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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, Published: January 01, 2009 under CC BY-NC-SA 3.0 license, in subject Information and Knowledge Engineering
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.
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Book contents
- Chapter 1A Data Mining & Knowledge Discovery Process Model
- Chapter 2Knowledge Discovery on the Grid
- Chapter 3Rough Set Theory Fundamental Concepts, Principals, Data Extraction, and Applications
- Chapter 4Robust Data Mining: An Integrated Approach
- Chapter 5On the Selection of Meaningful Association Rules
- Chapter 6Hybrid Clustering for Validation and Improvement of Subject-Classification Schemes
- Chapter 7Automatic Product Classification Control System Using RFID Tag Information and Data Mining
- Chapter 8Hyperspectral Remote Sensing Data Mining Using Multiple Classifiers Combination
- Chapter 9Content-based Image Classification via Visual Learning
- Chapter 10Clustering Parallel Data Streams
- Chapter 11Mining Multiple-level Association Rules Based on Pre-large Concepts
- Chapter 12Data Mining Applications: Promise and Challenges
- Chapter 13Mining Spatio-Temporal Datasets: Relevance, Challenges and Current Research Directions
- Chapter 14Benchmarking the Data Mining Algorithms with Adaptive Neuro-Fuzzy Inference System in GSM Churn Management
- Chapter 15Using Data Mining to Investigate the Behavior of Video Rental Customers
- Chapter 16A Novel Model for Global Customer Retention Using Data Mining Technology
- Chapter 17Data Mining in Web Applications
- Chapter 18Application of Data Mining Techniques to the Data Analyses to Ensure Safety of Medicine Usage
- Chapter 19Data Mining in the Molecular Biology Era A Study Directed to Carbohydrates Biosynthesis and Accumulation in Plants
- Chapter 20Microarray Data Mining for Biological Pathway Analysis
- Chapter 21Development of Microsatellite Markers by Data Mining from DNA Sequences
- Chapter 22Quality Improvement using Data Mining in Manufacturing Processes
- Chapter 23The Deployment of Data Mining into Operational Business Processes
- Chapter 24Data Mining Applied to the Instrumentation Data Analysis of a Large Dam
- Chapter 25A Data Mining Algorithm for Monitoring PCB Assembly Quality
- Chapter 26An Overview of Data Mining Techniques Applied to Power Systems
