… agglomerative methods stand out as particularly effective and popular approaches for clustering
… regarding the important issue of false positives while searching for clusters. A model of …

… Existing scalable hierarchical clustering methods sacrifice quality for speed and often … of
clusters. In this paper, we present a scalable, agglomerative method for hierarchical clustering …

… In addition to arguing for intrinsic interesting properties of multisetbased similarity approaches,
the present work describes a respectively based hierarchical agglomerative clustering …

… It uses a greedy algorithm for clustering nodes hierarchically ; groups are formed by … are
dense connections within clusters, but only sparse connections between clusters ; a robustness …

… process of assigning cluster memberships and re-estimating cluster parameters. … clusters
are combined using hierarchical agglomerative clustering [7], as long as the combined clusters …

… benefits and costs will drive a group of firms first move away from the agglomeration … of
agglomeration effects which is different from the agglomeration asymmetry of being in the cluster …

… A general algorithm for agglomerative clustering is as follows. … Hierarchical agglomerative
clustering The first parameter required by this algorithm is the number of clusters which is set …

… Abstract—In this work, we revisit fast dimension reduction approaches… agglomerative
clustering that is well suited to perform the feature grouping. This clustering algorithm finds clusters …

… model of agglomeration and trade that … the agglomeration process, (ii) a fullfledged
forward-looking analysis of the role of history and expectations in the emergence of economic …

… agglomeration economies in the Sheffield metals cluster wherein Marshall discovered them.
Despite the cluster's … underlying Marshallian agglomeration economies continue to occur …