Machine Learning and Data Mining in Pattern Recognition

8th International Conference, MLDM 2012, Berlin, Germany, July 13-20, 2012. Proceedings

  • Petra Perner

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7376)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 7376)

Table of contents

  1. Front Matter
  2. Theory

    1. Pavel Turkov, Olga Krasotkina, Vadim Mottl
      Pages 1-10
    2. Michelangelo Ceci, Annalisa Appice, Herna L. Viktor, Donato Malerba, Eric Paquet, Hongyu Guo
      Pages 11-25
    3. Hai Thanh Nguyen, Katrin Franke
      Pages 40-49
    4. Dieter William Joenssen, Udo Bankhofer
      Pages 63-75
    5. Saket Bharambe, Harshit Dubey, Vikram Pudi
      Pages 76-85
    6. Kartick Chandra Mondal, Nicolas Pasquier, Anirban Mukhopadhyay, Ujjwal Maulik, Sanghamitra Bandhopadyay
      Pages 86-101
    7. Aixiang Li, Makoto Haraguchi, Yoshiaki Okubo
      Pages 102-116
  3. Theory: Evaluation of Models and Performance Evaluation Methods

    1. Rui Leite, Pavel Brazdil, Joaquin Vanschoren
      Pages 117-131
    2. Upendra Sapkota, Barrett R. Bryant, Alan Sprague
      Pages 141-153
    3. Thais Mayumi Oshiro, Pedro Santoro Perez, José Augusto Baranauskas
      Pages 154-168
  4. Theory: Learning

    1. Heni Bouhamed, Afif Masmoudi, Thierry Lecroq, Ahmed Rebaï
      Pages 183-197
    2. Nikolaos Pitelis, Anastasios Tefas
      Pages 198-212
    3. Nong Thi Hoa, Bui The Duy
      Pages 213-221
  5. Theory: Clustering

    1. Javid Ebrahimi, Mohammad Saniee Abadeh
      Pages 237-251

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 8th International Conference, MLDM 2012, held in Berlin, Germany in July 2012. The 51 revised full papers presented were carefully reviewed and selected from 212 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and web mining.

Keywords

data stream clustering multi-relational classification particle swarm optimization support vector machine transductive learning

Editors and affiliations

  • Petra Perner
    • 1
  1. 1.Institute of Computer Vision and Applied Computer SciencesIBaILeipzigGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-31537-4
  • Copyright Information Springer-Verlag Berlin Heidelberg 2012
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-31536-7
  • Online ISBN 978-3-642-31537-4
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book