Data Analysis, Machine Learning and Applications

Proceedings of the 31st Annual Conference of the Gesellschaft für Klassifikation e.V., Albert-Ludwigs-Universität Freiburg, March 7-9, 2007

AvChristine Preisach,Hans Burkhardt

Häftad, Engelska, 2008

Del i serien Studies in Classification, Data Analysis, and Knowledge Organization

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Beskrivning

Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007.

Produktinformation

Utgivningsdatum:2008-04-29
Mått:155 x 235 x undefined mm
Format:Häftad
Språk:Engelska
Serie:Studies in Classification, Data Analysis, and Knowledge Organization
Antal sidor:719
Förlag:Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN:9783540782391

Utforska kategorier

Artificiell intelligens inom Data och IT

Recensioner i media

From the reviews: "Data analysis and machine learning are potential research areas at the intersection of computer science (including artificial intelligence) and mathematical sciences (including both mathematics and statistics). This book contains a good collection of papers in these areas, describing their application in areas such as marketing and bioinformatics. ... It is surely a must have book for any scientific library and indispensable for the scientific researcher." (Soubhik Chakraborthy, ACM Computing Reviews, February, 2010)

Innehållsförteckning

Classification.- Clustering.- Multidimensional Data Analysis.- Analysis of Complex Data.- Exploratory Data Analysis and Tools for Data Analysis.- Marketing and Management Science.- Banking and Finance.- Business Intelligence.- Text Mining, Web Mining, and the Semantic Web.- Linguistics.- Data Analysis in Humanities.