Graph-Based Clustering and Data Visualization Algorithms by Ágnes Vathy-Fogarassy

By Ágnes Vathy-Fogarassy

This paintings provides an information visualization method that mixes graph-based topology illustration and dimensionality aid tips on how to visualize the intrinsic facts constitution in a low-dimensional vector house. the applying of graphs in clustering and visualization has numerous merits. A graph of vital edges (where edges symbolize family and weights signify similarities or distances) offers a compact illustration of the whole complicated facts set. this article describes clustering and visualization equipment which are capable of make the most of details hidden in those graphs, in accordance with the synergistic blend of clustering, graph-theory, neural networks, info visualization, dimensionality aid, fuzzy equipment, and topology studying. The paintings includes a number of examples to assist within the realizing and implementation of the proposed algorithms, supported by means of a MATLAB toolbox to be had at an linked website.

Show description

Read Online or Download Graph-Based Clustering and Data Visualization Algorithms PDF

Similar graph theory books

How to Display Data

Powerful facts presentation is an important ability for anyone wishing to demonstrate or put up learn effects, but if performed badly, it may possibly show a deceptive or complicated message. This new addition to the preferred “How to” sequence explains the way to current information in magazine articles, furnish purposes or examine shows truly, properly and logically, expanding the possibilities of winning booklet.

Matroid theory

The research of matroids is a department of discrete arithmetic with easy hyperlinks to graphs, lattices, codes, transversals, and projective geometries. Matroids are of primary value in combinatorial optimization and their purposes expand into electric engineering and statics. This incisive survey of matroid thought falls into elements: the 1st half offers a complete advent to the fundamentals of matroid concept whereas the second one treats extra complex subject matters.

Graph Colouring and the Probabilistic Method

During the last decade, many significant advances were made within the box of graph coloring through the probabilistic technique. This monograph, through of the easiest at the subject, offers an available and unified remedy of those effects, utilizing instruments comparable to the Lovasz neighborhood Lemma and Talagrand's focus inequality.

Visualization for Computer Security: 5th International Workshop, VizSec 2008, Cambridge, MA, USA, September 15, 2008. Proceedings

This booklet constitutes the refereed lawsuits of the fifth foreign Workshop on Visualization for Cyber protection hung on September 15, 2008, in Cambridge, Massachusetts, united states, along with the eleventh foreign Symposium on contemporary Advances in Intrusion Detection (RAID). The 18 papers offered during this quantity have been rigorously reviewed and chosen from 27 submissions.

Additional resources for Graph-Based Clustering and Data Visualization Algorithms

Sample text

IEEE Trans. Fuzzy Syst. 4, 112–123 (1996) 6. : Some new indexes of cluster validity. IEEE Trans. Syst. Man Cybern. 28, 301–315 (1998) 7. : Algorithm5: a technique for fuzzy similarity clustering of chemical inventories. J. Chem. Inf. Comput. Sci. 36, 1195–1204 (1996) 8. : Well separated clusters and optimal fuzzy partitions. J. Cybern. 4, 95–104 (1974) 9. : On nearest-neighbor graphs. Discrete Comput. Geom. 17, 263–282 (1997) 10. : Minimum spanning tree: ordering edges to identify clustering structure.

A comparison of the stability characteristics of some graph theoretic clustering methods. IEEE Trans. Pattern Anal. Mach. Intell. 3, 393–402 (1980) 25. : The relative neighborhood graph of a finite planar set. Pattern Recogn. 12, 261–268 (1980) 26. : Iterative class discovery and feature selection using Minimal Spanning Trees. BMC Bioinform. 5, 126–134 (2004) 27. : Hybrid minimal spanning tree and mixture of Gaussians based clustering algorithm. In: Lecture Notes in Computer Science: Foundations of Information and Knowledge Systems vol.

Chim. Acta 515, 43–53 (2004) 11. : Voronoi diagrams and delaunay triangulations. K. ), Computing in Euclidean Geometry, pp. 193–223. World Scientific, Singapore (1992) 12. : A new statistical approach to geographic variation analysis. Syst. Zool. 18, 259–278 (1969) 13. : Unsupervised optimal fuzzy clustering. IEEE Trans. Pattern Anal. Mach. Intell. 11, 773–781 (1989) 14. : A clustering procedure based on the comparsion between the k nearest neighbors graph and the minimal spanning tree. Stat. Probab.

Download PDF sample

Rated 4.45 of 5 – based on 35 votes