Given n points in d-dimensional space, the goal of hierarchical clustering is to create asequenceofnestedpartitions,whichcanbeconvenientlyvisualized via a tree or hierarchy of clusters, also called the cluster dendogram. Theclustersinthehierarchy range from the fine-grained to the coarse

Hierarchical clustering is a common method used to determine clusters of similar data points in multidimensional spaces. O(n 2 ) algorithms are known for this problem [3, 4, 10, 18]. This paper reviews important results for sequential algorithms and describes previous work on parallel algorithms

Given n points in d-dimensional space, the goal of hierarchical clustering is to create asequenceofnestedpartitions,whichcanbeconvenientlyvisualized via a tree or hierarchy of clusters, also called the cluster dendogram. Theclustersinthehierarchy range from the fine-grained to the coarse

Abstract — Clustering techniques have a wide use and importance nowadays. This importance tends to increase as the amount of data grows and the processing power of the computers increases. Clustering applications are used extensively in various fields such as artificial intelligence, pattern

In this contribution I present current results on how galaxies, groups, clusters and superclusters cluster at low (z1) redshifts. I also discuss the measured and expected clustering evolution. In a program to study the clustering properties of small galaxy structures we have identified close

A structure–odour relationship study using EVA descriptors and

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algorithm to assess the reliability of

Fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. In particular, hierarchical clustering solutions provide a view of the data

to determine characteristics of the environment or detect an event. The communication or message passing process must be designed to conserve the Hmited energy resources of the sensors. Clustering sensors into groups, so that sensors communicate information only to clusterheads and then the clusterheads