Cognitive Big Data Intelligence with a Metaheuristic Approach presents an exact and compact organization of content relating to the latest metaheuristics methodologies based on new challenging big data application domains and cognitive computing. The combined model of cognitive big data intelligence with metaheuristics methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues in real-time. Various real-time case studies and implemented works are discussed in this book for better understanding and additional clarity.

A. Foundations and Architectural Models of Cognitive Big Data and Meta heuristics 1. Cognitive Computing fundamentals like perception, memory, reasoning, emotion, and problem solving 2. Cognitive Computing techniques using artificial intelligence, pattern and speech recognition, and natural language processing 3. Cognitive approaches within data mining and machine learning techniques 4. Big Data Infrastructure for Cognition and Distributed Data Centers for Cognition 5. Meta heuristics in classification, clustering and frequent pattern mining problems 6. Nature-inspired computing and Optimization algorithms 7. Meta heuristics and swarm intelligence approach 8. Use of Computational intelligence and Intelligent computing approaches in engineering domains 9. Big Data, Clouds and Internet of Things (IoT) 10. Dimensionality reduction models with Meta heuristics 11. Neuro-evolutionary and fuzzy models in big data and cognitive analytics 12. Innovative methods for cognitive business big data analytics 13. Cognitive techniques for mining unstructured, spatial-temporal, streaming and multimedia data 14. Data-driven large scale optimization architectures 15. Ensemble learning with Meta heuristics optimization