Gaul, Wolfgang A.
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 / [electronic resource] : edited by Wolfgang A. Gaul, Andreas Geyer-Schulz, Lars Schmidt-Thieme, Jonas Kunze. - XIV, 598p. 163 illus. online resource. - Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814 . - Studies in Classification, Data Analysis, and Knowledge Organization, .
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.
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.
9783642244667
10.1007/978-3-642-24466-7 doi
Statistics.
Data structures (Computer science).
Data mining.
Mathematical statistics.
Operations research.
Statistics.
Statistics and Computing/Statistics Programs.
Data Structures.
Operations Research, Management Science.
Operation Research/Decision Theory.
Data Mining and Knowledge Discovery.
QA276-280
519.5
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 / [electronic resource] : edited by Wolfgang A. Gaul, Andreas Geyer-Schulz, Lars Schmidt-Thieme, Jonas Kunze. - XIV, 598p. 163 illus. online resource. - Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814 . - Studies in Classification, Data Analysis, and Knowledge Organization, .
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.
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.
9783642244667
10.1007/978-3-642-24466-7 doi
Statistics.
Data structures (Computer science).
Data mining.
Mathematical statistics.
Operations research.
Statistics.
Statistics and Computing/Statistics Programs.
Data Structures.
Operations Research, Management Science.
Operation Research/Decision Theory.
Data Mining and Knowledge Discovery.
QA276-280
519.5