Knowledge discovery and data mining – Brief Article
KDD-98–New York, New York
Proceedings of the Fourth International
Conference on Knowledge Discovery and Data
Mining
Edited by Rakesh Agrawal, Paul Stolorz, and
Gregory Piatetsky-Shapiro
As an interdisciplinary field, KDD has made important strides
by generating cross-fertilization of ideas between individual
disciplines.
In keeping with this theme, KDD-98 was collocated
with the Conference on Very Large Databases with the goal of
catalyzing discussions and interactions between researchers in
the two fields. Paper topics in this proceedings include theory
and foundational issues in KDD, data mining methods and
algorithms, database-centric data mining, and KDD process and
human interaction applications.
ISBN 1-57735-070-7 392 pp., index, $75.00 softcover
KDD-97–Newport Beach, California
Proceedings of the Third International
Conference on Knowledge Discovery and Data
Mining
Edited by David Heckerman, Heikki Mannila,
Daryl Pregibon, and Ramasamy Uthurusamy
The rapid growth of data and information has created a need
and an opportunity for extracting knowledge from databases,
and researchers and application developers have been responding
to that need. The papers in this volume reflect the research
in knowledge discovery in databases (KDD)–also referred to as
“data mining”–being conducted by researchers in machine
discovery, statistics, databases, knowledge acquisition, machine
learning, data visualization, high performance computing, and
knowledge-based systems and describe KDD applications in
areas such as astronomy, biology, finance, insurance, marketing,
and medicine.
ISBN 1-57735-027-8 320 pp., index, $75.00 softcover
KDD-96—Portland, Oregon
Proceedings of the Second International
Conference on Knowledge Discovery and Data
Mining
Edited by Evangelos Simoudis, Jiawei Han, and
Usama Fayyad
Responding to the need to turn their rapidly expanding data
stores into accessible and actionable knowledge, researchers
from fields such as pattern recognition, statistics, artificial
intelligence, very large databases, and visualization are developing
tools and techniques to discover knowledge from large, complex
data stores. These researchers share a set of core issues:
representation of discovered knowledge, search complexity, the use
of prior knowledge, statistical inference, algorithms that scale to
analysis of massive amounts of data both in size and dimensionality,
managing uncertainty, and interactive (human-oriented)
presentation. The papers in this proceedings represent the current
state of the art and state of practice in each of the various
disciplines comprising KDD.
ISBN 1-57735-004-9 405 pp., index, $75.00 softcover
KDD-95–Montreal, Quebec
Proceedings of the First International
Conference on Knowledge Discovery and Data
Mining
Edited by Usama Fay)ad and Ramasamy Uthurusamy
The papers in this proceedings focus on unifying themes such as
the use of domain knowledge, managing uncertainty, interactive
(human-oriented) presentation, and applications.
ISBN 0-929280-82-2 359 pp., index, $75.00 softcover
COPYRIGHT 2001 American Association for Artificial Intelligence
COPYRIGHT 2002 Gale Group