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Other titles in the Intelligent Systems Reference Library series:

Intelligent Systems Reference Library #23: Data Mining: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification

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Intelligent Systems Reference Library #23: Data Mining: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification Cover

 

Synopses & Reviews

Publisher Comments:

Data mining is one of the most rapidly growing research areas in computer science and statistics. In Volume 1of this three volume series, we have brought together contributions from some of the most prestigious researchers in the fundamental data mining tasks of clustering, association and classification. Each of the chapters is self contained. Theoreticians and applied scientists/ engineers will find this volume valuable. Additionally, it provides a sourcebook for graduate students interested in the current direction of research in these aspects of data mining.

Synopsis:

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.

Table of Contents

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.

Product Details

ISBN:
9783642231650
Author:
Holmes, Dawn E. (edt)
Publisher:
Springer
Author:
Jain, Lakhmi C.
Author:
Holmes, Dawn E.
Subject:
Artificial Intelligence
Subject:
Computational intelligence
Subject:
Data mining
Subject:
Intelligent Paradigms
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
Computers-Reference - General
Copyright:
Edition Description:
2012
Series:
Intelligent Systems Reference Library
Series Volume:
Volume 1: Clustering
Publication Date:
20111021
Binding:
HARDCOVER
Language:
English
Pages:
352
Dimensions:
235 x 155 mm

Related Subjects

Business » Business Plans
Business » General
Business » Management
Business » Writing
Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Science and Mathematics » Chemistry » Organic

Intelligent Systems Reference Library #23: Data Mining: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification New Hardcover
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Product details 352 pages Springer - English 9783642231650 Reviews:
"Synopsis" by , 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.
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