|
Editorial
by Usama Fayyad (available in PDF
and Postscript
formats or HTML)
Chair's Message by
Won Kim (available in PDF
and Postscript
formats)
Conference
Reports
Behind-the-Scenes Data Mining by
George H. John
(available in PDF
and Postscript
formats)
ABSTRACT:Successful
technology becomes invisible. Few people think much about internal
combustion engines while they drive to work in three-thousand-pound hunks
of metal powered by them, or electricity while it enables countless parts
of their modern lives. Data mining has a long way to go before it
succeeds in this way -- or does it? At KDD-98, the Behind-the-Scenes
Data Mining panel presented five views on this aspect of the success of
data mining. George H. John, Data Mining Guru at E.piphany, moderated the
panel which included Usama Fayyad, Senior Researcher at Microsoft; Elliot
Fishman, Director of Product Management at DoubleClick; Gerald Fahner,
Project Analyst at Fair Isaac & Co.; and Paul DuBose, CTO of Analytika.
The story below is a fictional amalgam of their presentations, seen from
the viewpoint of an average citizen -- a day in the life of John Q. Record.
Keywords: Data
Mining, Applications, KDD-98 Panel Discussion Report, Embedded data mining
applications.
KDD-98 Exhibits Report by
Ismail Parsa
(available in PDF
and Postscript
formats)
ABSTRACT: Initially
started as a half-day long display of research prototypes, the KDD exhibits
quickly evolved into an industry event eagerly sought by the practitioners,
researchers and the vendors in the field. In this article, I provide an
overview of the KDD-98 exhibits program and the outline the factors that
led to its success.
Keywords:
KDD attendance statistics, KDD exhibits and KDD exhibit talks.
KDD at Interface-98 by
Arnold Goodman
(available in PDF
and Postscript
formats)
The
Interface?98 Conference - a Resource for KDD
by John Elder
(available in PDF
and Postscript
formats)
ABSTRACT: The
annual Symposium on the Interface between Computer Science and Statistics
is the statistical conference likely to be of greatest interest to quantitative
practitioners of KDD.
Keywords: Data Mining, Statistics |
SIGKDD
INFORMATION:
http://www.acm.org/sigkdd
join SIGKDD
today!
SIGKDD
NEWSLETTER CONTACT INFORMATION:
Usama
Fayyad
Microsoft
Research
One Microsoft
Way
Redmond,
WA 98052
Fax: +1-425-936-7329
fayyad@acm.org
Related
Links
SIGKDD
Explorations |
Contributed
Articles
Statistics and Data Mining: Intersecting Disciplines
by David J. Hand
(available in PDF
and Postscript
formats)
ABSTRACT: Statistics
and data mining have much in common, but they also have differences. The
nature of the two disciplines is examined, with emphasis on their similarities
and differences.
Keywords: Statistics, data mining, knowledge discovery.
A Survey of Data Mining software Tools
by Michael Goebel and Le Gruenwald
(available in PDF
and Postscript
formats)
ABSTRACT: Knowledge
discovery in databases is a rapidly growing field, whose development is
driven by strong research interests as well as urgent practical, social,
and economical needs. While the last few years knowledge discovery tools
have been used mainly in research environments, sophisticated software
products are now rapidly emerging. In this paper, we provide an overview
of common knowledge discovery tasks and approaches to solve these tasks.
We propose a feature classification scheme that can be used to study knowledge
and data mining software. This scheme is based on the software's general
characteristics, database connectivity, and data mining characteristics.
We then apply our feature classification scheme to investigate 43 software
products, which are either research prototypes or commercially available.
Finally, we specify features that we consider important for knowledge discovery
software to possess in order to accommodate its users effectively, as well
as issues that are either not addressed or insufficiently solved yet.
Keywords: Knowledge discovery in databases, data
mining, surveys.
A Bibliography of Temporal, Spatial, and Spatio-Temporal
Data Mining Research by J.F.
Roddick and M. Spiliopoulou
(available in PDF
and Postscript
formats)
ABSTRACT: With
the
growth in the size of datasets, data mining has recently become an important
research topic and is receiving substantial interest from both academia
and industry.At the same time, a
greater recognition of the value of temporal and spatial data has been
evident and the first papers looking at the confluence of these two areas
are starting to emerge.This short
paper provides a few comments on this research and provides a bibliography
of relevant research papers investigating temporal, spatial and spatio-temporal
data mining.
Keywords: Temporal Data Mining, Temporal Rules,
Temporal Patterns, Spatial Data Mining, Spatio-Temporal Data Mining.
Mining Sales Data using a Neural Network
Model of Market Response
by T. S. Gruca, B. R. Klemz, and
E. A. Furr Petersen
(available in PDF
and Postscript
formats)
ABSTRACT: Modeling
aggregate market response is a core issue in marketing research.
In this research, we extend previous forecasting comparative research by
comparing the forecasting accuracy of feed-forward neural network models
to the premier market modeling technique, Multiplicative Competitive Interaction
(MCI) models. Forecasts are compared in two separate studies: (1) the Information
Resources Inc. (IRI) coffee dataset from Marion, IN and (2) the A.C. Nielsen
catsup dataset from Sioux Falls, SD. Our results suggest neural networks
are a useful substitute for MCI models when there are too few observations
available to estimate a fully-extended MCI model. Implications are discussed.
Keywords: neural
networks, market response model, sales/market share forecasting
Book Reviews
Discovering Data Mining: From Concept to Implementation
by Karim K. Hirji
(available in PDF
and Postscript
formats)
ABSTRACT: This
paper is a review of the book Discovering Data Mining: From Concept to
Implementation - Peter Cabena, Pablo Hadjinian, Rolf Stadler, Jaap Verhees,
and Alessandro Zanasi (New Jersey: Prentice Hall, 195 pp., 1998).
Keywords: Data
mining, Book review.
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and Events
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and Postscript
formats)
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