Advances in Big Data Analytics
Springer Verlag, Singapore
978-981-16-3609-7 (ISBN)
Since each aspect mentioned above concerns a specific domain of application, taken together, the algorithms, procedures, analysis and empirical studies presented here offer a general picture of big data developments. Accordingly, the book can not only serve as a textbook for graduates with a fundamental grasp of training in big data analytics, but can also show practitioners how to use the proposed techniques to deal with real-world big data problems.
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.
| Erscheinungsdatum | 18.01.2023 |
|---|---|
| Zusatzinfo | 1 Illustrations, black and white; XIV, 728 p. 1 illus. |
| Verlagsort | Singapore |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Theorie / Studium ► Algorithmen | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Big data analysis • COVID-19 and Social Media • Data Science • Data streams • Evaluation Analysis • Feature Selection • IQ test for Artificial Intelligence and Applications • learning analysis • Link Analysis • Multi-Criteria Optimization • sentiment analysis • Support Vector Machine |
| ISBN-10 | 981-16-3609-5 / 9811636095 |
| ISBN-13 | 978-981-16-3609-7 / 9789811636097 |
| Zustand | Neuware |
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