Editors:
- Presents a wide range of selected inspiring and interesting state-of-the-art contributions on Data Science
- Includes sixteen successful examples of recent advances in the rapidly evolving field of Data Science
- Focuses on theory and applications in language technologies, optimization, computational thinking, intelligent decision support systems, decomposition of signals, model-driven development methodologies, interoperability of enterprise applications, anomaly detection in financial markets, 3D virtual reality, monitoring of environmental data, convolutional neural networks, and more
Part of the book series: Studies in Computational Intelligence (SCI, volume 869)
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Table of contents (16 chapters)
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Front Matter
About this book
Modern technologies allow us to store and transfer large amounts of data quickly. They can be very diverse - images, numbers, streaming, related to human behavior and physiological parameters, etc. Whether the data is just raw numbers, crude images, or will help solve current problems and predict future developments, depends on whether we can effectively process and analyze it. Data science is evolving rapidly. However, it is still a very young field.
In particular, data science is concerned with visualizations, statistics, pattern recognition, neurocomputing, image analysis, machine learning, artificial intelligence, databases and data processing, data mining, big data analytics, and knowledge discovery in databases. It also has many interfaces with optimization, block chaining, cyber-social and cyber-physical systems, Internet of Things (IoT), social computing, high-performance computing, in-memory key-value stores, cloud computing, social computing, data feeds, overlay networks, cognitive computing, crowdsource analysis, log analysis, container-based virtualization, and lifetime value modeling. Again, all of these areas are highly interrelated. In addition, data science is now expanding to new fields of application: chemical engineering, biotechnology, building energymanagement, materials microscopy, geographic research, learning analytics, radiology, metal design, ecosystem homeostasis investigation, and many others.
Editors and Affiliations
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Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania
Gintautas Dzemyda, Jolita Bernatavičienė
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Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland
Janusz Kacprzyk
Bibliographic Information
Book Title: Data Science: New Issues, Challenges and Applications
Editors: Gintautas Dzemyda, Jolita Bernatavičienė, Janusz Kacprzyk
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-39250-5
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-39249-9Published: 14 February 2020
Softcover ISBN: 978-3-030-39252-9Published: 14 February 2021
eBook ISBN: 978-3-030-39250-5Published: 13 February 2020
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVIII, 313
Number of Illustrations: 67 b/w illustrations, 59 illustrations in colour