Data Science, Learning by Latent Structures, and Knowledge Discovery

• Corporate Author: SpringerLink (Online service)
• Other Authors: Lausen, Berthold (Editor), Krolak-Schwerdt, Sabine (Editor), Böhmer, Matthias (Editor)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2015.
• Series: Studies in Classification, Data Analysis, and Knowledge Organization,
• Subjects: Statistics.; Marketing.; Operations research.; Decision making.; Data mining.; Biostatistics.; Psychometrics.; Statistics, general.; Data Mining and Knowledge Discovery.; Operation Research/Decision Theory.
• Physical Description: XXII, 560 p. 145 illus., 56 illus. in color. online resource.
• ISBN: 9783662449837
• ISSN: 1431-8814

This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering, and pattern recognition methods; strategies for modeling complex data and mining large data sets; applications of advanced methods in specific domains of practice. The contributions offer interesting applications to various disciplines such as psychology, biology, medical and health sciences; economics, marketing, banking, and finance; engineering; geography and geology;  archeology, sociology, educational sciences, linguistics, and musicology; library science. The book contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French-speaking Classification Society (SFC) in July 2013 at the University of Luxembourg.