New Book: Advances in Knowledge Discovery and Data Mining
R. Uthurusamy
SAMY at gmr.com
Sun Mar 3 21:52:41 EST 1996
New Book Announcement:
Advances in Knowledge Discovery and Data Mining
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Edited by Usama M. Fayyad, Gregory Piatetsky-Shapiro,
Padhraic Smyth, and Ramasamy Uthurusamy
Published by the AAAI Press / The MIT Press ISBN 0-262-56097-6
March 1996 625 pp. Price: $ 50.00
This book can be ordered online from The MIT Press: http://mitpress.mit.edu/
More info at: http://www-mitpress.mit.edu/mitp/recent-books/comp/fayap.html
http://www.aaai.org/Publications/Press/Catalog/fayyad.html
(This AAAI website also has abstracts of chapters)
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"Advances in Knowledge Discovery and Data Mining" brings together the latest
research -- in statistics, databases, machine learning, and artificial
intelligence -- that are part of the exciting and rapidly growing field of
Knowledge Discovery and Data Mining. Topics covered include fundamental
issues, classification and clustering, trend and deviation analysis,
dependency modeling, integrated discovery systems, next generation database
systems, and application case studies. The contributors include leading
researchers and practitioners from academia, government laboratories, and
private industry.
The last decade has seen an explosive growth in the generation and
collection of data. Advances in data collection, widespread use of bar codes
for most commercial products, and the computerization of many business and
government transactions have flooded us with data and generated an urgent
need for new techniques and tools that can intelligently and automatically
assist in transforming this data into useful knowledge. This book is a
timely and comprehensive overview of the new generation of techniques and
tools for knowledge discovery in data.
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Contents
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Foreword: On the Barriers and Future of Knowledge Discovery / vii
Gio Wiederhold
Preface / xiii
Chapter 1: From Data Mining to Knowledge Discovery: An Overview / 1
Usama M. Fayyad, Gregory Piatetsky-Shapiro, and Padhraic Smyth
Part I: Foundations
Chapter 2: The Process of Knowledge Discovery in Databases:
A Human-Centered Approach
Ronald J. Brachman and Tej Anand / 37
Chapter 3: Graphical Models for Discovering Knowledge
Wray Buntine / 59
Chapter 4: A Statistical Perspective on Knowledge Discovery in Databases
John Elder IV and Daryl Pregibon / 83
Part II Classification and Clustering
Chapter 5: Inductive Logic Programming and Knowledge Discovery in
Databases
Saso Dzeroski / 117
Chapter 6: Bayesian Classification (AutoClass): Theory and Results
Peter Cheeseman and John Stutz / 153
Chapter 7: Discovering Informative Patterns and Data Cleaning
Isabelle Guyon, Nada Matic, and Vladimir Vapnik / 181
Chapter 8: Transforming Rules and Trees into Comprehensible Knowledge
Structures
Brian R. Gaines / 205
Part III Trend and Deviation Analysis
Chapter 9: Finding Patterns in Time Series: A Dynamic Programming Approach
Donald J. Berndt and James Clifford / 229
Chapter 10: Explora: A Multipattern and Multistrategy Discovery Assistant
Willi Kloesgen / 249
Part IV Dependency Derivation
Chapter 11: Bayesian Networks for Knowledge Discovery
David Heckerman / 273
Chapter 12: Fast Discovery of Association Rules
Rakesh Agrawal, Heikki Mannila, Ramakrishnan Srikant,
Hannu Toivonen, and A. Inkeri Verkamo / 307
Chapter 13: From Contingency Tables to Various Forms of Knowledge in
Databases
Robert Zembowicz and Jan M. Zytkow / 329
Part V Integrated Discovery Systems
Chapter 14: Integrating Inductive and Deductive Reasoning for Data Mining
Evangelos Simoudis, Brian Livezey, and Randy Kerber / 353
Chapter 15: Metaqueries for Data Mining
Wei-Min Shen, KayLiang Ong, Bharat Mitbander, and
Carlo Zaniolo / 375
Chapter 16: Exploration of the Power of Attribute-Oriented Induction in
Data Mining
Jiawei Han and Yongjian Fu / 399
Part VI Next Generation Database Systems
Chapter 17: Using Inductive Learning To Generate Rules for Semantic
Query Optimization
Chun-Nan Hsu and Craig A. Knoblock / 425
Chapter 18: Data Surveyor: Searching the Nuggets in Parallel
Marcel Holsheimer, Martin L. Kersten, and
Arno P.J.M. Siebes / 447
Part VII KDD Applications
Chapter 19: Automating the Analysis and Cataloging of Sky Surveys
Usama M. Fayyad, S. George Djorgovski, and Nicholas Weir / 471
Chapter 20: Selecting and Reporting What is Interesting: The KEFIR
Application to Healthcare Data
Christopher J. Matheus, Gregory Piatetsky-Shapiro, and
Dwight McNeill / 495
Chapter 21: Modeling Subjective Uncertainty in Image Annotation
Padhraic Smyth, Usama M. Fayyad, Michael C. Burl, and
Pietro Perona / 517
Chapter 22: Predicting Equity Returns from Securities Data with Minimal
Rule Generation
Chidanand Apte and Se June Hong / 541
Chapter 23: From Data Mining to Knowledge Discovery: Current Challenges
and Future Directions
Ramasamy Uthurusamy / 561
Part VIII Appendices
Knowledge Discovery in Databases Terminology
Willi Kloesgen and Jan M. Zytkow / 573
Data Mining and Knowledge Discovery Internet Resources
Gregory Piatetsky-Shapiro / 593
About The Editors / 597
Index / 601
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For Additional Information contact:
American Association for Artificial Intelligence (AAAI)
445 Burgess Drive, Menlo Park, California 94025-3496 USA
Telephone: 415-328-3123 / Fax: 415-321-4457 / Email: info at aaai.org
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