Introduction to Clustering Large and High Dimensional Data pdf
Introduction to Clustering Large and High Dimensional Data pdf
Introduction to Clustering Large and High Dimensional Data.cJacob Kogan
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Author: Jacob Kogan
Page Count: 222 pages
Published Date: 30 Nov 2006
Publisher: CAMBRIDGE UNIVERSITY PRESS
Publication Country: Cambridge, United Kingdom
Language: English
ISBN: 9780521617932
File size: 30 Mb
File Name: Introduction.to.Clustering.Large.and.High.Dimensional.Data.pdf
Download Link: 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.
Read online Introduction to Clustering Large and High Dimensional Data Buy and read online Introduction to Clustering Large and High Dimensional Data Download and read Introduction to Clustering Large and High Dimensional Data for pc, mac, kindle, readers Download to iPad/iPhone/iOS, B&N nook Introduction to Clustering Large and High Dimensional Data
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Introduction to Clustering Large and High Dimensional Data.cJacob Kogan
Author: Jacob Kogan
Page Count: 222 pages
Published Date: 30 Nov 2006
Publisher: CAMBRIDGE UNIVERSITY PRESS
Publication Country: Cambridge, United Kingdom
Language: English
ISBN: 9780521617932
File size: 30 Mb
File Name: Introduction.to.Clustering.Large.and.High.Dimensional.Data.pdf
Download Link: 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.
Read online Introduction to Clustering Large and High Dimensional Data Buy and read online Introduction to Clustering Large and High Dimensional Data Download and read Introduction to Clustering Large and High Dimensional Data for pc, mac, kindle, readers Download to iPad/iPhone/iOS, B&N nook Introduction to Clustering Large and High Dimensional Data
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