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Advances in Data Analysis [electronic resource] :Proceedings of the 30th Annual Conference of the Gesellschaft für Klassifikation e.V., Freie Universität Berlin, March 8–10, 2006 / edited by Reinhold Decker, Hans -J. Lenz.

by Decker, Reinhold [editor.]; Lenz, Hans -J [editor.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Classification, Data Analysis, and Knowledge Organization: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.Description: XVI, 687 p. online resource.ISBN: 9783540709817.Subject(s): Statistics | Data mining | Mathematical statistics | Economics -- Statistics | Statistics | Statistical Theory and Methods | Data Mining and Knowledge Discovery | Statistics for Business/Economics/Mathematical Finance/Insurance | Statistics for Life Sciences, Medicine, Health Sciences | Statistics for Social Science, Behavorial Science, Education, Public Policy, and LawDDC classification: 519.5 Online resources: Click here to access online
Contents:
Clustering -- Classification -- Data and Time Series Analysis -- Visualization and Scaling Methods -- Information Retrieval, Data and Web Mining -- Marketing, Management Science and Economics -- Banking and Finance -- Bio- and Health Sciences -- Linguistics and Text Analysis -- Statistical Musicology and Sound Classification -- Archaeology.
In: Springer eBooksSummary: The book focuses on exploratory data analysis, learning of latent structures in datasets, and unscrambling of knowledge. It covers a broad range of methods from multivariate statistics, clustering and classification, visualization and scaling as well as from data and time series analysis. It provides new approaches for information retrieval and data mining. Furthermore, the book reports challenging applications in marketing and management science, banking and finance, bio- and health sciences, linguistics and text analysis, statistical musicology and sound classification, as well as archaeology. Special emphasis is put on interdisciplinary research and the interaction between theory and practice.
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Clustering -- Classification -- Data and Time Series Analysis -- Visualization and Scaling Methods -- Information Retrieval, Data and Web Mining -- Marketing, Management Science and Economics -- Banking and Finance -- Bio- and Health Sciences -- Linguistics and Text Analysis -- Statistical Musicology and Sound Classification -- Archaeology.

The book focuses on exploratory data analysis, learning of latent structures in datasets, and unscrambling of knowledge. It covers a broad range of methods from multivariate statistics, clustering and classification, visualization and scaling as well as from data and time series analysis. It provides new approaches for information retrieval and data mining. Furthermore, the book reports challenging applications in marketing and management science, banking and finance, bio- and health sciences, linguistics and text analysis, statistical musicology and sound classification, as well as archaeology. Special emphasis is put on interdisciplinary research and the interaction between theory and practice.

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