Introduction to clustering large and high dimensional data / Jacob Kogan.

Format:

Book

Author/Creator:

Kogan, Jacob, 1954-

Language:

English

Subjects (All):

Cluster analysis--Data processing.

Cluster analysis.

Cluster analysis--Computer programs.

Computer algorithms.

Dimensional analysis--Data processing.

Dimensional analysis.

Dimensional analysis--Computer programs.

Physical Description:

1 online resource (223 p.)

Place of Publication:

Cambridge ; New York : Cambridge University Press, 2007.

Language Note:

English

Summary:

This book focuses on a few of the most important clustering algorithms, providing a detailed account of these major models in an information retrieval context. The beginning chapters introduce the classic algorithms in detail, while the later chapters describe clustering through divergences and show recent research for more advanced audiences.

Contents:

Cover; Half-title; Title; Copyright; Dedication; Contents; Foreword; Preface; 1 Introduction and motivation; 2 Quadratic k-means algorithm; 3 BIRCH; 4 Spherical k-means algorithm; 5 Linear algebra techniques; 6 Information theoretic clustering; 7 Clustering with optimization techniques; 8 k-means clustering with divergences; 9 Assessment of clustering results; 10 Appendix: Optimization and linear algebra background; 11 Solutions to selected problems; Bibliography; Index

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

ISBN:

1-107-16544-X

1-280-70994-4

9786610709946

0-511-25698-1

0-511-25590-X

0-511-25748-1

0-511-31960-6

0-511-25647-7

OCLC:

489551293