Parallelizing the buckshot algorithm for efficient document clustering
Eric C. Jensen, Steven M. Beitzel, Angelo J. Pilotto, Nazli Goharian, Ophir Frieder · 2002
We present a parallel implementation of the Buckshot document clustering algorithm. We demonstrate that this parallel approach is highly efficient both in terms of load balancing and minimization of communication. In a series of experiments using the 2GB of SGML data from TReC disks 4 and 5, our parallel approach was shown to be scalable in terms of processors efficiently used and the number of clusters created.