Advances in Data Mining Knowledge Discovery and Applications

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InTeOp – 2012, 429 pages
ISBN: 9535107484, 9789535107484
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
Towards the Formulation of a Unified Data Mining Theory, Implemented by Means of Multiagent Systems (MASs)
Selecting Representative Data Sets
Similarity Measures and Dimensionality Reduction Techniques for Time Series Data Mining
Data Mining and Neural Networks: The Impact of Data Representation
Inconsistent Decision System: Rough Set Data Mining Strategy to Extract Decision Algorithm of a Numerical Distance Relay - Tutorial
An Unsupervised Classification Method for Hyperspectral Remote Sensing Image Based on Spectral Data Mining
Visualization Techniques: Which is the Most Appropriate in the Process of Knowledge Discovery in Data Base?
Analysis and Learning Frameworks for Large-Scale Data Mining
Section 2 Data Mining Applications
Data Mining Applied to Cognitive Radio Systems
Short-Term Energy Price Prediction Multi-Step-Ahead in the Brazilian Market Using Data Mining
Electricity Load Forecasting Using Data Minina Technique
Mining and Adaptivity in Automated Teller Machines
Data Mining for Motorsport Aerodynamics
The Performance Evaluation of Speech Recognition by Comparative Approach
Data Mining from Remote Sensing Snow and Vegetation Product
Mining Complex Network Data for Adaptive Intrusion Detection
BotNet Detection: Enhancing Analysis by Using Data Mining Techniques
Improving Decision Support Systems with Data Mining Techniques

Author(s): Karahoca A. (Ed.)

Language: English
Commentary: 962399
Tags: Информатика и вычислительная техника;Искусственный интеллект;Интеллектуальный анализ данных