Data Mining and Knowledge Discovery in Real Life Applications
eBook - PDF

Data Mining and Knowledge Discovery in Real Life Applications

  1. 402 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Data Mining and Knowledge Discovery in Real Life Applications

About this book

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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Yes, you can access Data Mining and Knowledge Discovery in Real Life Applications by Julio Ponce,Adem Karahoca, Julio Ponce , Adem Karahoca in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

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