Challenges at the Interface of Data Analysis, Computer Science, and Optimization
Proceedings of the 34th Annual Conference of the Gesellschaft für Klassifikation e. V., Karlsruhe, July 21 - 23, 2010
Published on 9. February 2012
Book
Paperback/Softback
XIV, 598 pages
978-3-642-24465-0 (ISBN)
Description
This volume provides approaches and solutions to challenges occurring at the interface of research fields such as data analysis, computer science, operations research, and statistics. It includes theoretically oriented contributions as well as papers from various application areas, where knowledge from different research directions is needed to find the best possible interpretation of data for the underlying problem situations. Beside traditional classification research, the book focuses on current interests in fields such as the analysis of social relationships as well as statistical musicology.
More details
Series
Edition
2012
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
163 s/w Abbildungen
XIV, 598 p. 163 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 33 mm
Weight
914 gr
ISBN-13
978-3-642-24465-0 (9783642244650)
DOI
10.1007/978-3-642-24466-7
Schweitzer Classification
Other editions
Additional editions
Wolfgang A. Gaul | Andreas Geyer-Schulz | Lars Schmidt-Thieme
Challenges at the Interface of Data Analysis, Computer Science, and Optimization
Proceedings of the 34th Annual Conference of the Gesellschaft für Klassifikation e. V., Karlsruhe, July 21 - 23, 2010
E-Book
02/2012
1st Edition
Springer
€96.29
Available for download
Content
Classification, Cluster Analysis, and Multidimensional Scaling.- Quantification Theory.- Analysis of m-Mode n-Way and Asymmetric Data.- Analysis of Visual, Spatial, and Temporal Data.- Network Data, Graphs, and Social Relationships.- Text Mining.- Dimension Reduction.- Statistical Musicology.- Data Analysis in Banking and Finance.- Data Analysis in Health and Environment.- Analysis of Marketing, Conjoint, and Multigroup Data.- Data Analysis in Education and Psychology.- Analysis of Tourism Data.