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Artificial Intelligence in Data Mining
Theories and Applications
- 1st Edition - February 17, 2021
- Editors: D. Binu, B.R. Rajakumar
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 0 6 0 1 - 0
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 0 6 1 6 - 4
Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-w… Read more
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Request a sales quoteArtificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area.
- Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering
- Presents coverage of key topics such as heuristic methods for data clustering, deep learning methods for data classification, and neural networks
- Includes case studies and real-world applications of AI techniques in data mining, for improved outcomes in clinical diagnosis, satellite data extraction, agriculture, security and defense
Engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area
- Cover image
- Title page
- Table of Contents
- Copyright
- List of contributors
- Preface
- 1. Introduction
- Abstract
- 1.1 Data mining
- 1.2 Description of data mining
- 1.3 Tools in data mining
- 1.4 Data mining terminologies
- 1.5 Merits of data mining
- 1.6 Disadvantages of data mining
- 1.7 Process of data mining
- 1.8 Data mining techniques
- 1.9 Data mining applications
- 1.10 Intelligent techniques of data mining
- 1.11 Expectations of data mining
- References
- 2. Intelligence methods for data mining task
- Abstract
- 2.1 Introduction
- 2.2 Procedure for intelligent data mining
- 2.3 Associate rule mining
- 2.4 Association rule mining: multiobjective optimization method
- 2.5 Intelligent methods for associate rule mining
- 2.6 Associate rule mining using genetic algorithm
- 2.7 Association rule mining using particle swarm optimization
- 2.8 Bees swarm optimization–association rule mining algorithm
- 2.9 Ant colony optimization algorithm
- 2.10 Penguins search optimization algorithm for association rules mining Pe-ARM
- 2.11 Deep learning in data mining
- References
- 3. Unsupervised learning methods for data clustering
- Abstract
- 3.1 Data clustering
- 3.2 Mode seeking and mixture-resolving algorithms
- 3.3 Conclusion
- 4. Heuristic methods for data clustering
- Abstract
- 4.1 What is the heuristic method?
- 4.2 Summary
- 5. Deep learning methods for data classification
- Abstract
- 5.1 Data classification
- 5.2 Data mining
- 5.3 Background and evolution of deep learning
- 5.4 Deep learning methods
- References
- 6. Neural networks for data classification
- Abstract
- 6.1 Neural networks
- 6.2 Different types of neural networks
- 6.3 Training of neural network
- 6.4 Training algorithms in neural network for data classification
- References
- 7. Application of artificial intelligence in the perspective of data mining
- Abstract
- 7.1 Artificial intelligence
- 7.2 Artificial intelligence versus data mining
- 7.3 Modeling theory based on artificial intelligence and data mining
- References
- 8. Biomedical data mining for improved clinical diagnosis
- Abstract
- 8.1 Introduction
- 8.2 Descriptions and features of data mining
- 8.3 Revolution of data mining
- 8.4 Data mining for healthcare
- 8.5 Data mining for biological application
- 8.6 Data mining for disease diagnosis
- 8.7 Data mining of drug discovery
- References
- 9. Satellite data: big data extraction and analysis
- Abstract
- 9.1 Remote-sensing data: properties and analysis
- 9.2 Summary
- References
- 10. Advancement of data mining methods for improvement of agricultural methods and productivity
- Abstract
- 10.1 Agriculture data: properties and analysis
- 10.2 Disease prediction using data mining
- 10.3 Pests monitoring using data mining
- 10.4 Summary
- References
- 11. Advanced data mining for defense and security applications
- Abstract
- 11.1 Military data: properties and analysis
- 11.2 Applying data mining for military application
- References
- Index
- No. of pages: 270
- Language: English
- Edition: 1
- Published: February 17, 2021
- Imprint: Academic Press
- Paperback ISBN: 9780128206010
- eBook ISBN: 9780128206164
DB
D. Binu
D. Binu is a Managing Director and Co-founder of Resbee Info Technologies Pvt. Ltd, India. He is a data scientist who specializes in integrating Artificial Intelligence (AI) technologies into e-learning platforms, utilising his eagerness, experience and passion to invent. He has contributed to developing the AI-based learning management system, named e-khool, which established Resbee Info Technologies Pvt. Ltd. He has contributed in the areas of AI, machine learning and data mining, with sound publications in reputed journals (including, IEEE transaction articles). He has published over 25 publications and filed more than 20 Indian patents.
Affiliations and expertise
Managing Director and Co-Founder, Resbee Info Technologies Pvt. Ltd, IndiaBR
B.R. Rajakumar
B.R. Rajakumar is a Director and Co-Founder of Resbee Info Technologies Pvt. Ltd, India. He is the Lead Researcher of the in-house research unit in Resbee Info Technologies, focusing on deploying Artificial Intelligence (AI) on e-learning platforms. He is also the technical advisor of the AI-based research products, and played a lead role in developing E-Khool, a next generation AI-enabled LMS. He has multidisciplinary expertise, specifically in AI and Soft Computing applications. He is the founder of the Lion Algorithm and published his research outcomes in refereed International Journals. He has filed 20+ Indian patents and holds researcher awards for his contributions.
Affiliations and expertise
Director and Co-Founder, Resbee Info Technologies Pvt. Ltd, IndiaRead Artificial Intelligence in Data Mining on ScienceDirect