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Collaborative tagging systems, or folksonomies, have the potential of becoming technological infrastructure to support knowledge management activities in an organization or a society. There are many challenges, however. This paper presents designs that enhance collaborative tagging systems to meet some key challenges: community identification, ontology generation, user and document recommendation. Design prototypes, evaluation methodology and selected preliminary results are presented.

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In this paper, we propose a scheme for matrix-matrix multiplication on a distributedmemory parallel computer. The scheme hides almost all of the communication cost with the computation and uses the standard, optimized Level-3 BLAS operation on each node. As a result, the overall performance of the scheme is nearly equal to the performance of the Level-3 optimized BLAS operation times the number of nodes in the computer, which is the peak performance obtainable for parallel BLAS. Another feature of our algorithm is that it can give peak performance for larger ®Copyright 1994 by International Business Machines Corporation. Copying in printed form for private use is permitted without payment of royalty provided that (1) each reproduction is done without alteration and (2) the