Davino / Palumbo / Wilhelm Recent Trends and Future Challenges in Learning from Data

1. Auflage 2024
ISBN: 978-3-031-54468-2
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 153 Seiten, eBook

Reihe: Studies in Classification, Data Analysis, and Knowledge Organization

This book collects together selected peer-reviewed contributions presented at the European Conference on Data Analysis, ECDA 2022, held in Naples, Italy, September 14-16, 2022. Highlighting the role of statistics in discovering novel and interesting patterns in the era of big data, it follows the motto of the conference: “Avoiding drowning in the data: recent trends and future challenges in learning from data”. The central focus is on multidisciplinary approaches to data analysis, classification, and the interface between computer science, data mining and statistics. Both methodological and applied topics are covered. The former includes supervised and unsupervised techniques with particular emphasis on advances in regression and clustering analysis and constructing composite indicators. The applications are mainly in risk analysis, biology, and education. The volume is organized into four main macro themes: methodological contributions in the social sciences and education, multivariate analysis methods for big data, innovative contributions for applications inspired by biology, and strategies for analyzing complex data in finance.

Zielgruppe

Research

Autoren/Hrsg.

Davino, Cristina

Palumbo, Francesco

Wilhelm, Adalbert F. X.

Kestler, Hans A.

Inhaltsverzeichnis

Preface.- Building hierarchies of factors with disjoint factor analysis.- Uncertainty in Latent Trait Models and dimensionality reduction methods for complex data: an analysis of taxpayer perception on the Fiscal System.- The predictivity of access tests for university success.- Asynchronous and synchronous-asynchronous particle swarms.- The impact of the Covid-19 pandemic on modelling volatility and risk analysis of returns in selected European financial markets.- Asymmetric binary regression models for imbalanced datasets: an application to students’ churn.- Computational models supporting decision-making in managing publication activity at Polish universities.- Stability of nonparametric methods for cognitive diagnostic assessment.- SMARTS: SeMi-supervised clustering for Assessment of Reviews using Topic and Sentiment.- The equitable and sustainable wellbeing through the pandemic. A first study to assess changes at local level in Italy.- Choice-Based Optimization under High-Dimensional MNL.- A first glance on co-evolution of Boolean networks to simulate the development of cross-talking systems in molecular biology.- Classification on polish fund market during COVID-19 pandemic - extreme risk modeling approach.

Über Autor(innen)

Cristina Davino is an Associate Professor in Statistics at the University of Naples Federico II, Italy. Her fields of interest and areas of expertise are multidimensional data analysis, data mining, quantile regression, statistical surveys, quality of life assessment, evaluation of university education processes, construction and validation of composite indicators and analysis of learning processes. She has been involved in many research projects whose results have been disseminated in international journals and conferences.

Francesco Palumbo is a Professor of Statistics at Federico II University of Naples, Italy. He teaches Statistics and Psychometric Statistics in basic and advanced courses. He is the Editor-in-Chief of the Italian Journal of Applied Statistics and an Associate Editor of Computational Statistics. He has collaborated on numerous European projects and has participated in and coordinated several national research projects. His main research interests are in classification and data analysis.

Adalbert Wilhelm holds a Professorship in Statistics at Constructor University, Bremen, Germany. He is also the Vice Dean of the Bremen International Graduate School of Social Sciences (BIGSSS). His main research is on statistical visualization, exploratory data analysis and data mining and his recent work addresses questions of digitalization and big data applied to a broad range of disciplines such as economics, business administration, political science, sociology and psychology.

Hans A. Kestler is currently a Professor and the Head of the Institute of Medical Systems Biology and the Core Unit Bioinformatics within the Faculties of Computer Science and Medicine, Ulm University, Germany. He is also an Associated Group Leader with the Leibniz Institute on Aging, Jena. He has published more than 330 articles in journals, books, and conferences. His research interests include methodological foundations of pattern recognition, bioinformatics, molecular systems biology, and digital health.