Data Analysis, Machine Learning and Knowledge Discovery

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Myra Spiliopoulou, Lars Schmidt-Thieme, Ruth Janning
Springer Science & Business Media, Nov 26, 2013 - Computers - 470 pages
Data analysis, machine learning and knowledge discovery 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, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and knowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012.
 

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Contents

Clustering Classifiers Streams and Social Networks
125
Part III AREA Data Analysis and Classification in Marketing
179
Part IV AREA Data Analysis in Finance
244
Part V AREA Data Analysis in Biostatistics and Bioinformatics
282
Data Analysis in Music Education and Psychology
312
Workshop on Classification and Subject Indexing in Library and Information Science
435
Index
463
Author Index
468
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