Data Mining for Scientific and Engineering Applications
Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists
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Data Mining for Scientific and Engineering Applications Edited by
Robert L. Grossman University of Illinois, Chicago
Chandrika Kamath Lawrence Livermore National Laboratory, Livermore
Philip Kegelmeyer Sandia National Laboratories, Livermore
Vipin Kumar Army High Performance Computing Research Center (AHPCRC), Minneapolis and
Raju R. Namburu Army Research Laboratory, Aberdeen Proving Ground
SPRINGER SCIENCE+BUSINESS MEDIA, B.V.
A C.LP. Catalogue record for this book is available from the Library of Congress.
ISBN 978-1-4020-0114-7 ISBN 978-1-4615-1733-7 (eBook) DOI 10.1007/978-1-4615-1733-7
Printed on acid-free paper
A l l Rights Reserved © 2001 Springer Science+Business Media Dordrecht Originally published by Kluwer Academic Publishers in 2001 Softcover reprint of the hardcover 1st edition 2001 No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without written permission from the copyright owner.
Table of Contents Foreword
.ix
List of Contributors
xi
List of Reviewers
xvii
Preface
xix
1
ON MINING SCIENTIFIC DATASETS Chandrika Kamath
2
1
UNDERSTANDING HIGH DIMENSIONAL AND LARGE DATA SETS: SOME MATHEMATICAL CHALLENGES AND OPPORTUNITIES Jagdish Chandra
3
23
DATA MINING AT THE INTERFACE OF COMPUTER SCIENCE AND STATISTICS Padhraic Smyth
4
35
MINING LARGE IMAGE COLLECTIONS Michael C. BurL
5
63
MINING ASTRONOMICAL DATABASES Roberta M. Humphreys, Juan E. Cabanela, and Jeffrey Kriessler.
6
SEARCHING FOR BENT-DOUBLE GALAXIES IN THE FIRST SURVEY Chandrika Kamath, Erick Cantu-Paz, Imola K. Fodor, and Nu Ai Tang
7
85
A DATASPACE INFRASTRUCTURE FOR ASTRONOMICAL DATA v
95
Robert Grossman, Emory Creel, Marco Mazzucco, and Roy Williams
8
115
DATA MINING APPLICATIONS IN BIOINFORMATICS Naren Ramakrishnan and Ananth Y. Grama
9 10
125
MINING RESIDUE CONTACTS IN PROTEINS Mohammed J. Zaki and Chris Bystroff..
141
KDD SERVICES AT THE GODDARD EARTH SCIENCES DISTRIBUTED ARCmVE CENTER Christopher Lynnes and Robert Mack
11
165
DATA MINING IN INTEGRATED DATA ACCESS AND DATA ANALYSIS SYSTEMS Ruixin Yang, Menas Kafatos, Kwang-Su Yang, and X. Sean Wang
12
183
SPATIAL DATA MINING FOR CLASSIFICATION, VISUALISATION AND INTERPRETATION WITH ARTMAPNEURALNETWORK Weiguo Liu, Sucharita Gopal, and Curtis Woodcock
13
REAL TIME FEATURE EXTRACTION FOR THE ANALYSIS OF TURBULENT FLOWS I. Marusic, G.V. Candler, V. Interrante, P.K. Subbareddy, and A. Moss
14
239
EVITA-EFFICIENT VISUALIZATION AND INTERROGATION OF TERA-SCALE DATA Raghu Machiraju, hmes E. Fowler, David Thompson, Bharat Soni, and Will Schroeder.
16
223
DATA MINING FOR TURBULENT FLOWS Eui-Hong (Sam) Han, George Karypis, and Vipin Kumar.
15
201
TOWARDS UBIQUITOUS MINING OF VI
257
DISTRIBUTED DATA Hillol Kargupta, Krishnamoorthy Sivakumar, Weiyun Huang, Rajeev Ayyagari, Rong Chen, Byung-Hoon Park, and Erik Johnson
17
281
DECOMPOSABLE ALGORITHMS FOR DATA
