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Elsevier Data Fusion Methodology and Applications: Volume 31 (Data Handling in Science and Technology, Volume 31)

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Description

Data Fusion Methodology and Applications explores the data-driven discovery paradigm in science and the need to handle large amounts of diverse data. Drivers of this change include the increased availability and accessibility of hyphenated analytical platforms, imaging techniques, the explosion of omics data, and the development of information technology. As data-driven research deals with an inductive attitude that aims to extract information and build models capable of inferring the underlying phenomena from the data itself, this book explores the challenges and methodologies used to integrate data from multiple sources, analytical platforms, different modalities, and varying timescales. Review Presents a comprehensive vision of methodologies and data analytics challenges, framing the nature of coupled data and enhanced discovery About the Author Marina Cocchi currently serves as the Associate Professor in the University of Modena and Reggio Emilia’s Department of Chemical and Geological Sciences. She has dedicated nearly two decades of chemometric and data analysis research to the university, exploring topics ranging from data fusion procedures to development and application of multivariates. Cocchi has also contributed to over one hundred scientific publications throughout her career.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
27 May 2019
Listed Since
09 February 2018

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