Lausen, B and Krolak-Schwerdt, S and Böhmer, M (2015) Data science, learning by latent structures, and knowledge discovery. Studies in Classification, Data Analysis, and Knowledge Organization, 48 . Springer, pp. 1-22.

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Abstract

This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering and pattern recognition methods; strategies for modeling complex data and mining large data sets; applications of advanced methods in specific domains of practice. The contributions offer interesting applications to various disciplines such as psychology, biology, medical and health sciences; economics, marketing, banking and finance; engineering; geography and geology; archeology, sociology, educational sciences, linguistics and musicology; library science. The book contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French-speaking Classification Society (SFC) in July 2013 at the University of Luxembourg.

Item Type:	Book
Additional Information:	European Conference on Data Analysis, Luxembourg, July, 2013, Series: Studies in Classification, Data Analysis, and Knowledge Organization
Subjects:	H Social Sciences > HA Statistics H Social Sciences > HF Commerce Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Science and Health Faculty of Science and Health > Mathematical Sciences, Department of
SWORD Depositor:	Elements
Depositing User:	Elements
Date Deposited:	05 Sep 2014 11:07
Last Modified:	15 Jan 2022 01:12
URI:	http://repository.essex.ac.uk/id/eprint/9968

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