"Data Mining: Concepts and Applictions" ed. by Ciza Thomas, Andries Engelbrecht

This book presents basic concepts, ideas, and research in data mining.

The availability of big data due to computerization and automation has generated an urgent need for new techniques to analyze and convert big data into useful information and knowledge. Data mining is a promising and leading-edge technology for mining large volumes of data, looking for hidden information, and aiding knowledge discovery. It can be used for characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, and much more in fields such as science, medicine, economics, engineering, computers, and even business analytics.

Contents
1. The Concept of Data Mining
2. Use Data Mining Cleansing to Prepare Data for Strategic Decisions
3. Privacy Preserving Data Mining
4. Multilabel Classification Based on Graph Neural Networks
5. DMAPT: Study of Data Mining and Machine Learning Techniques in Advanced Persistent Threat Attribution and Detection
6. Text Classification on the Instagram Caption Using Support Vector Machine
7. Computing on Vertices in Data Mining
8. Artificial Intelligence and Its Application in Optimization under Uncertainty
9. Practical Application Using the Clustering Algorithm
10. Leaching Mechanisms of Trace Elements from Coal and Host Rock Using Method of Data Mining
11. Tourist Sentiment Mining Based on Deep Learning
12. Data Mining Applied for Community Satisfaction Prediction of Rehabilitation and Reconstruction Project (Learn from Palu Disasters)


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