Springer, 2022. — 723 p. — ISBN: 978-981-16-3606-6.
Today, big data affects countless aspects of our daily lives. This book provides a comprehensive and cutting-edge study on big data analytics, based on the research findings and applications developed by the author and his colleagues in related areas. It addresses the concepts of big data analytics and/or data science, multi-criteria optimization for learning, expert and rule-based data analysis, support vector machines for classification, feature selection, data stream analysis, learning analysis, sentiment analysis, link analysis, and evaluation analysis. The book also explores lessons learned in applying big data to business, engineering, and healthcare. Lastly, it addresses the advanced topic of intelligence-quotient (IQ) tests for artificial intelligence.
Concept and Theoretical FoundationBig Data and Big Data Analytics
Multiple Criteria Optimization Classification
Support Vector Machine Classification
Functional AnalysisFeature Selection
Data Stream Analysis
Learning Analysis
Sentiment Analysis
Link Analysis
Evaluation Analysis
Application and Future AnalysisBusiness and Engineering Applications
Healthcare Applications
Artificial Intelligence IQ Test