Parallelizing the buckshot algorithm for efficient document clustering Eric C. Jensen, Steven M. Beitzel, Angelo J. Pilotto, Nazli Goharian, and Ophir Frieder   View Paper (PDF)   Return to Posters Abstract 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. DiSC'03 © 2003 Association for Computing Machinery