Big Data Mining and Complexity
Brian C. Castellani · Rajeev Rajaram
mar 2022 · SAGE
Libro electrónico
180
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Acerca de este libro electrónico
This book offers a much needed critical introduction to data mining and ‘big data’. Supported by multiple case studies and examples, the authors provide:
- Digestible overviews of key terms and concepts relevant to using social media data in quantitative research.
- A critical review of data mining and ‘big data’ from a complexity science perspective, including its future potential and limitations
- A practical exploration of the challenges of putting together and managing a ‘big data’ database
- An evaluation of the core mathematical and conceptual frameworks, grounded in a case-based computational modeling perspective, which form the foundations of all data mining techniques
Acerca del autor
Rajeev Rajaram is a Professor of Mathematics at Kent State University. Rajeev’s primary training is in control theory of partial differential equations and he is currently interested in applications of differential equations and ideas from statistical mechanics and thermodynamics to model and measure complexity. He and Brian Castellani have worked together to create a new case - based method for modeling complex systems, called the SACS Toolkit, which has been used to study topics in health, health care, societal infrastructures, power - grid reliability, restaurant mobility, and depression trajectories. More recently, he is interested in mathematical properties of entropy based diversity measures for probability distributions.
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