Overview
- Offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields
- With contributions from a variety of interdisciplinary fields
- Showcases the strong role of computational techniques in data analysis and classification
Part of the book series: Studies in Classification, Data Analysis, and Knowledge Organization (STUDIES CLASS)
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About this book
This book offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields. The contributions span a broad spectrum, from theoretical developments to practical applications; they all share a strong computational component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and Knowledge Discovery; Data Analysis in Marketing; Data Analysis in Finance and Economics; Data Analysis in Medicine and the Life Sciences; Data Analysis in the Social, Behavioural, and Health Care Sciences; Data Analysis in Interdisciplinary Domains; Classification and Subject Indexing in Library and Information Science.
The book presents selected papers from the Second European Conference on Data Analysis, held at Jacobs University Bremen in July 2014. This conference unites diverse researchers in the pursuit of a common topic, creating truly unique synergies in the process.
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Keywords
Table of contents (55 papers)
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Front Matter
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Invited Papers
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Front Matter
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Big Data
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Front Matter
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Clustering
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Front Matter
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Classification
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Front Matter
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Reviews
“Analysis of Large and Complex Data is a useful book for those who are very well read in sophisticated data analysis across variety of disciplines and are looking for a book that captures state-of-the-art scientific papers across a wide cross-section.” (Jonathan P. Wanderer, Anesthesia & Analgesia, Vol. 125 (1), July, 2017)
Editors and Affiliations
Bibliographic Information
Book Title: Analysis of Large and Complex Data
Editors: Adalbert F.X. Wilhelm, Hans A. Kestler
Series Title: Studies in Classification, Data Analysis, and Knowledge Organization
DOI: https://doi.org/10.1007/978-3-319-25226-1
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Softcover ISBN: 978-3-319-25224-7Published: 04 August 2016
eBook ISBN: 978-3-319-25226-1Published: 03 August 2016
Series ISSN: 1431-8814
Series E-ISSN: 2198-3321
Edition Number: 1
Number of Pages: XXVI, 656
Number of Illustrations: 139 b/w illustrations, 32 illustrations in colour
Topics: Statistics and Computing/Statistics Programs, Data Mining and Knowledge Discovery, Statistics for Life Sciences, Medicine, Health Sciences, Statistics for Business, Management, Economics, Finance, Insurance, Probability and Statistics in Computer Science, Biostatistics