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Machine Learning and Data Mining in Pattern Recognition

5th International Conference, MLDM 2007, Leipzig, Germany, July 18-20, 2007. Proceedings

  • Editors
  • Petra Perner

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4571)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 4571)

Table of contents

  1. Front Matter
  2. Invited Talk

    1. Anil K. Jain
      Pages 1-1
  3. Classification

    1. Paul R. Trundle, Daniel C. Neagu, Qasim Chaudhry
      Pages 32-46
    2. Claudio Marrocco, Mario Molinara, Francesco Tortorella
      Pages 47-60
    3. Longin Jan Latecki, Aleksandar Lazarevic, Dragoljub Pokrajac
      Pages 61-75
    4. Tao Wang, Zhoujun Li, Yuejin Yan, Huowang Chen
      Pages 91-103
    5. Gero Szepannek, Bernd Bischl, Claus Weihs
      Pages 104-116
  4. Feature Selection, Extraction and Dimensionality Reduction

    1. Ireneusz Czarnowski, Piotr Jȩdrzejowicz
      Pages 117-130
    2. Moonhwi Lee, Cheong Hee Park
      Pages 131-143
    3. Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yoshihira
      Pages 144-159
  5. Clustering

    1. Sandro Saitta, Benny Raphael, Ian F. C. Smith
      Pages 174-187
    2. Xuegang Hu, Dongbo Wang, Xindong Wu
      Pages 188-202
    3. Ivan O Kyrgyzov, Olexiy O Kyrgyzov, Henri Maître, Marine Campedel
      Pages 203-217
    4. Tomoya Sakai, Atsushi Imiya, Takuto Komazaki, Shiomu Hama
      Pages 218-232
    5. Airel Pérez Suárez, José E. Medina Pagola
      Pages 248-262
  6. Support Vector Machine

    1. D. Valincius, A. Verikas, M. Bacauskiene, A. Gelzinis
      Pages 263-275
    2. Chaofan Sun, Ricardo Vilalta
      Pages 286-295
    3. Jun Jiang, Horace H. S. Ip
      Pages 296-309
  7. Transductive Inference

    1. Stijn Vanderlooy, Laurens van der Maaten, Ida Sprinkhuizen-Kuyper
      Pages 310-323
    2. Michelangelo Ceci, Annalisa Appice, Nicola Barile, Donato Malerba
      Pages 324-338
  8. Association Rule Mining

    1. Yanbo J. Wang, Qin Xin, Frans Coenen
      Pages 339-348
    2. J. Hernández Palancar, O. Fraxedas Tormo, J. Festón Cárdenas, R. Hernández León
      Pages 349-363
  9. Mining Spam, Newsgroups, Blogs

    1. J. R. Méndez, B. Corzo, D. Glez-Peña, F. Fdez-Riverola, F. Díaz
      Pages 364-378
    2. James Geller, Sapankumar Parikh, Sriram Krishnan
      Pages 379-391
    3. Hongbo Liu, Jiahai Yang, Jiaxin Wang, Yu Zhang
      Pages 392-403
  10. Intrusion Detection and Networks

    1. Peter Géczy, Noriaki Izumi, Shotaro Akaho, Kôiti Hasida
      Pages 419-433
    2. Alessandro Micarelli, Giuseppe Sansonetti
      Pages 434-448
    3. Davide Ariu, Giorgio Giacinto, Roberto Perdisci
      Pages 449-463
  11. Frequent and Common Item Set Mining

    1. Robert Fuller, Mehmed Kantardzic
      Pages 464-478
    2. Fujiang Ao, Yuejin Yan, Jian Huang, Kedi Huang
      Pages 479-489
    3. Yohji Shidara, Atsuyoshi Nakamura, Mineichi Kudo
      Pages 490-498
  12. Mining Marketing Data

  13. Structural Data Mining

  14. Image Mining

About these proceedings

Introduction

MLDM / ICDM Medaillie Meissner Porcellan, the “White Gold” of King August the Strongest of Saxonia Gottfried Wilhelm von Leibniz, the great mathematician and son of Leipzig, was watching over us during our event in Machine Learning and Data Mining in Pattern Recognition (MLDM 2007). He can be proud of what we have achieved in this area so far. We had a great research program this year. This was the fifth MLDM in Pattern Recognition event held in Leipzig (www.mldm.de). Today, there are many international meetings carrying the title machine learning and data mining, whose topics are text mining, knowledge discovery, and applications. This meeting from the very first event has focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the view points of machine learning and data mining. Although it was a challenging program in the late 1990s, the idea has provided new starting points in pattern recognition and has influenced other areas such as cognitive computer vision. For this edition, the Program Committee received 258 submissions from 37 countries (see Fig. 1). To handle this high number of papers was a big challenge for the reviewers. Every paper was thoroughly reviewed and all authors received a detailed report on their submitted work.

Keywords

Spam classification cognition data mining learning machine learning pattern recognition

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-73499-4
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-73498-7
  • Online ISBN 978-3-540-73499-4
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site