Mining Complex Data

Buch | Hardcover
XII, 302 Seiten
2008 | 2009
Springer Berlin (Verlag)
978-3-540-88066-0 (ISBN)

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Mining Complex Data -
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This is the first book focusing specifically on mining complex data. The papers collected in it were selected from workshop papers presented annually since 2006 and address issues dealing with each step of the mining data process.

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.

General Aspects of Complex Data.- Using Layout Data for the Analysis of Scientific Literature.- Extracting a Fuzzy System by Using Genetic Algorithms for Imbalanced Datasets Classification: Application on Down's Syndrome Detection.- A Hybrid Approach of Boosting Against Noisy Data.- Dealing with Missing Values in a Probabilistic Decision Tree during Classification.- Kernel-Based Algorithms and Visualization for Interval Data Mining.- Rules Extraction.- Evaluating Learning Algorithms Composed by a Constructive Meta-learning Scheme for a Rule Evaluation Support Method.- Mining Statistical Association Rules to Select the Most Relevant Medical Image Features.- From Sequence Mining to Multidimensional Sequence Mining.- Tree-Based Algorithms for Action Rules Discovery.- Graph Data Mining.- Indexing Structure for Graph-Structured Data.- Full Perfect Extension Pruning for Frequent Subgraph Mining.- Parallel Algorithm for Enumerating Maximal Cliques in Complex Network.- Community Finding of Scale-Free Network: Algorithm and Evaluation Criterion.- The k-Dense Method to Extract Communities from Complex Networks.- Data Clustering.- Efficient Clustering for Orders.- Exploring Validity Indices for Clustering Textual Data.

Erscheint lt. Verlag 13.10.2008
Reihe/Serie Studies in Computational Intelligence
Zusatzinfo XII, 302 p. 114 illus.
Verlagsort Berlin
Sprache englisch
Maße 155 x 235 mm
Gewicht 637 g
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik Angewandte Mathematik
Technik
Schlagworte algorithms • classification • Clustering • Complex Data • Computational Intelligence • Databases • Data Mining • Decision Tree • extension • fuzzy system • Genetic algorithms • Heterogeneous Data • Information Retrieval • Kernel • Knowledge • Knowledge Discovery • Layout • learning • similarity measures • Statistics • Visualization
ISBN-10 3-540-88066-6 / 3540880666
ISBN-13 978-3-540-88066-0 / 9783540880660
Zustand Neuware
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