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Advances in Machine Learning II

Dedicated to the Memory of Professor Ryszard S.Michalski

  • Jacek Koronacki
  • Zbigniew W. Raś
  • Sławomir T. Wierzchoń
  • Janusz Kacprzyk

Part of the Studies in Computational Intelligence book series (SCI, volume 263)

Table of contents

  1. Front Matter
  2. General Issues

    1. Front Matter
      Pages 1-1
    2. Andrzej Skowron, Marcin Szczuka
      Pages 23-42
    3. Stan Matwin, Tomasz Szapiro
      Pages 43-74
    4. Phillipa M. Avery, Zbigniew Michalewicz
      Pages 75-100
    5. Mirsad Hadzikadic, Min Sun
      Pages 101-118
  3. Logical and Relational Learning, and Beyond

  4. Text and Web Mining

    1. Front Matter
      Pages 205-205
    2. Katharina Morik, Michael Wurst
      Pages 207-223
    3. Miroslav Kubat, Kanoksri Sarinnapakorn, Sareewan Dendamrongvit
      Pages 225-244
    4. Boris Mirkin, Susana Nascimento, Luís Moniz Pereira
      Pages 245-257
    5. Marzena Kryszkiewicz, Henryk Rybiński, Katarzyna Cichoń
      Pages 259-289
  5. Classification and Beyond

    1. Front Matter
      Pages 291-291
    2. Derek Sleeman, Andy Aiken, Laura Moss, John Kinsella, Malcolm Sim
      Pages 293-314
    3. Eduardo R. Gomes, Ryszard Kowalczyk
      Pages 315-349
    4. Christian Borgelt
      Pages 351-369
    5. Michał Dramiński, Marcin Kierczak, Jacek Koronacki, Jan Komorowski
      Pages 371-385
    6. Halina Kwaśnicka, Mariusz Paradowski
      Pages 387-411
  6. Neural Networks and Other Nature Inspired Approaches

    1. Front Matter
      Pages 413-413
    2. Boris Kryzhanovsky, Vladimir Kryzhanovsky, Leonid Litinskii
      Pages 427-443
    3. Hongbo Liu, Ajith Abraham, Benxian Yue
      Pages 445-466
    4. Tomasz Maszczyk, Marek Grochowski, Włodzisław Duch
      Pages 467-484
    5. Vladimir Golovko, Sergei Bezobrazov, Pavel Kachurka, Leanid Vaitsekhovich
      Pages 485-513
    6. Alexander O. Tarakanov
      Pages 515-529
  7. Back Matter

About this book

Introduction

This is the second volume of a large two-volume editorial project we wish to dedicate to the memory of the late Professor Ryszard S. Michalski who passed away in 2007. He was one of the fathers of machine learning, an exciting and relevant, both from the practical and theoretical points of view, area in modern computer science and information technology. His research career started in the mid-1960s in Poland, in the Institute of Automation, Polish Academy of Sciences in Warsaw, Poland. He left for the USA in 1970, and since then had worked there at various universities, notably, at the University of Illinois at Urbana – Champaign and finally, until his untimely death, at George Mason University. We, the editors, had been lucky to be able to meet and collaborate with Ryszard for years, indeed some of us knew him when he was still in Poland. After he started working in the USA, he was a frequent visitor to Poland, taking part at many conferences until his death. We had also witnessed with a great personal pleasure honors and awards he had received over the years, notably when some years ago he was elected Foreign Member of the Polish Academy of Sciences among some top scientists and scholars from all over the world, including Nobel prize winners.

Professor Michalski’s research results influenced very strongly the development of machine learning, data mining, and related areas. Also, he inspired many established and younger scholars and scientists all over the world.

We feel very happy that so many top scientists from all over the world agreed to pay the last tribute to Professor Michalski by writing papers in their areas of research. These papers will constitute the most appropriate tribute to Professor Michalski, a devoted scholar and researcher. Moreover, we believe that they will inspire many newcomers and younger researchers in the area of broadly perceived machine learning, data analysis and data mining.

The papers included in the two volumes, Machine Learning I and Machine Learning II, cover diverse topics, and various aspects of the fields involved. For convenience of the potential readers, we will now briefly summarize the contents of the particular chapters.

Keywords

STATISTICA Web 2.0 classification data analysis data mining evolutionary algorithm heuristics learning machine learning proving supervised learning unsupervised learning visualization web mining

Editors and affiliations

  • Jacek Koronacki
    • 1
  • Zbigniew W. Raś
    • 2
  • Sławomir T. Wierzchoń
    • 1
  • Janusz Kacprzyk
    • 3
  1. 1.Institute of Computer SciencePolish Academy of SciencesWarsawPoland
  2. 2.Woodward Hall 430C, University of North CarolinaCharlotteUSA
  3. 3.Systems Research InstitutePolish Academy of SciencesWarsawPoland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-05179-1
  • Copyright Information Springer-Verlag Berlin Heidelberg 2010
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-05178-4
  • Online ISBN 978-3-642-05179-1
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site