Introduction to Clustering Large and High-Dimensional Data

Valutazione media 4
( su 1 valutazioni fornite da GoodReads )
 
9780521852678: Introduction to Clustering Large and High-Dimensional Data

There is a growing need for a more automated system of partitioning data sets into groups, or clusters. For example, digital libraries and the World Wide Web continue to grow exponentially, the ability to find useful information increasingly depends on the indexing infrastructure or search engine. Clustering techniques can be used to discover natural groups in data sets and to identify abstract structures that might reside there, without having any background knowledge of the characteristics of the data. Clustering has been used in a variety of areas, including computer vision, VLSI design, data mining, bio-informatics (gene expression analysis), and information retrieval, to name just a few. 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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Recensione:

"...this book may serve as a useful reference for scientists and engineers who need to understand the concepts of clustering in general and/or to focus on text mining applications. It is also appropriate for students who are attending a course in pattern recognition, data mining, or classification and are interested in learning more about issues related to the k-means scheme for an undergraduate or master's thesis project. Last, it supplies very interesting material for instructors."
Nicolas Loménie, IAPR Newsletter

Descrizione del libro:

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

I migliori risultati di ricerca su AbeBooks

1.

Jacob Kogan
Editore: Cambridge Univ Pr (2007)
ISBN 10: 0521852676 ISBN 13: 9780521852678
Nuovi Rilegato Quantità: 1
Da
Revaluation Books
(Exeter, Regno Unito)
Valutazione libreria
[?]

Descrizione libro Cambridge Univ Pr, 2007. Hardcover. Condizione libro: Brand New. 1st edition. 205 pages. 9.00x6.25x0.75 inches. In Stock. Codice libro della libreria __0521852676

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 58,45
Convertire valuta

Aggiungere al carrello

Spese di spedizione: EUR 6,94
Da: Regno Unito a: U.S.A.
Destinazione, tempi e costi

2.

JACOB KOGAN
ISBN 10: 0521852676 ISBN 13: 9780521852678
Nuovi Rilegato Quantità: 1
Da
Herb Tandree Philosophy Books
(Stroud, GLOS, Regno Unito)
Valutazione libreria
[?]

Descrizione libro 2007. Hardback. Condizione libro: NEW. 9780521852678 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Codice libro della libreria HTANDREE01229107

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 57,34
Convertire valuta

Aggiungere al carrello

Spese di spedizione: EUR 9,25
Da: Regno Unito a: U.S.A.
Destinazione, tempi e costi

3.

Jacob Kogan
Editore: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2006)
ISBN 10: 0521852676 ISBN 13: 9780521852678
Nuovi Rilegato Quantità: 1
Da
The Book Depository
(London, Regno Unito)
Valutazione libreria
[?]

Descrizione libro CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2006. Hardback. Condizione libro: New. 236 x 157 mm. Language: English . Brand New Book. There is a growing need for a more automated system of partitioning data sets into groups, or clusters. For example, digital libraries and the World Wide Web continue to grow exponentially, the ability to find useful information increasingly depends on the indexing infrastructure or search engine. Clustering techniques can be used to discover natural groups in data sets and to identify abstract structures that might reside there, without having any background knowledge of the characteristics of the data. Clustering has been used in a variety of areas, including computer vision, VLSI design, data mining, bio-informatics (gene expression analysis), and information retrieval, to name just a few. 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. Codice libro della libreria AAA9780521852678

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 66,69
Convertire valuta

Aggiungere al carrello

Spese di spedizione: GRATIS
Da: Regno Unito a: U.S.A.
Destinazione, tempi e costi

4.

Jacob Kogan
Editore: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2006)
ISBN 10: 0521852676 ISBN 13: 9780521852678
Nuovi Rilegato Quantità: 1
Da
The Book Depository US
(London, Regno Unito)
Valutazione libreria
[?]

Descrizione libro CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2006. Hardback. Condizione libro: New. 236 x 157 mm. Language: English . Brand New Book. There is a growing need for a more automated system of partitioning data sets into groups, or clusters. For example, digital libraries and the World Wide Web continue to grow exponentially, the ability to find useful information increasingly depends on the indexing infrastructure or search engine. Clustering techniques can be used to discover natural groups in data sets and to identify abstract structures that might reside there, without having any background knowledge of the characteristics of the data. Clustering has been used in a variety of areas, including computer vision, VLSI design, data mining, bio-informatics (gene expression analysis), and information retrieval, to name just a few. 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. Codice libro della libreria AAA9780521852678

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 66,89
Convertire valuta

Aggiungere al carrello

Spese di spedizione: GRATIS
Da: Regno Unito a: U.S.A.
Destinazione, tempi e costi

5.

Kogan, Jacob
Editore: Cambridge University Press (2006)
ISBN 10: 0521852676 ISBN 13: 9780521852678
Nuovi Rilegato Quantità: 1
Da
Booked Again
(Summit, NJ, U.S.A.)
Valutazione libreria
[?]

Descrizione libro Cambridge University Press, 2006. Hardcover. Condizione libro: New. New item. Codice libro della libreria QX-228-67-7707507

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 147,63
Convertire valuta

Aggiungere al carrello

Spese di spedizione: EUR 9,21
In U.S.A.
Destinazione, tempi e costi