraisal system. These problems become more prominent in the context of the era of big data. The use of big data technology, such as large capacity, real-time control, intelligent Settings and other characteristics, will be able to improve the current many problems. Therefore, this paper focuses on how to combine big data with comprehensive budget management. This paper holds that it is not enough for comprehensive budget management to stay in the current stage, but also need to use big data technology, which is a higher level of information stage. Therefore, this paper adopts the method of double subordination fuzzy support vector machine to study the effect of budget management of scientific research projects in Chinese universities. Based on the construction of comprehensive budget management performance evaluation index system throughout the whole process of college budget cycle, taking S university as an example, this paper analyzes the performance of comprehensive budget management in S university, and points out that big data can optimize and innovate the budget management mode, which has great significance for college budget management.

Research on innovative cultivation mode of English and American literature translation talents based on internet environment

Abstract English and American literature translation can help readers appreciate foreign cultures and deepen their interpretation and knowledge of English and American literature. There are more relevant contents involved in the teaching of English and American literature translation. Translation is a very important task for different countries to communicate and must be given enough attention, and the translation of English and American literature is very important for readers to deeply appreciate the cultural style of foreign countries. In order to solve these problems and find the appropriate strategies for translating talents from English and American literature. In this paper, we will analyze this specifically, meet the requirements of training translation talents, combine the development of our country and our own background, and create a new training mode according to the Internet environment, so as to strengthen the training of talents. At the same time, the idea of constructing the teaching and composite innovative talents cultivation model of environmental ecology courses under the background of Internet big data is proposed, and the characteristics and functions of the innovative teaching and talents cultivation model are analyzed. The ultimate goal is to cultivate outstanding talents with a sense of family, global vision, innovation and practical ability, and to promote their application through teaching salons and symposiums. With the use of this model, the current environment of the Internet has been innovated in the innovative mode of talent training, and the corresponding training methods have created the best learning space for students and improved their ability to read original English and American texts and translate their works.

Research on the Impact of Information Literacy on the Creativity of Foreign Language Teachers in Chinese Universities Under the Background of Big Data

The arrival of big data poses a challenge to foreign language teachers in colleges and universities. Based on the background of big data, this study verifies the impact of information literacy on creativity of foreign language teachers in colleges and universities. By collecting 205 foreign language teachers from colleges and universities in central and western China, the hypothesis was verified by descriptive statistics, testing of validity and reliability, correlation analysis, and regression analysis. The results show that information literacy has a significant positive impact on creativity, among which information knowledge, information awareness, and information ability have a significant positive impact on creativity to varying degrees, while information morality has no significant impact on creativity.

Exploration of Online Marketing Strategies for Young Entrepreneurs Under the Background of Big Data Accuracy

This paper mainly studies the development and breakthrough of young entrepreneurs in multi-sensory marketing strategies in online marketing. Based on the background of big data, the combination of online marketing and sensory marketing was studied and discussed by using qualitative research, focus groups, literature research, measurement research and other methods, and concluded that online sensory marketing is indeed a hot topic at present, which has been valued by young entrepreneurs and brands. Some progress has been made, but deeper extended studies can be conducted.

Intelligent Modeling Analysis of the Practice Path of Vocational Education Fusion of Education and Production Under the Background of Big Data

Intelligent Modeling Analysis of the Practice Path of Vocational Education Fusion of Education and Production Under the Background of Big Data

Empirical Study on Civil Law Protection of the Right to Be Forgotten in the Era of Big Data

Under the background of big data, the legal protection of the right to be forgotten is ofgreat significance in safeguarding people's interests and dignity. On the basis ofclarifying the concept, legal characteristics and significance of the right to be forgotten,this paper analyzes the protection status of the right to be forgotten in the currentjudicial practice and the problems such as fuzzy content, nature orientation, difficult toguarantee the technical basis and lack of relief paths, and finally provides legal basis andrule guidance for establishing and improving the protection of the right to be forgottenin civil law. This research will effectively improve the data subject's awareness ofpersonal information protection and use and strengthen the legal protection of the rightto personality.

Development and Application Status of Healthcare Big Data

As informatization progresses in society, the data in the health and medical fields is soaring quickly, which promotes the healthcare big data generated. Healthcare is closely related to each individual's life and health, and healthcare big data has both brought great opportunities and challenges to the health and medical field. Therefore, the development of big data in healthcare is being focused on in the medical and health fields. At present, healthcare big data are being applied in clinical diagnosis, public health, infectious disease prevention, medical research, and drug development. However, these applications are not being used very efficiently nowadays. A large amount of big data is stored, but most of it still cannot be used because of the hazards of storing uniform and different structure data types. This paper uses literature searching to summarize the status quo of healthcare big data at present. Based on the background of big data, this paper describes the sources and characteristics of healthcare big data and figures out the promising applications in the health and medical areas. Moreover, this research also focuses on the data governance of healthcare big data and represents the problems now, such as the barrier between information due to non-uniform data collection methods, and provides development strategies.

Application Prospect of the SOFA Score and Related Modification Research Progress in Sepsis.

In 2016, the SOFA score was proposed as the main evaluation system for diagnosis in the definition of sepsis 3.0, and the SOFA score has become a new research focus in sepsis. Some people are skeptical about diagnosing sepsis using the SOFA score. Experts and scholars from different regions have proposed different, modified versions of SOFA score to make up for the related problems with the use of the SOFA score in the diagnosis of sepsis. While synthesizing the different improved versions of SOFA proposed by experts and scholars in various regions, this paper also summarizes the relevant definitions of sepsis put forward in recent years to build a clear, improved application framework of SOFA score. In addition, the comparison between machine learning and SOFA scores related to sepsis is described and discussed in the article. Taken together, by summarizing the application of the improved SOFA score proposed in recent years in the related definition of sepsis, we believe that the SOFA score is still an effective means of diagnosing sepsis, but in the process of the continuous refinement and development of sepsis in the future, the SOFA score needs to be further refined and improved to provide more accurate coping strategies for different patient populations or application directions regarding sepsis. Against the big data background, machine learning has immeasurable value and significance, but its future applications should add more humanistic references and assistance.

The Predicament of College English Curriculum Education Reform under the Background of Big Data and Internet of Things

The Predicament of College English Curriculum Education Reform under the Background of Big Data and Internet of Things

Research on the coordinated development of cross-border e-commerce and logistics under the background of big data

Abstract Cross-border electronic platform trade is an important embodiment of the digitalization of international trade, with much attention and response to national policies. This is a global business activity in which traders from different countries negotiate and conclude deals online, and the flow of goods is realized through international transportation. Taking the effectiveness of the coordinated development of cross-border trade and international transportation as the direction of exploration, we study the development mechanism of the harmonious, proper coordination, and virtuous cycle of both from the digital background. According to the established model assumptions, based on the principles of science, objectivity, operability, and representativeness, the evaluation system of coordinated development level is constructed, and the subsystem sequential covariate efficacy function and the composite system coordination degree are calculated. From the results of correlation and coordination degree analysis, it shows that the total volume of transactions in this form of trade grows from $1.4 trillion in 2013 to $8.7 trillion in 2020, with an average annual growth rate of 32%. The orderliness of the cross-border logistics subsystem keeps increasing between 2013 and 2020, and the growth rate reached an average of 15.84 %/year. On the whole, the orderliness of each of the two subsystems steadily increases year by year. The resulting coordinated development trend of electronic trade between countries and international transportation coincides with the electronic trade between countries stepping into a brand-new development period, which is sufficient to verify the science and reasonableness of the evaluation system.

Intelligent Smart Community Public Service Supply Optimization Algorithm under Big Data Background for Smart City

Abstract Nowadays, the organizational structure of public service facilities is loose, which is not conducive to the development and progress of public services. Therefore, it is very important to find an optimization algorithm for the supply of public services in intelligent communities. Aiming at the resource waste problem of high repetition rate and low utilization rate in the current method, an optimization algorithm for providing public services in intelligent communities under the background of big data is proposed. According to the attributes of planning factors, the planning scheme of the spatial layout is divided into multiple subsystems and the goodness value of the factors in the scheme is calculated by using the single factor modular root method. Taking each subsystem as a factor, the comprehensive goodness value of each decision scheme is obtained respectively, so as to complete the creation of the spatial layout model of public service facilities. Based on this model, the fractal dimension, shape, and discrete index of a land patch are calculated for the public service facilities of the intelligent community, and the calculated results are used to optimize the public service supply in intelligent communities. The experimental results show that the proposed algorithm can optimize the public service supply of intelligent communities and give them the advantages of low repetition rate and high utilization rate.

Establishment and application of traditional Wushu intelligent learning resource database under the background of big data

Abstract The survival soil on which the traditional martial arts culture depends is becoming thinner and thinner. A large number of superb martial arts skills and martial arts experience disappear with the passing of the older generation of martial artists. In order to realize the information preservation of traditional Wushu, this paper puts forward the establishment and application of traditional Wushu intelligent learning resource database under the background of big data. In the context of big data, data mining technology is used to realize personalized recommended learning services, obtain the feature structure of intelligent learning system through operation, extract the average dynamic features of specific data in the resource database, obtain fuzzy constraints according to the value, determine the membership function, and adjust the membership function parameters through training fuzzy neural network, so as to gradually improve the reasoning accuracy. Finally, the matching rule set is used to filter the resource data packets to achieve the purpose of communication. In order to verify the effect of the model, compared with the traditional model, the results show that when the number of nodes is 500, the average transmission rate is as high as 90%, the average delay is 12 seconds, and the throughput performance is 91%. It can be verified that the model designed in this paper can effectively improve the propagation rate, reduce the average delay and strengthen the throughput performance.