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Advances in Data Analysis, Data Handling and Business Intelligence, Proceedings of the 32nd Annual Conference of the Gesellschaft für Klassifikation e.V., Joint Conference with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), Helmut-Schmidt-University, Hamburg, July 16-18, 2008

Fink, A and Lausen, B and Seidel, W and Ultsch, A (2010) Advances in Data Analysis, Data Handling and Business Intelligence, Proceedings of the 32nd Annual Conference of the Gesellschaft für Klassifikation e.V., Joint Conference with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), Helmut-Schmidt-University, Hamburg, July 16-18, 2008. Studies in Classification, Data Analysis, and Knowledge Organization . Springer-Verlag. ISBN 978-3-642-01043-9

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Abstract

Data Analysis, Data Handling and Business Intelligence 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 in marketing, finance, economics, engineering, linguistics, archaeology, musicology, medical science, and biology. This volume contains the revised versions of selected papers presented during the 32nd Annual Conference of the German Classification Society (Gesellschaft für Klassifikation, GfKl). The conference, which was organized in cooperation with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), was hosted by Helmut-Schmidt-University, Hamburg, Germany, in July 2008.

Item Type: Book
Uncontrolled Keywords: Artificial Intelligence; Classification; Clustering; Data Analysis; Databionics; Machine Learning
Subjects: H Social Sciences > HA Statistics
Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Mathematical Sciences, Department of
Depositing User: Jim Jamieson
Date Deposited: 12 Dec 2011 16:49
Last Modified: 18 Oct 2017 16:18
URI: http://repository.essex.ac.uk/id/eprint/1778

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