Data Mining: Foundations and Intelligent Paradigms

Volume 1: Clustering, Association and Classification
Herausgegeben:Holmes, Dawn E.; Jain, Lakhmi C

• Broschiertes Buch

Produktbeschreibung

There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled "DATA MINING: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification" we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.

Produktdetails

• Intelligent Systems Reference Library 23
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 978-3-642-43093-0
• 2012
• Seitenzahl: 352
• Erscheinungstermin: 26. Januar 2014
• Englisch
• Abmessung: 235mm x 155mm x 20mm
• Gewicht: 534g
• ISBN-13: 9783642430930
• ISBN-10: 3642430937
• Artikelnr.: 40085644

Inhaltsangabe

Introductory Chapter.- Clustering Analysis in Large Graphs with Rich Attributes.- Temporal Data Mining: Similarity-Profiled Association Pattern.- Bayesian Networks with Imprecise Probabilities: Theory and Application to Classification.- Hierarchical Clustering for Finding Symmetries and Other Patterns in Massive, High Dimensional Datasets.- Randomized Algorithm of Finding the True Number of Clusters Based on Chebychev Polynomial Approximation.- Bregman Bubble Clustering: A Robust Framework for Mining Dense Clusters.- DepMiner: A method and a system for the extraction of significant dependencies.- Integration of Dataset Scans in Processing Sets of Frequent Itemset Queries.- Text Clustering with Named Entities: A Model, Experimentation and Realization.- Regional Association Rule Mining and Scoping from Spatial Data.- Learning from Imbalanced Data: Evaluation Matters.