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Clustering High--Dimensional Data : First International Workshop, CHDD 2012, Naples, Italy, May 15, 2012, Revised Selected Papers / edited by Francesco Masulli, Alfredo Petrosino, Stefano Rovetta.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Masulli, F. (Francesco), Editor.
Petrosino, Alfredo, Editor.
Rovetta, Stefano, Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 7627
Information Systems and Applications, incl. Internet/Web, and HCI ; 7627
Language:
English
Subjects (All):
Database management.
Application software.
Artificial intelligence.
Information storage and retrieval systems.
Data mining.
Algorithms.
Database Management.
Computer and Information Systems Applications.
Artificial Intelligence.
Information Storage and Retrieval.
Data Mining and Knowledge Discovery.
Local Subjects:
Database Management.
Computer and Information Systems Applications.
Artificial Intelligence.
Information Storage and Retrieval.
Data Mining and Knowledge Discovery.
Algorithms.
Physical Description:
1 online resource (IX, 149 pages) : 41 illustrations in color.
Edition:
1st ed. 2015.
Contained In:
Springer Nature eBook
Place of Publication:
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2015.
System Details:
text file PDF
Summary:
This book constitutes the proceedings of the International Workshop on Clustering High-Dimensional Data, CHDD 2012, held in Naples, Italy, in May 2012. The 9 papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with the general subject and issues of high-dimensional data clustering; present examples of techniques used to find and investigate clusters in high dimensionality; and the most common approach to tackle dimensionality problems, namely, dimensionality reduction and its application in clustering. .
Other Format:
Printed edition:
ISBN:
978-3-662-48577-4
9783662485774
Access Restriction:
Restricted for use by site license.

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