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
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Beschreibung
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.
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.
Includes supplementary material: sn.pub/extras
Autor*in
Christine Preisach
Themen in »Data Analysis, Machine Learning and Applications«
artificial intelligence bioinformatics business intelligence classification clustering computer science data analysis intelligence learning linguistics machine learning semantic web service-oriented computing web mining
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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)
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