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Computer and Information Science » Computer Science and Engineering
Data Mining and Knowledge Discovery in Real Life Applications
Edited by Julio Ponce and Adem Karahoca, ISBN 978-3-902613-53-0, Hard cover, 436 pages, Publisher: I-Tech Education and Publishing, Chapters published January 01, 2009 under CC BY-NC-SA 3.0 license
DOI: 10.5772/97 
This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social. Twenty six chapters cover different special topics with proposed novel ideas. Each chapter gives an overview of the subjects and some of the chapters have cases with offered data mining solutions. We hope that this book will be a useful aid in showing a right way for the students, researchers and practitioners in their studies.
- Chapter 1
A Data Mining & Knowledge Discovery Process Model - Chapter 2 Knowledge Discovery on the Grid
- Chapter 3 Rough Set Theory — Fundamental Concepts, Principals, Data Extraction, and Applications
- Chapter 4 Robust Data Mining: An Integrated Approach
- Chapter 5 On the Selection of Meaningful Association Rules
- Chapter 6 Hybrid Clustering for Validation and Improvement of Subject-Classification Schemes
- Chapter 7 Automatic Product Classification Control System Using RFID Tag Information and Data Mining
- Chapter 8 Hyperspectral Remote Sensing Data Mining Using Multiple Classifiers Combination
- Chapter 9 Content-based Image Classification via Visual Learning
- Chapter 10 Clustering Parallel Data Streams
- Chapter 11 Mining Multiple-level Association Rules Based on Pre-large Concepts
- Chapter 12 Data Mining Applications: Promise and Challenges
- Chapter 13 Mining Spatio-Temporal Datasets: Relevance, Challenges and Current Research Directions
- Chapter 14 Benchmarking the Data Mining Algorithms with Adaptive Neuro-Fuzzy Inference System in GSM Churn Management
- Chapter 15 Using Data Mining to Investigate the Behavior of Video Rental Customers
- Chapter 16 A Novel Model for Global Customer Retention Using Data Mining Technology
- Chapter 17 Data Mining in Web Applications
- Chapter 18 Application of Data Mining Techniques to the Data Analyses to Ensure Safety of Medicine Usage
- Chapter 19 Data Mining in the Molecular Biology Era — A Study Directed to Carbohydrates Biosynthesis and Accumulation in Plants
- Chapter 20 Microarray Data Mining for Biological Pathway Analysis
- Chapter 21 Development of Microsatellite Markers by Data Mining from DNA Sequences
- Chapter 22 Quality Improvement using Data Mining in Manufacturing Processes
- Chapter 23 The Deployment of Data Mining into Operational Business Processes
- Chapter 24 Data Mining Applied to the Instrumentation Data Analysis of a Large Dam
- Chapter 25 A Data Mining Algorithm for Monitoring PCB Assembly Quality
- Chapter 26 An Overview of Data Mining Techniques Applied to Power Systems