Data Science, Learning by Latent Structures, and Knowledge Discovery

Berthold Lausen

ISBN 10: 366244982X / ISBN 13: 9783662449820

Published by Springer, Springer Spektrum Mai 2015, 2015

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 584 pp. Englisch.

Seller Inventory # 9783662449820

Bibliographic Details

• Title: Data Science, Learning by Latent Structures, and Knowledge Discovery
• Publisher: Springer, Springer Spektrum Mai 2015
• Publication Date: 2015
• Language: English
• ISBN 10: 366244982X
• ISBN 13: 9783662449820
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 32D millimeters 235 millimeters width by 155 millimeters height by 32 millimeters depth
• Weight: 873 grams

About this title

Synopsis

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.