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Mining Complex Data

  • Book
  • © 2009

Overview

Editors:
  1. Djamel A. Zighed

    1. University of Lyon, Lyon, France

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  2. Shusaku Tsumoto

    1. Shimane University, Shimane, Japan

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  3. Zbigniew W. Ras

    1. University of North Carolina, Charlotte, USA

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  4. Hakim Hacid

    1. University of Lyon, Lyon, France

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  • First publication focusing specifically on mining complex data

Part of the book series: Studies in Computational Intelligence (SCI, volume 165)

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Table of contents (16 chapters)

  1. Front Matter

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  2. General Aspects of Complex Data

    1. Front Matter

      Pages 1-1
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    2. Using Layout Data for the Analysis of Scientific Literature

      • Brigitte Mathiak, Andreas Kupfer, Silke Eckstein
      Pages 3-22

    3. Extracting a Fuzzy System by Using Genetic Algorithms for Imbalanced Datasets Classification: Application on Down’s Syndrome Detection

      • Vicenç Soler, Marta Prim
      Pages 23-39

    4. A Hybrid Approach of Boosting Against Noisy Data

      • Emna Bahri, Stephane Lallich, Nicolas Nicoloyannis, Maddouri Mondher
      Pages 41-54

    5. Dealing with Missing Values in a Probabilistic Decision Tree during Classification

      • Lamis Hawarah, Ana Simonet, Michel Simonet
      Pages 55-74

    6. Kernel-Based Algorithms and Visualization for Interval Data Mining

      • Thanh-Nghi Do, François Poulet
      Pages 75-91

  3. Rules Extraction

    1. Front Matter

      Pages 93-93
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    2. Evaluating Learning Algorithms Composed by a Constructive Meta-learning Scheme for a Rule Evaluation Support Method

      • Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
      Pages 95-111

    3. Mining Statistical Association Rules to Select the Most Relevant Medical Image Features

      • Marcela X. Ribeiro, Andre G. R. Balan, Joaquim C. Felipe, Agma J. M. Traina, Caetano Traina Jr.
      Pages 113-131

    4. From Sequence Mining to Multidimensional Sequence Mining

      • Karine Zeitouni
      Pages 133-152

    5. Tree-Based Algorithms for Action Rules Discovery

      • Zbigniew W. RaÅ›, Li-Shiang Tsay, Agnieszka DardziÅ„ska
      Pages 153-163

  4. Graph Data Mining

    1. Front Matter

      Pages 165-165
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    2. Indexing Structure for Graph-Structured Data

      • Stanislav Bartoň, Pavel Zezula
      Pages 167-188

    3. Full Perfect Extension Pruning for Frequent Subgraph Mining

      • Christian Borgelt, Thorsten Meinl
      Pages 189-205

    4. Parallel Algorithm for Enumerating Maximal Cliques in Complex Network

      • Nan Du, Bin Wu, Liutong Xu, Bai Wang, Pei Xin
      Pages 207-221

    5. Community Finding of Scale-Free Network: Algorithm and Evaluation Criterion

      • Sen Qin, Guanzhong Dai
      Pages 223-242

    6. The k-Dense Method to Extract Communities from Complex Networks

      • Kazumi Saito, Takeshi Yamada, Kazuhiro Kazama
      Pages 243-257

  5. Data Clustering

    1. Front Matter

      Pages 259-259
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    2. Efficient Clustering for Orders

      • Toshihiro Kamishima, Shotaro Akaho
      Pages 261-279
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Keywords

About this book

The aim of this book is to gather the most recent works that address issues related to the concept of mining complex data. The whole knowledge discovery process being involved, our goal is to provide researchers dealing with each step of this process by key entries. Actually, managing complex data within the KDD process implies to work on every step, starting from the pre-processing (e.g. structuring and organizing) to the visualization and interpretation (e.g. sorting or filtering) of the results, via the data mining methods themselves (e.g. classification, clustering, frequent patterns extraction, etc.). The papers presented here are selected from the workshop papers held yearly since 2006.

Editors and Affiliations

  • University of Lyon, Lyon, France

    Djamel A. Zighed, Hakim Hacid

  • Shimane University, Shimane, Japan

    Shusaku Tsumoto

  • University of North Carolina, Charlotte, USA

    Zbigniew W. Ras

Bibliographic Information

  • Book Title: Mining Complex Data

  • Editors: Djamel A. Zighed, Shusaku Tsumoto, Zbigniew W. Ras, Hakim Hacid

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-540-88067-7

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2009

  • Hardcover ISBN: 978-3-540-88066-0Published: 13 October 2008

  • Softcover ISBN: 978-3-642-09980-9Published: 28 October 2010

  • eBook ISBN: 978-3-540-88067-7Published: 10 October 2008

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XII, 302

  • Number of Illustrations: 114 b/w illustrations

  • Topics: Mathematical and Computational Engineering, Artificial Intelligence

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