Data Science, Learning by Latent Structures, and Knowledge Discovery (Paperback)

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.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Studies in Classification, Data Analysis, and Knowledge Organization
Release date:	May 2015
First published:	2015
Editors:	Berthold Lausen • Sabine Krolak-Schwerdt • Matthias Boehmer
Dimensions:	235 x 155 x 32mm (L x W x T)
Format:	Paperback
Pages:	560
ISBN-13:	978-3-662-44982-0
Categories:	Books > Reference & Interdisciplinary > Communication studies > Research methods Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > Applications of computing > Databases > Data mining Promotions
LSN:	3-662-44982-X
Barcode:	9783662449820

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