Journal
SCIENCE
Volume 344, Issue 6191, Pages 1492-1496Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.1242072
Keywords
-
Categories
Funding
- grant Associazione Italiana per la Ricerca sul Cancro 5 per mille [12214]
- Fondo per gli Investimenti della Ricerca di Base-Accordo di programma [RBAP11ETKA]
Ask authors/readers for more resources
a Cluster analysis is aimed at classifying elements into categories on the basis of their similarity. Its applications range from astronomy to bioinformatics, bibliometrics, and pattern recognition. We propose an approach based on the idea that cluster centers are characterized by a higher density than their neighbors and by a relatively large distance from points with higher densities. This idea forms the basis of a clustering procedure in which the number of clusters arises intuitively, outliers are automatically spotted and excluded fromthe analysis, and clusters are recognized regardless of their shape and of the dimensionality of the space inwhich they are embedded. We demonstrate the power of the algorithm on several test cases.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available