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
Herausgegeben:Gaul, Wolfgang; Geyer-Schulz, Andreas; Schmidt-Thieme, Lars; Kunze, Jonas

• Broschiertes Buch

Produktbeschreibung

This volume provides approaches and solutions to challenging problems 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 an adequate analysis and interpretation of the observed data that match optimally the underlying practical situations. Beside traditional classification research, the book focuses also on current interests in fields such as the analysis of network data, graphs, and social relationships as well as on statistical musicology.

Produktdetails

• Studies in Classification, Data Analysis, and Knowledge Organization
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 80113997, 978-3-642-24465-0
• 2012
• Seitenzahl: 612
• Erscheinungstermin: 9. Februar 2012
• Englisch
• Abmessung: 235mm x 155mm x 33mm
• Gewicht: 914g
• ISBN-13: 9783642244650
• ISBN-10: 3642244653
• Artikelnr.: 33926169

Inhaltsangabe

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.

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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.