Overview
- Presents new models and algorithms for knowledge discovery
- Provides readers with new tools for developing practical algorithms for solving problems in data analysis
- Addresses difficult questions in data analysis for either well-known tools or recently developed advanced tools
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 202)
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Table of contents (24 chapters)
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Front Matter
Keywords
About this book
This book presents the state-of-the-art in the emerging field of data science and includes models for layered security with applications in the protection of sites—such as large gathering places—through high-stake decision-making tasks. Such tasks include cancer diagnostics, self-driving cars, and others where wrong decisions can possibly have catastrophic consequences. Additionally, this book provides readers with automated methods to analyze patterns and models for various types of data, with applications ranging from scientific discovery to business intelligence and analytics.
The book primarily includes exploratory data analysis, pattern mining, clustering, and classification supported by real life case studies. The statistical section of this book explores the impact of data mining and modeling on the predictability assessment of time series. Further new notions of mean values based on ideas of multi-criteria optimization are compared with their conventional definitions, leading to new algorithmic approaches to the calculation of the suggested new means.The style of the written chapters and the provision of a broad yet in-depth overview of data mining, integrating novel concepts from machine learning and statistics, make the book accessible to upper level undergraduate and graduate students in data mining courses. Students and professionals specializing in computer and management science, data mining for high-dimensional data, complex graphs and networks will benefit from the cutting-edge ideas and practically motivated case studies in this book.
Editors and Affiliations
About the editors
Professor Sergei O. Kuznetsov graduated from the Faculty of Applied Mathematics and Control of the Moscow Institute for Physics and Technology in 1985. He obtained his Doctor of Science Degree in Theoretical Computer Science at the Computing Center of Russian Academy of Science. Since 2006 the Head of Department for Data Analysis and Artificial Intelligence, Head of the International Laboratory for Intelligent Systems and Structural Analysis and Academic Supervisor of the Data Science master program at National Research University Higher School of Economics (Moscow). His researchinterests are in the algorithms of data mining, knowledge discovery, and Formal Concept Analysis.
Bibliographic Information
Book Title: Data Analysis and Optimization
Book Subtitle: In Honor of Boris Mirkin's 80th Birthday
Editors: Boris Goldengorin, Sergei Kuznetsov
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-3-031-31654-8
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-31653-1Published: 24 September 2023
Softcover ISBN: 978-3-031-31656-2Due: 30 October 2023
eBook ISBN: 978-3-031-31654-8Published: 23 September 2023
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 1
Number of Pages: XXXV, 422
Number of Illustrations: 1 b/w illustrations
Topics: Data Mining and Knowledge Discovery, Operations Research, Management Science, Discrete Mathematics, Artificial Intelligence