Overview
- First publication focusing specifically on mining complex data
Part of the book series: Studies in Computational Intelligence (SCI, volume 165)
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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.
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Keywords
Table of contents (16 chapters)
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General Aspects of Complex Data
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Rules Extraction
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Graph Data Mining
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Data Clustering
Editors and Affiliations
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
Industry Sectors: Aerospace, Automotive, Biotechnology, Electronics, Energy, Utilities & Environment, Engineering, IT & Software, Oil, Gas & Geosciences, Telecommunications