Graph-Based Clustering and Data Visualization Algorithms

Buch | Softcover
110 Seiten
2013
Springer London Ltd (Verlag)
978-1-4471-5157-9 (ISBN)

Lese- und Medienproben

Graph-Based Clustering and Data Visualization Algorithms - Ágnes Vathy-Fogarassy, János Abonyi
64,19 inkl. MwSt
This work presents a data visualization technique that combines graph-based topology representation and dimensionality reduction methods to visualize the intrinsic data structure in a low-dimensional vector space. The application of graphs in clustering and visualization has several advantages. A graph of important edges (where edges characterize relations and weights represent similarities or distances) provides a compact representation of the entire complex data set. This text describes clustering and visualization methods that are able to utilize information hidden in these graphs, based on the synergistic combination of clustering, graph-theory, neural networks, data visualization, dimensionality reduction, fuzzy methods, and topology learning. The work contains numerous examples to aid in the understanding and implementation of the proposed algorithms, supported by a MATLAB toolbox available at an associated website.

Vector Quantisation and Topology-Based Graph Representation.- Graph-Based Clustering Algorithms.- Graph-Based Visualisation of High-Dimensional Data.

Erscheint lt. Verlag 5.6.2013
Reihe/Serie SpringerBriefs in Computer Science
Zusatzinfo 62 Illustrations, black and white; XIII, 110 p. 62 illus.
Verlagsort England
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Informatik Software Entwicklung User Interfaces (HCI)
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik Graphentheorie
ISBN-10 1-4471-5157-7 / 1447151577
ISBN-13 978-1-4471-5157-9 / 9781447151579
Zustand Neuware
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