Modern algorithms of cluster analysis / Sławomir T. Wierzchoń, Mieczysław A. Kłopotek.
2018
QA278
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Can lend chapters, not whole ebooks
Details
Title
Modern algorithms of cluster analysis / Sławomir T. Wierzchoń, Mieczysław A. Kłopotek.
ISBN
9783319693088 (electronic book)
3319693085 (electronic book)
3319693077
9783319693071
3319693085 (electronic book)
3319693077
9783319693071
Publication Details
Cham : Springer, 2018.
Language
English
Description
1 online resource.
Call Number
QA278
Dewey Decimal Classification
519.5/3
Summary
This book provides the reader with a basic understanding of the formal concepts of the cluster, clustering, partition, cluster analysis etc. The book explains feature-based, graph-based and spectral clustering methods and discusses their formal similarities and differences. Understanding the related formal concepts is particularly vital in the epoch of Big Data; due to the volume and characteristics of the data, it is no longer feasible to predominantly rely on merely viewing the data when facing a clustering problem. Usually clustering involves choosing similar objects and grouping them together. To facilitate the choice of similarity measures for complex and big data, various measures of object similarity, based on quantitative (like numerical measurement results) and qualitative features (like text), as well as combinations of the two, are described, as well as graph-based similarity measures for (hyper) linked objects and measures for multilayered graphs. Numerous variants demonstrating how such similarity measures can be exploited when defining clustering cost functions are also presented. In addition, the book provides an overview of approaches to handling large collections of objects in a reasonable time. In particular, it addresses grid-based methods, sampling methods, parallelization via Map-Reduce, usage of tree-structures, random projections and various heuristic approaches, especially those used for community detection.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (viewed January 10, 2018).
Added Author
Kłopotek, Mieczysław A., author.
Series
Studies in big data ; v. 34.
Available in Other Form
Print version: 9783319693071
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