An overview on Data Mining - Semantic Scholar.
Data mining, in contrast, is data driven in the sense that patterns are automatically ex-tracted from data. The goal of this tutorial is to provide an introduction to data mining techniques. The.
A lot of data mining research focused on tweaking existing techniques to get small percentage gains The Data Mining Process Generally, data mining process is composed by data preparation, data mining, and information expression and analysis decision-making phases, the specific process as shown in fig.1(5). Fig.3: General process of Data Mining. ISSN 2249-6343 International Journal of.
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Performance Analysis and Prediction in Educational Data Mining: A Research Travelogue Pooja Thakar Assistant Professor VIPS, GGSIPU Delhi, India Anil Mehta, Ph.D Professor University of Rajasthan Jaipur, India Manisha, Ph.D Associate Professor Banasthali University Jaipur, India ABSTRACT In this era of computerization, education has also revamped.
Data Mining - Techniques, Methods and Algorithms: A Review on Tools and their Validity Mansi Gera Computer Science and Engineering Department, Thapar University, Patiala, Punjab, India-147001 Shivani Goel Computer Science and Engineering Department Thapar University, Patiala, Punjab, India-147001 ABSTRACT Data mining is the process of extracting the useful data, patterns and trends from a.
DATA MINING TECHNIQUES AND APPLICATIONS Mrs. Bharati M. Ramageri, Lecturer Modern Institute of Information Technology and Research, Department of Computer Application, Yamunanagar, Nigdi Pune, Maharashtra, India-411044. Abstract Data mining is a process which finds useful patterns from large amount of data. The paper discusses few of the data mining techniques, algorithms and some of the.
International Journal of Data Mining Techniques and Applications (IJDMTA) is a peer-reviewed bi-annual journal that publishes high-quality papers on all aspects of IJDMTA. The primary objective of IJDMTA is to be an authoritative International forum for delivering both theoretical and innovative applied researches in the data mining concepts, to implementations.
A Survey of Data Mining Techniques for Social Media Analysis Mariam Adedoyin-Olowe 1, Mohamed Medhat Gaber 1 and Frederic Stahl 2 1School of Computing Science and Digital Media, Robert Gordon University Aberdeen, AB10 7QB, UK 2School of Systems Engineering, University of Reading PO Box 225, Whiteknights, Reading, RG6 6AY, UK.
Survey of Clustering Data Mining Techniques Pavel Berkhin Accrue Software, Inc. Clustering is a division of data into groups of similar objects. Representing the data by fewer clusters necessarily loses certain fine details, but achieves simplification. It models data by its clusters. Data modeling puts clustering in a.
Applying machine learning and data mining methods in DM research is a key approach to utilizing large volumes of available diabetes-related data for extracting knowledge. The severe social impact of the specific disease renders DM one of the main priorities in medical science research, which inevitably generates huge amounts of data.
Informing data mining research with educational theory. Developing new techniques for mining educational data. Data mining to understand how learners interact in formal and informal educational contexts. Modeling students’ affective states and engagement with multimodal data. Synthesizing rich data to inform students and educators.
As a part of this research work more than 25 papers has been explored and thoroughly studied. Few papers related to Data Mining in Education: Data Classification and Decision Tree Approach Sonali Agarwal, G. N. Pandey, and M. D. Tiwari 140 International Journal of e-Education, e-Business, e-Management and e-Learning, Vol. 2, No. 2, April 2012.
The purpose of this research is to present a sample study analyzing data gathered from an educational study using data mining techniques appropriate for processing these data. In order to achieve this aim, a “Computer Self-efficiency Scale” used in educational sciences was selected and this scale was applied in a study group. Data was analyzed using descriptive statistics (ttest and.
