Research on the Changing Trend of Employment-Relevant Terms Based on Internet Big Data Analysis

With publicly-available data collected from mainstream information platforms, this study used the term frequency inverse document frequency (TF-IDF) algorithm to detect 74 popular terms and phrases about employment, analyzed the changes in the ranking of these terms and phrases, and visualized the changing trend in the attention to employment skills from 2017 to 2019. The research result will facilitate application of big data technology to teaching administration in colleges, and provide a guide for college students to plan their study of vocational skills.

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Big Data Analysis of Sports and Physical Activities among Korean Adolescents

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17155577 ◽

2020 ◽

Vol 17 (15) ◽

pp. 5577

Author(s):

Sung-Un Park ◽

Hyunkyun Ahn ◽

Dong-Kyu Kim ◽

Wi-Young So

Keyword(s):

Physical Activity ◽

Big Data ◽

Social Network ◽

Data Analysis ◽

Frequency Analysis ◽

Big Data Analysis ◽

Inverse Document Frequency ◽

Korean Adolescents ◽

Document Frequency ◽

Sports And Physical Activity

The Korean government (Ministry of Culture, Sports and Tourism, Ministry of Health and Welfare, and Ministry of Education) has framed policies and conducted many projects to encourage adolescents to be more physically active. Despite these efforts, the participation rate of physical activity in Korean adolescents keeps decreasing. Thus, the purpose of this study was to analyze the perception of sports and physical activity in Korean adolescents through big data analysis of the last 10 years and to provide research data and statistical direction with regard to sports and physical activity participation in Korean adolescents. For data collection, data from 1 January 2010 to 31 December 2019 were collected from Naver (NAVER Corp., Seongnam, Korea), Daum (Kakao Corp., Jeju, Korea), and Google (Alphabet Inc., Mountain View, CA, USA), which are the most widely used search engines in Korea, using TEXTOM 4.0 (The Imc Inc., Daegu, Korea), a big data collection and analysis solution. Keywords such as “adolescent + sports + physical activity” were used. TEXTOM 4.0 can generate various collection lists at once using keywords. Collected data were processed through text mining (frequency analysis, term frequency–inverse document frequency analysis) and social network analysis (SNA) (degree centrality, convergence of iterated correlations analysis) by using TEXTOM 4.0 and UCINET 6 social network analysis software (Analytic Technologies Corp., Lexington, KY, USA). A total of 9278 big data (10.36 MB) were analyzed. Frequency analysis of the top 50 terms through text mining showed exercise (872), mind (851), health (824), program (782), and burden (744) in a descending order. Term frequency–inverse document frequency analysis revealed exercise (2108.070), health (1961.843), program (1928.765), mind (1861.837), and burden (1722.687) in a descending order. SNA showed that the terms with the greatest degree of centrality were exercise (0.02857), program (0.02406), mind (0.02079), health (0.02062), and activity (0.01872) in a descending order. Convergence of the iterated correlations analysis indicated five clusters: exercise and health, child to adult, sociocultural development, therapy, and program. However, female gender, sports for all, stress, and wholesome did not have a high enough correlation to form one cluster. Thus, this study provides basic data and statistical direction to increase the rate of physical activity participation in Korean adolescents by drawing significant implications based on terms and clusters through bid data analysis.

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Design of Computer Multimedia Intelligent Platform Using Big Data Analysis

Journal of Interconnection Networks ◽

10.1142/s0219265921430246 ◽

2022 ◽

Author(s):

Zhenna Chen

Keyword(s):

Big Data ◽

Data Analysis ◽

Multimedia Information ◽

Real Time ◽

Data Storage ◽

Big Data Analysis ◽

Intelligent Vehicle ◽

Time Data ◽

Vehicle Operation ◽

Big Data Technology

This exploration aims to transfer, process and store multimedia information timely, accurately and comprehensively through computer comprehensive technology processing, and organically combine various elements under the background of big data analysis, so as to form a complete intelligent platform design for multimedia information processing and application. In this exploration, the intelligent vehicle monitoring system is taken as an example. Data acquisition, data transmission, real-time data processing, data storage and data application are realized through the real-time data stream processing framework of [Formula: see text] of big data technology. Data interaction is realized through Spring, Spring MVC, VUE front-end framework, and Ajax asynchronous communication local update technology. Data storage is achieved through Red is cache database, and intelligent vehicle operation supervision system is achieved through multimedia information technology processing. Its purpose is to manage the vehicle information, real-time monitor the running state of the vehicle and give an alarm when there are some problems. The basic functions of vehicle operation monitoring and management system based on big data analysis are realized. The research on the design of vehicle operation monitoring and management system based on big data analysis shows that big data technology can be applied to the design of computer multimedia intelligent platform, and provides a reference case for the development of computer multimedia intelligent platform based on big data analysis.

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Research on the Communication Transformation and Its Risk Prevention Method in the Background of Big Data

Journal of Physics Conference Series ◽

10.1088/1742-6596/2136/1/012041 ◽

2021 ◽

Vol 2136 (1) ◽

pp. 012041

Author(s):

Haoyang Zhu

Keyword(s):

Big Data ◽

Data Analysis ◽

Big Data Analysis ◽

Risk Prevention ◽

The Core ◽

Practical Development ◽

The Subject ◽

Prevention Method ◽

Streaming Big Data ◽

Big Data Technology

Abstract The communication based on big data technology is an organized communication form built with data and algorithms as the core, which has a very serious risk of liquefaction in the practical development. Therefore, based on the understanding of the transformation of communication ontology and the uncertainty of the subject under the background of big data technology, this paper studies and analyzes the risk prevention countermeasures based on streaming big data analysis according to the alienated risks it presents.

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Copying and Recreation Methods of Painting Works Relying on Mobile Digital Multimedia Big Data Analysis

Computational Intelligence and Neuroscience ◽

10.1155/2022/7734506 ◽

2022 ◽

Vol 2022 ◽

pp. 1-9

Author(s):

Li Xue ◽

Chuangjian Yang

Keyword(s):

Big Data ◽

Data Analysis ◽

Image Coding ◽

Feature Recognition ◽

Big Data Analysis ◽

Simulation Methods ◽

Multimedia Big Data ◽

Digital Multimedia ◽

Processing Module ◽

Big Data Technology

In order to improve the effect of copying and recreation of painting works, this paper combines mobile digital multimedia big data technology to improve the image coding algorithm, identify the characteristics of existing works, apply the algorithm to the detailed analysis of painting works, and construct the main functional structure modules of the system. Moreover, this paper combines the existing hardware equipment to construct the painting works’ recreation system and obtains the image processing module. After the system is constructed, the effect of copying and recreating painting works is analyzed through the mobile digital multimedia big data analysis technology. Finally, this paper constructs the system of this paper through simulation methods and uses experiments to calculate the feature recognition effect and copy effect of the painting works of the system. Through experimental analysis, it can be known that the copying and recreation system of painting works based on mobile digital multimedia big data analysis proposed in this paper can help painters effectively improve the effect of recreation.

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Research on Influencing Factors of Export Complexity of Chinese High-tech Industry Based on Big Data Analysis

E3S Web of Conferences ◽

10.1051/e3sconf/202123503013 ◽

2021 ◽

Vol 235 ◽

pp. 03013

Author(s):

Junsheng Wang ◽

Zhong Ziqi ◽

Haoran Wang

Keyword(s):

Big Data ◽

Data Analysis ◽

Rapid Development ◽

Big Data Analysis ◽

High Tech ◽

Industrial Agglomeration ◽

High Tech Industry ◽

Technical Content ◽

Big Data Technology

Export trade can measure the economic level of a country, but it can only reflect the amount of exports, but not the quality of exported products and the technical content of exported products. Therefore, domestic and foreign scholars have begun to study the complexity of export technology. The development of big data technology makes it possible to analyze the export complexity using big data analysis technology. With the rapid development of high-tech industries represented by high-end manufacturing, there is more and more research on the export of high-tech industries. Based on the existing research results, this article first introduces the current export profile of high-tech products and explains the concept of export complexity. Then, the flow of big data analysis was sorted out. Finally, this paper theoretically analyzes the influence of industrial agglomeration on industrial export complexity, and uses big data analysis and regression verification. The results show that industrial agglomeration has a significant role in promoting the export complexity of China’s high-tech products.

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Overview of Construction and Application of Big Data Analysis Platform

Journal of Electronic Research and Application ◽

10.26689/jera.v4i6.1750 ◽

2021 ◽

Vol 4 (6) ◽

Author(s):

Difei Zhang

Keyword(s):

Big Data ◽

Data Analysis ◽

Resource Sharing ◽

Data Exchange ◽

Big Data Analysis ◽

Time Data ◽

Data Platform ◽

Complete Data Analysis ◽

Analysis Platform ◽

Big Data Technology

Big data technology is widely spread around the world, and is constantly developing and applying. In order to enhance the application value of big data analysis platform, it is necessary to constantly improve the data analysis and processing capacity of big data platform, so as to build a complete data analysis platform, realize resource sharing and real-time data collection. As a key point of contemporary information development, big data analysis platform is of great significance to promote social data exchange. Based on this, this paper focuses on two aspects: first, it describes the construction process and content of big data platform; second, it summarizes the relevant application and development of big data platform for reference.

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Analysis on the Application of Big Data Technology in “Internet + Wisdom Judicial Expertise”

E3S Web of Conferences ◽

10.1051/e3sconf/202125101029 ◽

2021 ◽

Vol 251 ◽

pp. 01029

Author(s):

Juan Xu

Keyword(s):

Big Data ◽

Data Analysis ◽

Information Structure ◽

Big Data Analysis ◽

Resource Network ◽

Big Data Application ◽

Application Requirements ◽

Analysis Platform ◽

Judicial Expertise ◽

Big Data Technology

It can be seen from the current development process of the field of forensic expertise that there are many problems in the application of the mechanism of the information structure. These problems lead to imperfect informatization construction process and too limited identification forms, which will have a great impact on the final identification results. This article summarizes the main content of big data technology in the construction of “Internet + Wisdom Judicial Expertise”. This article discusses the specific application recommendations of big data technology in the “Internet + smart forensic appraisal”, from focusing on forensic appraisal data collection and sorting, understanding forensic appraisal big data application requirements, building forensic appraisal big data analysis platform, and strengthening big data analysis platform resource network sharing four aspects.

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Research on Higher Vocational Network Teaching Quality Evaluation System Based on Big Data Analysis

contemporary Education and Teaching Research ◽

10.47852/bonviewcetr2021020109 ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Xue-yan Li

Keyword(s):

Big Data ◽

Data Analysis ◽

Evaluation System ◽

Online Teaching ◽

Quality Evaluation ◽

Teaching Quality ◽

Big Data Analysis ◽

Network Teaching ◽

Quality Evaluation System ◽

Big Data Technology

Internet technology has developed rapidly, and online teaching has become the development trend of teaching in higher vocational colleges, which is conducive to modern learning methods for students and innovative teaching models for teachers. However, online teaching is still in the preliminary stage of development, and there is no unified standard for teaching quality evaluation. For this reason, big data technology can be integrated into the evaluation of higher vocational online teaching. This article first introduces the concept of online teaching quality evaluation, and then The application advantages of big data technology in the evaluation of network teaching quality are analyzed, and the key points of the construction of a higher vocational network teaching quality evaluation system based on big data analysis are explored in detail.

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