0
Your cart

Your cart is empty

Books > Computing & IT > Applications of computing > Artificial intelligence

Buy Now

Modern Algorithms of Cluster Analysis (Hardcover, 1st ed. 2018) Loot Price: R5,328
Discovery Miles 53 280
Modern Algorithms of Cluster Analysis (Hardcover, 1st ed. 2018): Slawomir Wierzchon, Mieczyslaw Klopotek

Modern Algorithms of Cluster Analysis (Hardcover, 1st ed. 2018)

Slawomir Wierzchon, Mieczyslaw Klopotek

Series: Studies in Big Data, 34

 (sign in to rate)
Loot Price R5,328 Discovery Miles 53 280 | Repayment Terms: R499 pm x 12*

Bookmark and Share

Expected to ship within 10 - 15 working days

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.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Studies in Big Data, 34
Release date: 2018
First published: 2018
Authors: Slawomir Wierzchon • Mieczyslaw Klopotek
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 421
Edition: 1st ed. 2018
ISBN-13: 978-3-319-69307-1
Categories: Books > Business & Economics > Business & management > Business mathematics & systems > General
Books > Science & Mathematics > Mathematics > Applied mathematics > General
Books > Computing & IT > Applications of computing > Databases > General
Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN: 3-319-69307-7
Barcode: 9783319693071

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!

Partners