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Advances in Intelligent Data Analysis VI

6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005, Proceedings

  • Conference proceedings
  • © 2005

Overview

Editors:
  1. A. Fazel Famili

    1. Institute for Information Technology, National Research Council Canada, Ottawa, Canada

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  2. Joost N. Kok

    1. LIACS, Leiden University, The Netherlands

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  3. José M. Peña

    1. IFM, Linköping University, Linköping, Sweden

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  4. Arno Siebes

    1. Department of Computer Science, Universiteit Utrecht,  

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  5. Ad Feelders

    1. Utrecht University, TB Utrecht,, the Netherlands

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3646)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: IDA 2005.

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About this book

One of the superb characteristics of Intelligent Data Analysis (IDA) is that it is an interdisciplinary ?eld in which researchers and practitioners from a number of areas are involved in a typical project. This also creates a challenge in which the success of a team depends on the participation of users and domain experts who need to interact with researchers and developers of any IDA system. All this is usually re?ected in successful projects and of course on the papers that were evaluated by this year’s program committee from which the ?nal program has been developed. In our call for papers, we solicited papers on (i) applications and tools, (ii) theory and general principles, and (iii) algorithms and techniques. We received a total of 184 papers, reviewing these was a major challenge. Each paper was assigned to three reviewers. In the end 46 papers were accepted, which are all included in the proceedings and presented at the conference. This year’s papers re?ect the results of applied and theoretical researchfrom a number of disciplines all of which are related to the ?eld of Intelligent Data Analysis. To have the best combination of theoretical and applied research and also provide the best focus, we have divided this year’s IDA program into tu- rials, invited talks, panel discussions and technical sessions.

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Table of contents (46 papers)

  1. Front Matter

    Download chapter PDF

  2. Probabilistic Latent Clustering of Device Usage

    • Jean-Marc Andreoli, Guillaume Bouchard
    Pages 1-11

  3. Condensed Nearest Neighbor Data Domain Description

    • Fabrizio Angiulli
    Pages 12-23

  4. Balancing Strategies and Class Overlapping

    • Gustavo E. A. P. A. Batista, Ronaldo C. Prati, Maria C. Monard
    Pages 24-35

  5. Modeling Conditional Distributions of Continuous Variables in Bayesian Networks

    • Barry R. Cobb, Rafael Rumí, Antonio Salmerón
    Pages 36-45

  6. Kernel K-Means for Categorical Data

    • Julia Couto
    Pages 46-56

  7. Using Genetic Algorithms to Improve Accuracy of Economical Indexes Prediction

    • Óscar Cubo, Víctor Robles, Javier Segovia, Ernestina Menasalvas
    Pages 57-65

  8. A Distance-Based Method for Preference Information Retrieval in Paired Comparisons

    • Esther Dopazo, Jacinto González-Pachón, Juan Robles
    Pages 66-73

  9. Knowledge Discovery in the Identification of Differentially Expressed Genes in Tumoricidal Macrophage

    • A. Fazel Famili, Ziying Liu, Pedro Carmona-Saez, Alaka Mullick
    Pages 74-85

  10. Searching for Meaningful Feature Interactions with Backward-Chaining Rule Induction

    • Doug Fisher, Mary Edgerton, Lianhong Tang, Lewis Frey, Zhihua Chen
    Pages 86-96

  11. Exploring Hierarchical Rule Systems in Parallel Coordinates

    • Thomas R. Gabriel, A. Simona Pintilie, Michael R. Berthold
    Pages 97-108

  12. Bayesian Networks Learning for Gene Expression Datasets

    • Giacomo Gamberoni, Evelina Lamma, Fabrizio Riguzzi, Sergio Storari, Stefano Volinia
    Pages 109-120

  13. Pulse: Mining Customer Opinions from Free Text

    • Michael Gamon, Anthony Aue, Simon Corston-Oliver, Eric Ringger
    Pages 121-132

  14. Keystroke Analysis of Different Languages: A Case Study

    • Daniele Gunetti, Claudia Picardi, Giancarlo Ruffo
    Pages 133-144

  15. Combining Bayesian Networks with Higher-Order Data Representations

    • Elias Gyftodimos, Peter A. Flach
    Pages 145-156

  16. Removing Statistical Biases in Unsupervised Sequence Learning

    • Yoav Horman, Gal A. Kaminka
    Pages 157-167

  17. Learning from Ambiguously Labeled Examples

    • Eyke Hüllermeier, Jürgen Beringer
    Pages 168-179

  18. Learning Label Preferences: Ranking Error Versus Position Error

    • Eyke Hüllermeier, Johannes Fürnkranz
    Pages 180-191

  19. FCLib: A Library for Building Data Analysis and Data Discovery Tools

    • Wendy S. Koegler, W. Philip Kegelmeyer
    Pages 192-203

  20. A Knowledge-Based Model for Analyzing GSM Network Performance

    • Pasi Lehtimäki, Kimmo Raivio
    Pages 204-215
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Other volumes

  1. Advances in Intelligent Data Analysis VI

Editors and Affiliations

  • Institute for Information Technology, National Research Council Canada, Ottawa, Canada

    A. Fazel Famili

  • LIACS, Leiden University, The Netherlands

    Joost N. Kok

  • IFM, Linköping University, Linköping, Sweden

    José M. Peña

  • Department of Computer Science, Universiteit Utrecht,  

    Arno Siebes

  • Utrecht University, TB Utrecht,, the Netherlands

    Ad Feelders

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