… patterns efficiently. Our goal is to propose a theoretical framework where the expressive power
of clustering systems … Part I of this paper reviews the following issues related to clustering …

… We propose a novel clustering method that is based on physical intuition derived from …
cluster centers. The method has one parameter, determining the scale over which cluster …

… the comparison of clustering algorithms. In this paper, five clustering algorithms taken from
… In this paper, five clustering algorithms taken from the literature are reviewed, assessed and …

… particular problem in urban geography. The new feature in our approach … clustering may
be characterized as transformation of a clustering problem into a problem of pattern recognition. …

… , 2) unsupervised classification (eg, clustering) in which the pattern is assigned to a hitherto
unknown class. Note that the recognition problem here is being posed as a classification or …

… applied to practical problems of decision‐making, pattern recognition, and clustering problems.
This … domain of study; it can be effectively applied in diverse decision‐making problems. …

… logic applications in pattern recognition, classification and clustering problems is presented.
… logic in the fields of pattern recognition, classification and clustering, where it has helped …

… clustering techniques may be found in Ball [ 1 1 ] and Friedman and Rubin [ 121. The clustering
… of cluster interdispersion to cluster intradispersion. It achieves its speed by building one …

… In this paper, we consider the problem of clustering m objects in c clusters. The objects are
… on several clustering problems from the literature as well as several random problems and …

… In this type of problem, we are given a set of feature … cluster (group) “similar” vectors together.
This is known as unsupervised pattern recognition or unsupervised learningor clustering. …