Mining Complex Data

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.

• Extension
• algorithms
• classification
• clustering
• computational intelligence
• data mining
• decision tree
• fuzzy system
• genetic algorithms
• kernel
• knowledge
• knowledge discovery
• layout
• learning
• visualization

• 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

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