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Analysis of Large and Complex Data

  • Adalbert F.X. Wilhelm
  • Hans A. Kestler

Table of contents

  1. Front Matter
    Pages i-xxvi
  2. Invited Papers

  3. Big Data

    1. Front Matter
      Pages 69-69
    2. Lyn-Rouven Schirra, Ludwig Lausser, Hans A. Kestler
      Pages 79-89
    3. Robert Retz, Friedhelm Schwenker
      Pages 91-101
    4. Maxim Yakovlev, Ekaterina Chernyak
      Pages 103-112
    5. Claus Weihs, Daniel Horn, Bernd Bischl
      Pages 113-122
  4. Clustering

    1. Front Matter
      Pages 123-123
    2. Hans-Joachim Mucha, Hans-Georg Bartel
      Pages 125-135
    3. Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols
      Pages 147-157
    4. Florent Domenach, George Portides
      Pages 159-169
  5. Classification

    1. Front Matter
      Pages 171-171
    2. Tomasz Górecki, Mirosław Krzyśko, Waldemar Wołyński
      Pages 173-183
    3. Angelos Markos, Alfonso Iodice D’Enza
      Pages 185-194
    4. Luca Frigau, Claudio Conversano, Francesco Mola
      Pages 207-217
  6. Regression and Other Statistical Techniques

    1. Front Matter
      Pages 219-219
    2. Sri Utami Zuliana, Aris Perperoglou
      Pages 231-239
    3. Dhouha Mejri, Mohamed Limam, Claus Weihs
      Pages 241-250
  7. Applications

    1. Front Matter
      Pages 251-251
    2. Sonja Köppl, Markus Hellmann, Klaus Jostschulte, Christian Wöhler
      Pages 265-274
    3. Osama Mahmoud, Andrew Harrison, Asma Gul, Zardad Khan, Metodi V. Metodiev, Berthold Lausen
      Pages 275-285
  8. Data Analysis in Marketing

    1. Front Matter
      Pages 299-299
  9. Data Analysis in Finance

  10. Data Analysis in Medicine and Life Sciences

    1. Front Matter
      Pages 383-383
    2. Timm Intemann, Hermann Pohlabeln, Diana Herrmann Wolfgang Ahrens, Iris Pigeot
      Pages 385-394
    3. Zardad Khan, Asma Gul, Osama Mahmoud, Miftahuddin Miftahuddin, Aris Perperoglou, Werner Adler et al.
      Pages 395-409
    4. Asma Gul, Zardad Khan, Aris Perperoglou, Osama Mahmoud, Miftahuddin Miftahuddin, Werner Adler et al.
      Pages 411-421
  11. Data Analysis in Musicology

    1. Front Matter
      Pages 423-423
    2. Denis Amelynck, Pieter-Jan Maes, Marc Leman, Jean-Pierre Martens
      Pages 425-435
    3. Igor Vatolkin, Geoffray Bonnin, Dietmar Jannach
      Pages 437-447
    4. Christophe Rhodes, Tim Crawford, Mark d’Inverno
      Pages 449-459
    5. Nadja Bauer, Klaus Friedrichs, Bernd Bischl, Claus Weihs
      Pages 461-472

About these proceedings

Introduction

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.p>

Keywords

Big Data Classification Cluster Analysis Complex Data Computational Statistics Data Analysis Musicology

Editors and affiliations

  • Adalbert F.X. Wilhelm
    • 1
  • Hans A. Kestler
    • 2
  1. 1.Jacobs University Bremen BremenGermany
  2. 2.Universität UlmInstitute of Medical Systems Biology Universität UlmUlmGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-25226-1
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-25224-7
  • Online ISBN 978-3-319-25226-1
  • Series Print ISSN 1431-8814
  • Series Online ISSN 2198-3321
  • Buy this book on publisher's site