Parallelizing the buckshot algorithm for efficient document clustering

Authors:
Eric C. Jensen;Steven M. Beitzel;Angelo J. Pilotto;Nazli Goharian;Ophir Frieder
Affiliations:
Illinois Institute of Technology, Chicago, IL;Illinois Institute of Technology, Chicago, IL;Illinois Institute of Technology, Chicago, IL;Illinois Institute of Technology, Chicago, IL;Illinois Institute of Technology, Chicago, IL
Venue:
Proceedings of the eleventh international conference on Information and knowledge management
Year:
2002

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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.