Data Science, Learning by Latent Structures, and Knowledge Discovery
Data Science, Learning by Latent Structures, and Knowledge Discovery
Springer | Business & Management | June 14 2015 | ISBN-10: 366244982X | 560 pages | pdf | 30.6 mb
Springer | Business & Management | June 14 2015 | ISBN-10: 366244982X | 560 pages | pdf | 30.6 mb
by Berthold Lausen (Editor), Sabine Krolak-Schwerdt (Editor), Matthias Böhmer (Editor)
From the Back Cover
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.
Topics
Statistics (general)
Marketing
Psychometrics
Biostatistics
Data Mining and Knowledge Discovery
Operation Research / Decision Theory