Advances in Big Data Analytics

Yong Shi is the Director of the Research Center on Fictitious Economy and Data Science, and Director of the Key Lab of Big Data Mining and Knowledge Management, Chinese Academy of Sciences. He has been an Isaacson Professor, Union Pacific Chair, and Charles W. and Margre H. Durham Distinguished Professor of Information Technology at the College of Information Science and Technology, University of Nebraska at Omaha, USA. He has served on the State Council of the PRC (2016), as an elected member of the International Eurasian Academy of Science (2017), and as an elected fellow of the World Academy of Sciences for the Advancement of Science in Developing Countries (2015). His research interests include big data analysis, data science, business intelligence, data mining and multiple-criteria decision making. He has published more than 20 books, over 500 papers in various journals, and numerous conferences/proceedings papers. He is the Editor-in-Chief of both the International Journal ofInformation Technology and Decision Making (SCI) and of Annals of Data Science (Springer), and serves on the Editorial Boards of numerous academic journals.

• Part One: Concept and Theoretical Foundation.- Chapter 1: Big Data and Big Data Analytics.- Chapter 2: Multiple Criteria Optimization Classification.- Chapter 3: Support Vector Machine Classification.- Part Two: Functional Analysis.- Chapter 4: Feature Selection.- Chapter 5: Data Stream Analysis.- Chapter 6: Learning Analysis.- Chapter 7: Sentiment Analysis.- Chapter 8: Link Analysis.- Chapter 9: Evaluation Analysis.- Part Three: Application and Future Analysis.- Chapter 10: Business and Engineering Applications.- Chapter 11: Healthcare Applications.- Chapter 12: Artificial Intelligence IQ Test.- Chapter 13: Conclusions.