Background Of Big Data Research Articles

The application of business intelligence system based on big data in e-commerce data analysis

In the face of the rapid development of modern science and technology, in order to ensure that the commercial level is in line with The Times, we need to change the traditional operation mode, and fully apply the science and technology to the e-commerce data analysis. Nowadays, driven by the era of big data development, social process, bring new changes to daily life, consumption, such as electricity is a new product, as the latest business model in modern society, has an important impact on market development, want to ensure electricity enterprises can meet the demand of social development, then from the perspective of electricity data analysis, effectively grasp the market changes, so as to more effective to carry out subsequent work, to fundamentally improve the comprehensive competitiveness of electricity enterprises in the modern market. In view of this, in order that the article wants to ensure the smooth progress of the e-commerce data analysis work, it should start with the business intelligence system under the background of big data, and combine it to ensure the steady development of the e-commerce industry.

Design and Practice of Japanese Interactive Teaching Systems in Colleges and Universities Under the Background of Big Data

Relying on the background of big data, this paper introduces the blended teaching model into the secondary vocational Japanese oral classroom and explores whether the teaching model is conducive to the improvement of the secondary vocational Japanese oral learning effect and teaching effect. In order to make this research more scientific and effective, this paper refers to a large number of literature materials. First, the purpose, content, and methods of this research are clarified; secondly, the relevant literature is sorted out and summarized. The SPOC blended teaching design was carried out, and teaching experiments were carried out accordingly. Finally, the data collected during the experiment were compared and analyzed, and the research results were verified with objective data. Research has shown that the use of a Japanese language teaching system enhances students' learning experience, promotes effective use of time, and improves overall learning outcomes.

Strategies for Cultivating Postgraduates' English Autonomous Learning Ability Under the Background of Big Data

The wide application of big data not only provides convenience for the teaching between teachers and students, but also plays a great role in the education and training of college students. However, how to cultivate students' ability to learn English independently in the current era remains to be studied. Under the background of big data, it is very important for today's education to make effective use of this technological advantage to explore scientific and reasonable strategies, stimulate college students' attention to English autonomous learning, and explore the learning process. Investigating the value of specific big data technology is also an important consideration in this study. At the same time, graduate students who are not English majors usually have fewer English courses, and students' English level is also very different. Therefore, we should also pay attention to improving students' oral English ability and pay special attention to the cultivation of students' self-discipline and autonomous learning ability.

Challenges and countermeasures of international economy and trade under the background of big data

In the era of big data, international economy and trade are facing unprecedented challenges and opportunities. This paper analyzes the influence of big data on international economy and trade, discusses the related challenges, and puts forward the countermeasures. In terms of challenges, big data brings privacy and security risks, data standardization issues and the widening digital divide. In order to meet these challenges, the international community needs to strengthen data security regulations, formulate international data standards, promote digital inclusion, and improve the transparency of data governance. In addition, this paper also emphasizes the great potential of big data in international trade, including improving market access, reducing trade costs and optimizing supply chain.

Retracted: E-Commerce Enterprise Supply Chain Cost Control under the Background of Big Data

Retracted: E-Commerce Enterprise Supply Chain Cost Control under the Background of Big Data

Exploration of the Innovation Path of Enterprise Archive Management Mode in the Context of Big Data

Archives, as the materials for all kinds of work assessments, are the imprints of the past and the basis for guiding the future. Compared with traditional archive management methods, informatized archive management is more efficient and of better quality. The efficiency of various departments of society has made a qualitative leap and improvement under the background of the information age. To develop archive management business and make archive management more efficient and safe, it is necessary to explore a scientific and efficient informatized archive management work mode on the practical road of the new era. The advent of the big data era has brought fundamental changes to data mining technology. It can analyze and intelligently mine massive data, making it possible to mine data at a deeper level. Therefore, it is necessary to actively explore archive data mining technology, so that data mining technology can be widely applied to archive management work, as far as possible to mine and transmit potential archive information, play its due role, and maximize the economic and social benefits of archive data. This article, through the analysis of the characteristics of archive management under the big data environment, points out the problems existing in the current archive management work and the challenges and necessity of innovation in the archive management mode under the big data background, and discusses how to improve the innovation of the archive management work mode from practice

Research on the Optimization of Vocational Education Resources Allocation Based on Big Data

This article is based on the resource analysis function of CNKI database, sorting out the keyword network analysis, and then sorting out the current situation of vocational education resource allocation under the background of big data. Then it combs out some problems existing in the current allocation of vocational education resources, such as the total amount of educational resources to be increased, the unbalanced investment in education funds and the lack of data resources professionals. Finally, based on some existing problems in the allocation of vocational education resources, this paper puts forward some solutions, such as multi-online education based on the platform, and the education policy under the principle of resource integration and sharing in colleges and universities.

Research on the Digital Transformation of Financial Management in Small and Medium-sized Enterprises Under the Background of Big Data and Cloud Computing

Research on the Digital Transformation of Financial Management in Small and Medium-sized Enterprises Under the Background of Big Data and Cloud Computing

Research on the Optimization of the Joint Mechanism of "One Matter" in Grassroots Government Services under the Background of Big Data -- Taking M City as an Example

Research on the Optimization of the Joint Mechanism of "One Matter" in Grassroots Government Services under the Background of Big Data -- Taking M City as an Example

Research on the innovation of logistics and catering management in colleges and universities under the background of big data

Research on the innovation of logistics and catering management in colleges and universities under the background of big data

大数据背景下统计学专业教学与思政教育的深度融合探索

大数据背景下统计学专业教学与思政教育的深度融合探索

RETRACTION: Application of Machine Learning Algorithms in the Development and Consumption Trend of Green and Intelligent Vehicles under the Background of Big Data

RETRACTION: Application of Machine Learning Algorithms in the Development and Consumption Trend of Green and Intelligent Vehicles under the Background of Big Data

Research on Innovative Parenting Mode of Ideological and Political Education in Colleges and Universities under the Background of Big Data

Abstract In the context of the new era, the education concept has been transformed, and practical parenting has attracted much attention, and the talent cultivation mechanism of colleges and universities therefore urgently needs to be innovated to meet the requirements of the development of the times. In this paper, we optimize the original objective function of the sample of students’ civic education, use Taylor’s formula to expand the objective function approximation, calculate the complexity of the tree model, and complete the construction of XGBoost student learning behavior. Improve the K-means algorithm based on Canopy, combined with the improved SVM algorithm, to provide early warning for students’ academic performance in Civics. The assessment framework for teaching effect is designed to assess students’ Civics learning process. The results show that after the intervention of the model proposed in this paper, the students’ Civics performance improved from 60.59 to 65.63. The cognitive ability of Civics has a significant effect on social learning and individual learning behaviors at the same time, with the effects of 0.8623 and 0.9782. The innovative nurturing model of Civics in colleges and universities is improved by the proposed model in this paper.

The Path of “Dual-Teacher” Teacher Cultivation in Applied Local Higher Teacher Colleges under the Background of Big Data

Abstract The cultivation path of the applied “dual-teacher” teacher team in this paper mainly relies on the qualification standard and evaluation system. Big data technology is used to collect data, deeply mine fragmented data, and further extract index factors that affect the quality of teachers. The multi-level fuzzy hierarchical evaluation model realizes the quantification of the decision-making process with less quantitative information, and determines the weights through the multi-level comparison of importance, to test and evaluate the teaching ability of “dual-teacher” teachers. The results show that, among the 166 survey respondents, 77 respondents belong to the “ Dual-teacher” teachers, accounting for about 45.03%. The primary needs and ways for most of the teachers to participate in the training of “dual-teacher” teachers are to improve the practical ability of industry and enterprise positions (score 0.86) and the school-based training of dual-teacher teachers (0.93), which is centralized in the college. In evaluating “dual-teacher” teaching, the weight of industry-teaching integration is 0.3378, so the ability of industry-teaching integration is a more meaningful indicator. College students are satisfied with “dual-teacher teaching”, and the score shows that the essential satisfaction is more than half of the total number of samples, which is 343.

Research on the Path to Improve the Employment Quality of Private College Students under the Background of Big Data

Abstract In this paper, we use space-sensitive crawler technology to obtain the initial data of college students’ employment quality research from the websites or databases of private colleges and universities. We determine the evaluation indexes of college students’ employment quality through data cleaning and conversion of the initial data. On this basis, because of the limitations of the clustering algorithm, grey correlation analysis is used to optimize the clustering algorithm, and the evaluation model of college students’ employment quality based on grey correlation optimization clustering is constructed. Then the clustering analysis of college students’ employment evaluation indexes is carried out. The results show that the main influencing factors of job satisfaction of female graduates in some disciplines such as literature, history and philosophy and education and law are family economic situation Q7 (-1.9328), participation in innovative and entrepreneurial activities Q8 (29.2178), political outlook Q11 (3.0279), and graduation destination Q13 (2.5824), and that this paper’s method is effective in revealing the key factors. This study benefits the enrichment and innovation of the research content of employment quality. It provides theoretical support for solving the problem of future employment quality of college students in private colleges and universities.

Research and analysis of Python in economics courses in the background of big data

Research and analysis of Python in economics courses in the background of big data

Exploration of badminton teaching reform and development ideas in colleges and universities under the background of big data

Abstract Intelligent wearable devices effectively collect real-time data and physiological indicators of students performing badminton sports activities through the functions of collecting, organizing, and analyzing mobile big data. Meanwhile, the SVM classification algorithm based on data fusion theory is proposed to realize the collection and monitoring of human posture and other signals. The smart wearable device is used as an auxiliary teaching means to help students quickly master basic movement skills, and a 32-credit-hour teaching experiment is conducted to compare and analyze the effect of its teaching impact. It was analyzed that the physical quality and basic skills of hairball of the two groups of students before the experiment were basically similar (P>0.05). The mean values of badminton long-throw movement of the experimental group before the experiment and after the experiment were 4.72 and 5.73, respectively, and showed a significant difference (P<0.01), and the four movements such as forehand serve high long ball were also significantly improved (P<0.01). 43.75% of the students felt that the smart wearable device badminton special learning was of interest. The reform and development of badminton teaching in colleges and universities in the era of big data can be promoted by this paper’s method.

Research on the standardization of higher education management under the background of big data

Research on the standardization of higher education management under the background of big data

Optimization of economic management mode and risk control based on the background of big data

Abstract In this paper, the enterprise data is processed without outline, PCA is used for data dimensionality reduction SVM is used to categorize the dimensionality reduction data, and the prediction of future trends is made based on the categorization situation. The PCA-SVM risk control model based on big data is established, and the PSO particle swarm algorithm is used to find the optimal parameters for SVM to improve its classification performance and optimize the prediction of enterprise management risks. In order to test the effect of risk management and control optimization, data processing is carried out for two types of companies, namely, banking and real estate industries, and predictions are made for their future operation based on the processing results. During the period from 2022Q1 to 2022Q2, the CSI banking index falls from 0.11 to −0.59; the output of this paper’s model is 1, i.e., there is a risk, and it is predicted that the values of Q1 and Q2 in 2024 are 1, and a financial risk may occur. The PCA-SVM model has a 95% determination rate for training samples, and it can predict low-risk sample companies accurately with a comprehensive error rate of only 6.67%. The data proves that the model can effectively predict the future risk status of enterprises according to the existing information and provide optimization reference for enterprises to change their economic management mode.

The impact of personalized recommendation on purchase intention under the background of big data

The impact of personalized recommendation on purchase intention under the background of big data