scholarly journals A Review on Prediction of Multiple Diseases and Performance Analysis using Data Mining and Visualization Techniques

2016 ◽  
Vol 155 (1) ◽  
pp. 34-38
Author(s):  
Ajinkya Kunjir ◽  
Harshal Sawant ◽  
Nuzhat F.
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
And Performance ◽  
Using Data ◽  
Visualization Techniques

scholarly journals Using Data Mining for Improving Education of University Students – A Survey

2018 ◽  
Vol 6 (9) ◽  
pp. 78-83 ◽  
Author(s):  
K. P. S. D. Kumarapathirana
Keyword(s):  
Data Mining ◽  
Academic Success ◽  
Student Retention ◽  
Student Performance ◽  
Poor Performance ◽  
Academic Behavior ◽  
System Logs ◽  
Using Data ◽  
Visualization Techniques ◽  
The University

Data mining combines machine learning, statistical and visualization techniques to discover and extract knowledge. Student retention is an indicator of academic performance and enrolment management of the university. Poor student retention could reflect badly on the university. Universities are facing the immense and quick growth of the volume of educational data stored in different types of databases and system logs. Moreover, the academic success of students is another major issue for the management in all professional institutes. So the early prediction to improve the student performance through counseling and extra coaching will help the management to take timely action for decrease the percentage of poor performance by the students. Data mining can be used to find relationships and patterns that exist but are hidden among the vast amount of educational data. This survey conducts a literature survey to identify data mining technologies to monitor student, analyze student academic behavior and provide a basis for efficient intervention strategies. The results can be used to develop a decision support system and help the authorities to timely actions on weak students.

scholarly journals Performance Analysis and Prediction Student Performance to build effective student Using Data Mining Techniques

2019 ◽  
Vol 3 (2) ◽  
pp. 10
Author(s):  
Ardalan Husin Awlla
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Student Performance ◽  
Fraud Detection ◽  
Classification Model ◽  
Data Mining Techniques ◽  
Incipient Stage ◽  
The Everyday ◽  
Using Data

In this period of computerization, schooling has additionally remodeled itself and is not restrained to old lecture technique. The everyday quest is on to discover better approaches to make it more successful and productive for students. These days, masses of data are gathered in educational databases, however it stays unutilized. To be able to get required advantages from such major information, effective tools are required. Data mining is a developing capable tool for examination and expectation. It is effectively applied in the field of fraud detection, marketing, promoting, forecast and loan assessment. However, it is in incipient stage in the area of education. In this paper, data mining techniques have been applied to construct a classification model to predict the performance of students.

A Survey on Building Recommendation Systems Using Data Mining Techniques

2022 ◽  
pp. 24-56
Author(s):  
Rajab Ssemwogerere ◽  
Wamwoyo Faruk ◽  
Nambobi Mutwalibi
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Recommender Systems ◽  
Performance Measures ◽  
Data Mining Technique ◽  
Data Mining Techniques ◽  
Learning Hypothesis ◽  
Depth Study ◽  
And Performance ◽  
Using Data

Classification is a data mining technique or approach used to estimate the grouped membership of items on a basis of a common feature. This technique is virtuous for future planning and discovering new knowledge about a specific dataset. An in-depth study of previous pieces of literature implementing data mining techniques in the design of recommender systems was performed. This chapter provides a broad study of the way of designing recommender systems using various data mining classification techniques of machine learning and also exploiting their methodological decisions in four aspects, the recommendation approaches, data mining techniques, recommendation types, and performance measures. This study focused on some selected classification methods and can be so supportive for both the researchers and the students in the field of computer science and machine learning in strengthening their knowledge about the machine learning hypothesis and data mining.

Data mining artificial intelligence technology for college english test framework and performance analysis system

2020 ◽  
pp. 1-11
Author(s):  
Lin Shen
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Evaluation Model ◽  
Diagnostic Evaluation ◽  
Test Paper ◽  
Test Question ◽  
College English ◽  
Question Recommendation ◽  
And Performance ◽  
Analysis System

This article first studies and designs the college English test framework and performance analysis system. The author analyzes a large number of data collected by the system in three dimensions: using data mining title association models, using machine learning to merge college English score prediction models, and finally diagnosing on the basis of the sexual evaluation model, the author designed and implemented a test paper algorithm based on the association rules of the question type, and carried out relevant verification from the three aspects of test paper time, test question recommendation and improvement according to scores. Finally, according to the needs analysis, the author uses the diagnostic evaluation model and related test paper algorithm to design and implement the diagnostic evaluation model, which is added to the college English diagnostic practice system. It can be obtained through comparative experiments that the paper-based algorithm based on the diagnostic evaluation model proposed in this paper can effectively give better practice guidance and test question recommendation to the learner’s learning status and knowledge point problem obstacles, and can effectively improve learning. The achievements of the authors have broad application prospects and research value.

New Similarity Measures between Vague Sets and Performance Analysis

2013 ◽  
Vol 811 ◽  
pp. 547-551 ◽  
Author(s):  
Hong Xu Wang ◽  
Hai Feng Wang ◽  
Kun Zhang ◽  
Hui Wang
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Similarity Measure ◽  
Similarity Measures ◽  
Practical Case ◽  
Vague Sets ◽  
Diagnosis Method ◽  
And Performance ◽  
Definition Of ◽  
New Formula

In order to amend the defects of existing similarity measure formula between vague sets, a new definition of similarity measure between vague sets is proposed and a new formula with higher resolution and highlighted uncertainty is presented on the basis of data mining vague value method. A general fault diagnosis method of Vague sets (GFDMVS) is proposed. The same practical case is studied with three methods and the results demonstrate the validity and reasonability of the method proposed in this paper.

scholarly journals A SURVEY ON RURAL SCHOOL STUDENTS EDUCATION PERFORMANCE USING DATA MINING TECHNIQUES

2021 ◽  
pp. 209-212
Author(s):  
Suresh Solomon. G ◽  
Nancy Jasmine Goldina
Keyword(s):  
Data Mining ◽  
Rural Areas ◽  
Urban Areas ◽  
Research Study ◽  
Rural School ◽  
Vital Role ◽  
School Students ◽  
And Performance ◽  
Using Data ◽  
Education Performance

In India there exists a lot of Rural areas in which the educational performance of the rural school students are inferior when compared it to the performance of the urban areas due to the lack of facilities, environment, income, employment opportunities and exposure. Equality is one among the basic principle of our country, so it’s a mere responsibility of any research study to perform a detailed analysis towards the performance of rural school students by focusing on to the factors to be monitored and improved so that the Rural areas also raise to the equilant level of competition with the Urban areas. For this goal Data mining plays a vital role in order to handle the data in proper way for analysis and prediction of performances for the improvement of rural school student’s education domain results. This paper presents a survey on Data Mining strategies used for prediction and performance analysis of rural school students education improvements. KEYWORDS—Data Mining, Rural, Urban, Prediction, Performance

scholarly journals A review on performance analysis of data mining methods in IoT

2020 ◽  
Vol 7 (73) ◽  
pp. 193-200
Author(s):  
Ashutosh Kumar Dubey ◽  
Dimple Kapoor ◽  
Vijaita Kashyap
Keyword(s):  
Systematic Review ◽  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Performance Analysis ◽  
System Component ◽  
Different Types ◽  
Communication Capability ◽  
Mining Methods ◽  
And Performance

IoT is capable and helpful in interdisciplinary areas along with the convergence of multiple technologies and platforms. This study adheres the adaptation of data mining technologies along with big data and cloud computing with the IoT system with detailed discussion. This paper supports and provide systematic review and analysis based on the computational parameters and performance analysis. The analysis and discussion are based on the communication capability, system component communication, aspects of data mining, big data and cloud computing in IoT. Different types of transmission and communication barriers have also been discussed and analyze. Finally, based on the study and analysis a framework has been suggested for the smooth functioning of the IoT protocols.

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