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Knowledge Discovery in Inductive Databases

5th International Workshop, KDID 2006 Berlin, Germany, September 18th, 2006 Revised Selected and Invited Papers

  • Conference proceedings
  • © 2007

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Overview

Editors:
  1. Sašo Džeroski
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    You can also search for this editor in PubMed   Google Scholar

  2. Jan Struyf
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4747)

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: KDID 2006.

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Keywords

Table of contents (16 papers)

  1. Front Matter

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  3. Contributed Papers

    1. Mining Bi-sets in Numerical Data

      • Jérémy Besson, Céline Robardet, Luc De Raedt, Jean-François Boulicaut
      Pages 11-23
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    2. Extending the Soft Constraint Based Mining Paradigm

      • Stefano Bistarelli, Francesco Bonchi
      Pages 24-41
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    3. On Interactive Pattern Mining from Relational Databases

      • Francesco Bonchi, Fosca Giannotti, Claudio Lucchese, Salvatore Orlando, Raffaele Perego, Roberto Trasarti
      Pages 42-62
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    4. Analysis of Time Series Data with Predictive Clustering Trees

      • Sašo Džeroski, Valentin Gjorgjioski, Ivica Slavkov, Jan Struyf
      Pages 63-80
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    5. Integrating Decision Tree Learning into Inductive Databases

      • Élisa Fromont, Hendrik Blockeel, Jan Struyf
      Pages 81-96
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    6. Using a Reinforced Concept Lattice to Incrementally Mine Association Rules from Closed Itemsets

      • Arianna Gallo, Rosa Meo
      Pages 97-115
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    7. An Integrated Multi-task Inductive Database VINLEN: Initial Implementation and Early Results

      • Kenneth A. Kaufman, Ryszard S. Michalski, Jarosław Pietrzykowski, Janusz Wojtusiak
      Pages 116-133
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    8. Beam Search Induction and Similarity Constraints for Predictive Clustering Trees

      • Dragi Kocev, Jan Struyf, Sašo Džeroski
      Pages 134-151
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    9. Frequent Pattern Mining and Knowledge Indexing Based on Zero-Suppressed BDDs

      • Shin-ichi Minato, Hiroki Arimura
      Pages 152-169
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    10. Extracting Trees of Quantitative Serial Episodes

      • Mirco Nanni, Christophe Rigotti
      Pages 170-188
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    11. IQL: A Proposal for an Inductive Query Language

      • Siegfried Nijssen, Luc De Raedt
      Pages 189-207
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    12. Mining Correct Properties in Incomplete Databases

      • François Rioult, Bruno Crémilleux
      Pages 208-222
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    13. Efficient Mining Under Rich Constraints Derived from Various Datasets

      • Arnaud Soulet, Jiří Kléma, Bruno Crémilleux
      Pages 223-239
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    14. Three Strategies for Concurrent Processing of Frequent Itemset Queries Using FP-Growth

      • Marek Wojciechowski, Krzysztof Galecki, Krzysztof Gawronek
      Pages 240-258
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  4. Discussion Paper

    1. Towards a General Framework for Data Mining

      • Sašo Džeroski
      Pages 259-300
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  5. Back Matter

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Other volumes

  1. Knowledge Discovery in Inductive Databases

Bibliographic Information

  • Book Title: Knowledge Discovery in Inductive Databases

  • Book Subtitle: 5th International Workshop, KDID 2006 Berlin, Germany, September 18th, 2006 Revised Selected and Invited Papers

  • Editors: Sašo Džeroski, Jan Struyf

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-540-75549-4

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2007

  • Softcover ISBN: 978-3-540-75548-7Published: 07 November 2007

  • eBook ISBN: 978-3-540-75549-4Published: 29 September 2007

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: X, 301

  • Topics: Data Structures and Information Theory, Database Management, Artificial Intelligence

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