"Advances in Data Mining Knowledge Discovery and Applications" ed. by Adem Karahoca

This book aims to help data miners, researchers, scholars, and PhD students who wish to apply data mining techniques. The primary contribution of this book is highlighting frontier fields and implementations of the knowledge discovery and data mining.

This book presents knowledge discovery and data mining applications.

Contents
Preface
Section 1 Knowledge Discovery
1 Towards the Formulation of a Unified Data Mining Theory, Implemented by Means of Multiagent Systems (MASs)
2 Selecting Representative Data Sets
3 Similarity Measures and Dimensionality Reduction Techniques for Time Series Data Mining
4 Data Mining and Neural Networks: The Impact of Data Representation
5 Inconsistent Decision System: Rough Set Data Mining Strategy to Extract Decision Algorithm of a Numerical Distance Relay - Tutorial
6 An Unsupervised Classification Method for Hyperspectral Remote Sensing Image Based on Spectral Data Mining
7 Visualization Techniques: Which is the Most Appropriate in the Process of Knowledge Discovery in Data Base?
8 Analysis and Learning Frameworks for Large-Scale Data Mining
Section 2 Data Mining Applications
9 Data Mining Applied to Cognitive Radio Systems
10 Short-Term Energy Price Prediction Multi-Step-Ahead in the Brazilian Market Using Data Mining
11 Electricity Load Forecasting Using Data Minina Technique
12 Mining and Adaptivity in Automated Teller Machines
13 Data Mining for Motorsport Aerodynamics
14 The Performance Evaluation of Speech Recognition by Comparative Approach
15 Data Mining from Remote Sensing Snow and Vegetation Product
16 Mining Complex Network Data for Adaptive Intrusion Detection
17 BotNet Detection: Enhancing Analysis by Using Data Mining Techniques
18 Improving Decision Support Systems with Data Mining Techniques