The Application of Data Mining Technology in the Remote Open Management System

2014 ◽  
Vol 687-691 ◽  
pp. 1141-1144
Author(s):  
Mei Bai
Keyword(s):  
Data Mining ◽  
Quality Assessment ◽  
Information Management ◽  
Management System ◽  
Information Management System ◽  
Assessment System ◽  
Detailed Design ◽  
Mining Technology ◽  
Open Management ◽  
At Home

This paper introduces the concept of database and data mining, combined with management system of quality assessment system and method of data mining technology. In this paper, applying the data mining skill to the field of remote open management system, introduces the development of data mining in China and the necessity and importance of data mining in remote open information management system. This thesis analyzes the main problems in the remote open management system. On the basis of the relevant researches both at home and abroad, it presents the significance of the application of data mining in remote open management system. It analyzes the needs of the system based on data mining and presents a detailed design and implication of such a system.

Data Mining technology as a tool for supporting analytical decision making process in Health Information Management System (HIMS)

2021 ◽  
Vol 5 (2) ◽  
pp. 139-147
Author(s):  
Gbenga Femi Asere ◽  
Dung Emmanuel Botson
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information System ◽  
Strategic Management ◽  
Information Management ◽  
Management System ◽  
Clinical Decision Making ◽  
Information Management System ◽  
Decision Making Process ◽  
Mining Technology

Wide spread use of information system in the delivery of managed healthcare system and the challenges of identifying and disseminating relevant healthcare information, complex and diverse data and knowledge forms and tasks coupled with the prevalence of legacy systems require automated approaches for effective and efficient utilization of massive amount of data to support in strategic planning and decision-making and assist the strategic management mechanisms. Despite the fact that data mining is progressively used in information systems as a technology to support analytical decision making, it is however still barely used in hospital information system to support analytical decision making process. Hence, this paper presents the usefulness of data mining technology in Hospital Information Management System (HIMS). Data mining technology offered capabilities to increase the productivity of medical personnel, analyze care outcomes, lower healthcare costs, improve healthcare quality by using fast and better clinical decision making and generally assist the strategic management mechanisms.

Study on Data Mining with Decision Tree Algorithm in the Student Information Management System

2014 ◽  
Vol 543-547 ◽  
pp. 3602-3605
Author(s):  
Liang Li ◽  
Ying Zheng ◽  
Xiao Hua Sun ◽  
Fu Shun Wang
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Information Management ◽  
Management System ◽  
Information Management System ◽  
Decision Tree Algorithm ◽  
Mining Technology ◽  
Tree Algorithm ◽  
Student Information ◽  
Decision Tree Method

With the advance of education informationization in china, information technology and data mining technology has been widely used in the field of education. The decision tree method is one of the data mining methods; it does not require any assumption, can intelligent classification to a large amount of data directly. According to certain rules to find hidden and valuable information.Use the idea of learners as the center as guiding principle, using decision tree algorithm of data mining technology to build student information management system, selects typical C4.5 algorithm among the decision tree methods, Take mass information about employment of graduation in university students' information management system as an example to generate the decision tree, collect potential rules and factors in favor of graduat employment, so as to guide the education and management.

scholarly journals Construction of Student Information Management System Based on Data Mining and Clustering Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
XueHong Yin
Keyword(s):  
Data Mining ◽  
Genetic Algorithm ◽  
Information Management ◽  
Management System ◽  
Clustering Algorithm ◽  
Student Evaluation ◽  
Information Management System ◽  
Fuzzy Genetic Algorithm ◽  
Student Information ◽  
Fuzzy Genetic

Data mining is a new technology developed in recent years. Through data mining, people can discover the valuable and potential knowledge hidden behind the data and provide strong support for scientifically making various business decisions. This paper applies data mining technology to the college student information management system, mines student evaluation information data, uses data mining technology to design student evaluation information modules, and digs out the factors that affect student development and the various relationships between these factors. Predictive assessment of knowledge and personalized teaching decision-making provide the basis. First, the general situation of genetic algorithm and fuzzy genetic algorithm is introduced, and then, an improved genetic fuzzy clustering algorithm is proposed. Compared with traditional clustering algorithm and improved genetic fuzzy clustering algorithm, the effectiveness of the algorithm proposed in this paper is proved. Based on the analysis system development related tools and methods, in response to the needs of the student information management system, a simple student information management system is designed and implemented, which provides a platform and data source for the next application of clustering algorithm for performance analysis. Finally, clustering the students’ scores with a clustering algorithm based on fuzzy genetic algorithm, the experimental results show that this method can better analyze the students’ scores and help relevant teachers and departments make decisions.

scholarly journals Optimization of Clinical Nursing Management System Based on Data Mining

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yongxia Chen
Keyword(s):  
Data Mining ◽  
Information System ◽  
Information Management ◽  
Management System ◽  
Clinical Care ◽  
Nursing Management ◽  
Mining Technology ◽  
Clinical Nursing ◽  
Medical Order ◽  
Nursing Information System

The clinical nursing work based on the establishment and improvement of the clinical nursing system breaks through the traditional nursing work model, which has achieved the advantages of full traceability, practical operation, comprehensive analysis, and individual error correction of nursing work, and greatly improves the nursing quality and work efficiency of nurses. With the advent of the era of big data, how to organically combine data mining technology with nursing information to optimize the nursing information system, apply big data to clinical nursing work through nursing information system, and provide patients with more efficient, high-quality, and safe nursing services is a problem that needs urgent consideration in today’s era. Therefore, this research is based on the framework of the hospital’s existing clinical care system, using data mining technology to improve the Bayesian algorithm and data preprocessing, optimizes the design of functional modules in the clinical nursing management system, and optimizes the patient information management, medical order management, medical order execution management, basic information and expense management, nursing execution process management, system and data management, barcode management, physical sign management, WAP information management, and other subsystems in the clinical nursing information management system. Experiments have proved that the use of a data mining-based clinical care management system can simplify user operations and improve users’ application of software. The application system of nursing methods based on data mining technology more completely integrates nursing information management business, makes nursing information management initially “digital,” and can improve the quality of hospital care to a large extent.

Design for the Large Sport Stadium Information Management System

2014 ◽  
Vol 543-547 ◽  
pp. 4518-4522
Author(s):  
Jing Bai ◽  
Gang Guo ◽  
Li Chen
Keyword(s):  
Information Management ◽  
Management System ◽  
System Development ◽  
Information Management System ◽  
Main Function ◽  
Detailed Design ◽  
Frame Design ◽  
Loosely Coupled ◽  
Framework Design ◽  
Middleware Technology

In this paper, the framework and subsystem detailed design of LSSIMS (Large Sport Stadium Information Management System) is proposed on the basis of main function-demand analysis. After the main function demand is analyzed under 6 iterative stages, the overall framework design of the system is proposed on the basis of the principles of frame design. Then the LSSIMS is divided into the subsystems including the gateway websites, ticketing business subsystem, fitness management subsystem, online interactive subsystems, commercial operation subsystem and advertisement management subsystem. Finally the subsystems are designed individually by adopting the middleware technology and the thought of multi-level, loosely coupled and open design. Through the later stages of detailed design and full system development, it is showed that based on the framework design the LSSIMS provides managers with detailed statistical analysis, decision support and standardization interfaces, which can make good social benefits.

Sign in / Sign up

Export Citation Format

Share Document