New Frontiers in Mining Complex Patterns

Third International Workshop, NFMCP 2014, Held in Conjunction with ECML-PKDD 2014, Nancy, France, September 19, 2014, Revised Selected Papers

  • Annalisa Appice
  • Michelangelo Ceci
  • Corrado Loglisci
  • Giuseppe Manco
  • Elio Masciari
  • Zbigniew W. Ras
Conference proceedings NFMCP 2014
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8983)

Table of contents

  1. Front Matter
    Pages I-XII
  2. Classification and Regression

    1. Front Matter
      Pages 1-1
    2. Jurica Levatić, Michelangelo Ceci, Dragi Kocev, Sašo Džeroski
      Pages 3-18
    3. Gjorgji Madjarov, Ivica Dimitrovski, Dejan Gjorgjevikj, Sašo Džeroski
      Pages 19-37
  3. Clustering

    1. Front Matter
      Pages 39-39
    2. Ayman Hajja, Hakim Touati, Zbigniew W. Raś, James Studnicki, Alicja A. Wieczorkowska
      Pages 41-55
    3. Julian Yarkony, Thorsten Beier, Pierre Baldi, Fred A. Hamprecht
      Pages 56-68
    4. Parinaz Sobhani, Herna Viktor, Stan Matwin
      Pages 69-83
  4. Data Streams and Sequences

    1. Front Matter
      Pages 85-85
    2. Jens Haase, Ulf Brefeld
      Pages 102-116
    3. Rui Sarmento, Mário Cordeiro, João Gama
      Pages 117-131
    4. Marc Plantevit, Vasile-Marian Scuturici, Céline Robardet
      Pages 132-146
  5. Applications

    1. Front Matter
      Pages 147-147
    2. Claudia Diamantini, Laura Genga, Domenico Potena, Emanuele Storti
      Pages 149-163
    3. Stefano Ferilli, Berardina De Carolis, Floriana Esposito
      Pages 164-178
    4. Elżbieta Kubera, Alicja A. Wieczorkowska
      Pages 194-209
  6. Back Matter
    Pages 211-211

About these proceedings

Introduction

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2014, held in conjunction with ECML-PKDD 2014 in Nancy, France, in September 2014. The 13 revised full papers presented were carefully reviewed and selected from numerous submissions. They illustrate advanced data mining techniques which preserve the informative richness of complex data and allow for efficient and effective identification of complex information units present in such data. The papers are organized in the following sections: classification and regression; clustering; data streams and sequences; applications.

Keywords

classification clustering data mining feature selection machine learning network models semantic similarity measures support vector machines time series analysis validation

Editors and affiliations

  • Annalisa Appice
    • 1
  • Michelangelo Ceci
    • 2
  • Corrado Loglisci
    • 3
  • Giuseppe Manco
    • 4
  • Elio Masciari
    • 5
  • Zbigniew W. Ras
    • 6
  1. 1.Università degli Studi di Bari Aldo MoroBariItaly
  2. 2.Università degli Studi di Bari Aldo MoroBariItaly
  3. 3.Università degli Studi di Bari Aldo MoroBariItaly
  4. 4.ICAR-CNRRendeItaly
  5. 5.ICAR-CNRRendeItaly
  6. 6.University of North Carolina, Charlotte, USA and Warsaw University of TechnologyWarsawPoland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-17876-9
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-17875-2
  • Online ISBN 978-3-319-17876-9
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book