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zighed djamel a. (curatore); tsumoto shusaku (curatore); ras zbigniew w. (curatore); hacid hakim (curatore) - mining complex data

Mining Complex Data

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Dettagli

Genere:Libro
Lingua: Inglese
Pubblicazione: 10/2008
Edizione: 2009





Trama

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.





Sommario

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.










Altre Informazioni

ISBN:

9783540880660

Condizione: Nuovo
Collana: Studies in Computational Intelligence
Dimensioni: 235 x 155 mm
Formato: Copertina rigida
Illustration Notes:XII, 302 p. 114 illus.
Pagine Arabe: 302
Pagine Romane: xii


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