Advances in Intelligent Data Analysis VIII

8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009. Proceedings

  • Niall M. Adams
  • Céline Robardet
  • Arno Siebes
  • Jean-François Boulicaut
Conference proceedings IDA 2009

DOI: 10.1007/978-3-642-03915-7

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5772)

Table of contents (35 papers)

  1. Front Matter
  2. Invited Papers

  3. Selected Contributions 1 (Long Talks)

    1. Change (Detection) You Can Believe in: Finding Distributional Shifts in Data Streams
      Tamraparni Dasu, Shankar Krishnan, Dongyu Lin, Suresh Venkatasubramanian, Kevin Yi
      Pages 21-34
    2. Exploiting Data Missingness in Bayesian Network Modeling
      Sérgio Rodrigues de Morais, Alex Aussem
      Pages 35-46
    3. How to Control Clustering Results? Flexible Clustering Aggregation
      Martin Hahmann, Peter B. Volk, Frank Rosenthal, Dirk Habich, Wolfgang Lehner
      Pages 59-70
    4. Context-Based Distance Learning for Categorical Data Clustering
      Dino Ienco, Ruggero G. Pensa, Rosa Meo
      Pages 83-94
    5. Improving k-NN for Human Cancer Classification Using the Gene Expression Profiles
      Manuel Martín-Merino, Javier De Las Rivas
      Pages 107-118
    6. Subgroup Discovery for Test Selection: A Novel Approach and Its Application to Breast Cancer Diagnosis
      Marianne Mueller, Rómer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, Stefan Kramer
      Pages 119-130
    7. Trajectory Voting and Classification Based on Spatiotemporal Similarity in Moving Object Databases
      Costas Panagiotakis, Nikos Pelekis, Ioannis Kopanakis
      Pages 131-142
    8. Leveraging Call Center Logs for Customer Behavior Prediction
      Anju G. Parvathy, Bintu G. Vasudevan, Abhishek Kumar, Rajesh Balakrishnan
      Pages 143-154
    9. ART-Based Neural Networks for Multi-label Classification
      Elena P. Sapozhnikova
      Pages 167-177
    10. Two-Way Grouping by One-Way Topic Models
      Eerika Savia, Kai Puolamäki, Samuel Kaski
      Pages 178-189
    11. Incremental Bayesian Network Learning for Scalable Feature Selection
      Grégory Thibault, Alex Aussem, Stéphane Bonnevay
      Pages 202-212

About these proceedings


bayesian networks bioinformatics calculus clustering computer architecture data streams database distance learning gene expression machine learning modeling optimization statistics time series clustering visualization

Editors and affiliations

  • Niall M. Adams
    • 1
  • Céline Robardet
    • 2
  • Arno Siebes
    • 3
  • Jean-François Boulicaut
    • 4
  1. 1.Department of MathematicsImperial College LondonLondonUnited Kingdom
  2. 2.INSA Lyon, LIRIS CNRS UMR 5205, Bâtiment Blaise PascalUniversity of LyonVilleurbanneFrance
  3. 3.Department of Information and Computer ScienceUniversiteit UtrechtUtrechtThe Netherlands
  4. 4.INSA-Lyon, LIRIS CNRS UMR5205University of LyonVilleurbanneFrance

Bibliographic information

  • Copyright Information Springer-Verlag Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-03914-0
  • Online ISBN 978-3-642-03915-7
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349