منابع مشابه
Hierarchical Adaptive Clustering
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Clustering of data has numerous applications and has been studied extensively. It is very important in Bioinformatics and data mining. Though many parallel algorithms have been designed, most of algorithms use the CRCW-PRAM or CREW-PRAM models of computing. This paper proposed a parallel EREW deterministic algorithm for hierarchical clustering. Based on algorithms of complete graph and Euclidea...
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In many applications of clustering (for example, ontologies or clusterings of animal or plant species), hierarchical clusterings are more descriptive than a flat clustering. A hierarchical clustering over n elements is represented by a rooted binary tree with n leaves, each corresponding to one element. The subtrees rooted at interior nodes capture the clusters. In this paper, we study active l...
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One of the most important issues in urban planning is developing sustainable public transportation. The basic condition for this purpose is analyzing current condition especially based on data. Data mining is a set of new techniques that are beyond statistical data analyzing. Clustering techniques is a subset of it that one of it’s techniques used for analyzing passengers’ trip. The result of...
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ژورنال
عنوان ژورنال: Informatica
سال: 2008
ISSN: 0868-4952,1822-8844
DOI: 10.15388/informatica.2008.204