Ontology Learning in Text Mining for Handling Big Data in Healthcare Systems

Irfan, Rizwana; Rehman, Zobia; Abro, Ahsanullah; Chira, Camelia; Anwar, Waqas

doi:10.1166/jmihi.2019.2681

Cited by 7 publications

(4 citation statements)

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“…e information extracted by data mining has the features of validity, practicability, and unknowingness [4].…”

Section: Introductionmentioning

confidence: 99%

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College Physical Education and Training in Big Data: A Big Data Mining and Analysis System

Wang

2021

Journal of Healthcare Engineering

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Recently, big data has been broadly used as a research method in all aspects of analysis, prediction, and evaluation. The application of big data to college students’ physical education plays a significant role in encouraging the completion of physical education at various levels. The application of the Internet and the advent of smartphones impact the way college students participate in physical exercise. At present, more and more students begin to participate in sports, and students’ demand for physical training is increasing. During physical education training, a lot of data is generated every moment because of various actions and behaviors. Due to technical limitations, these data were not effectively collected and applied. In this environment, the development and management of sports data mining systems have become more and more important. This paper designs an intelligent big data system for college physical education training. The study mainly focuses on data decentralization, lack of data talents, insufficient technical support, and low utilization of venues in physical education. While designing a big data system, the data is collected based on ease of data collection, and a response framework with excellent performance in storing analytical data is selected. The design and management of this system have a certain significance for the improvement and optimization of current college physical education training.

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“…e information extracted by data mining has the features of validity, practicability, and unknowingness [4].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, data mining technology is a new method that can increase efficiency and scientific decision making. The information extracted by data mining has the features of validity, practicability, and unknowingness [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

College Physical Education and Training in Big Data: A Big Data Mining and Analysis System

Wang

2021

Journal of Healthcare Engineering

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“…With the continuous development of science and technology, data and information in various fields and research disciplines are growing at an exponential rate [ 7 , 8 ]. Especially in recent years, in order to find potential users in various industries in the market, more and more daily information and data will be reserved for users, the rational use of data and information has become more and more important in daily production activities, and the application requirements for data and information are spreading in all aspects of people's lives [ 9 ]. With the advent of the era of big data, the reasonable division and application of data information can make people's production and life more convenient and efficient [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Internet Digital Economy Development Forecast Based on Artificial Intelligence and SVM-KNN Network Detection

Zhou

Mei

2022

Computational Intelligence and Neuroscience

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The development and spread of Internet technology have made it easier to find web servers. People can browse various websites to shop or pay for living expenses, which brings great convenience to life, but as a result, Internet security problems continue to appear. This article is based on a detailed theoretical analysis of mainstream algorithms, making an analysis of web logs which is of great significance and practical value. In addition, through reasoning analysis, technical support is provided for improving the weight factor of the KNN (K-nearest neighbor) algorithm, and the literature research method of the SVM-KNN hybrid algorithm and the KNN classifier is proposed. This paper conducts a detailed theoretical analysis based on the mainstream algorithms that are widely used in the current classification technology and integrates the mainstream classification algorithms in real-life applications and popularization, selecting the support vector machine and KNN calculation method. In the digital economy development model, although China has a large number of netizens, obvious late-comer advantages and institutional advantages as a guarantee, due to the constraints of two key factors, capital and technology, a series of social problems have also arisen. During the transformation of the digital economy, prominent digital security issues, high-risk vulnerabilities, and increasing number of cyber-attacks, along with uneven data quality levels and lagging laws and regulations, have brought many challenges and obstacles.

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“…As the times evolve, the style presented by the game of basketball will become the brand of basketball of that era. Style is the research crystallization and core of the winning elements of the game [4]. The gradual improvement in the understanding of the laws of basketball, the understanding of the game-winning factors from shallow to deep, and the emergence of ways to defeat the opponent have driven the display of various styles.…”

Section: Introductionmentioning

confidence: 99%

Construction and Simulation of a Multiattribute Training Data Mining Model for Basketball Players Based on Big Data

Yun-bin

Wei

2021

Wireless Communications and Mobile Computing

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This paper provides an in-depth analysis and research on the construction and simulation of a big data model for multiattribute training of basketball players. To get a more accurate and three-dimensional information, the training can use a multitraining target robot, i.e., to detect feedback on multiple indicators at the same time and correct the player’s errors in time; the other is an auxiliary robot, which can actively correct technical movements and train the player to form muscle memory, compared with general training. The analysis results show that by either constructing a human model or designing an active assistive robot, the player’s technical movements can be regulated accordingly, protecting the player’s body laterally and improving the player’s ability. An assisted training system with an accurate model of physiological indicators is constructed based on the data of the player throughout the season. The Warriors, who have applied this system, not only have the best record in recent years but also have the lowest injury rate in the league, indicating that this method has indeed reduced the injury rate of players.

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Ontology Learning in Text Mining for Handling Big Data in Healthcare Systems

Cited by 7 publications

References 0 publications

College Physical Education and Training in Big Data: A Big Data Mining and Analysis System

College Physical Education and Training in Big Data: A Big Data Mining and Analysis System

Internet Digital Economy Development Forecast Based on Artificial Intelligence and SVM-KNN Network Detection

Construction and Simulation of a Multiattribute Training Data Mining Model for Basketball Players Based on Big Data

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