Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I

  • Editors
  • Walter Daelemans
  • Bart Goethals
  • Katharina Morik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5211)

Table of contents

  1. Front Matter
  2. Invited Talks (Abstracts)

  3. Machine Learning Journal Abstracts

    1. Christos Dimitrakakis, Michail G. Lagoudakis
      Pages 7-7
    2. Krishnamurthy Dvijotham, Soumen Chakrabarti, Subhasis Chaudhuri
      Pages 8-8
    3. Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik
      Pages 9-10
    4. Heng Luo, Changyong Niu, Ruimin Shen, Carsten Ullrich
      Pages 12-12
    5. Stijn Vanderlooy, Eyke Hüllermeier
      Pages 13-13
    6. Markus Weimer, Alexandros Karatzoglou, Alex Smola
      Pages 14-14
  4. Data Mining and Knowledge Discovery Journal Abstracts

    1. Petteri Hintsanen, Hannu Toivonen
      Pages 15-15
    2. Apostolos N. Papadopoulos, Apostolos Lyritsis, Yannis Manolopoulos
      Pages 18-18
    3. Chedy Raïssi, Toon Calders, Pascal Poncelet
      Pages 19-19
    4. Arnaud Soulet, Bruno Crémilleux
      Pages 20-21
    5. Jimeng Sun, Charalampos E. Tsourakakis, Evan Hoke, Christos Faloutsos, Tina Eliassi-Rad
      Pages 22-22

Other volumes

  1. Machine Learning and Knowledge Discovery in Databases
    European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I
  2. European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II

About these proceedings

Introduction

This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008.

The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer.

The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.

Keywords

Averaging Support Vector Machine active learning algorithmic learning association rule mining bayesian learning case-based learning clustering distributed computing k-Means machine learning master data management performance performance evaluation reinforcement learning

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-87479-9
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-87478-2
  • Online ISBN 978-3-540-87479-9
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book