Scalable High Performance Computing for Knowledge Discovery and Data Mining: A Special Issue of Data Mining and Knowledge Discovery Volume 1, No.4 (1997)

by Paul Stolorz (Editor), Ron Musick (Editor)

Overview

Scalable High Performance Computing for Knowledge Discovery and Data Mining brings together in one place important contributions and up-to-date research results in this fast moving area.
Scalable High Performance Computing for Knowledge Discovery and Data Mining serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

Product Details

ISBN-13:	9780792380979
Publisher:	Springer US
Publication date:	01/31/1998
Edition description:	Reprinted from DATA MINING AND KNOWLEDGE DISCOVERY, 1:4, 1998
Pages:	100
Product dimensions:	6.10(w) x 9.25(h) x 0.36(d)

Table of Contents

Guest Editorial; P. Stolorz, R. Musick. Parallel Algorithms for Discovery of Association Rules; M.J. Zaki, S. Parthasarathy, M. Ogihara. A Distributed Algorithm for Content Based Indexing of Images by Projections on Ritz Primary Images; H. Schweitzer. High Performance OLAP and Data Mining on Parallel Computers; S. Goil, A. Choudhary. Halo World: Tools for Parallel Cluster Finding in Astrophysical N-Body Simulations; D.W. Pfitzer, J.K. Salmon, T. Sterling.

Editorial Reviews

This special issue of , v.1, no.4 (1997) features four papers on sophisticated means to cope with information overload, with an editorial by Stolorz (Jet Propulsion Laboratory) and Musick (Lawrence Livermore National Laboratory) on the new interdisciplinary field of Knowledge Discovery in Databases. The focus is on applications of KDD methods on scalable high-performance computing platforms. Each contribution treats a KDD problem involving massive datasets, describes analytic techniques (e.g. association rules, On-Line Analytical Processing) grounded in a particular discipline (such as astrophysical -body simulations), and tests parallel versions of these methods. There appears to be quite a future for meta-supercomputing. No index. Annotation c. by Book News, Inc., Portland, Or.

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