Data Science, Learning by Latent Structures, and Knowledge Discovery

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.Data Science, Learning by Latent Structures, and Knowledge Discovery and published by Springer. ISBNs for Data Science, Learning by Latent Structures, and Knowledge Discovery are 9783662449837, 3662449838 and the print ISBNs are 9783662449820, 366244982X.