Data Mining & knowledge Discovery Journal: contents vol 1:1

[Usama Fayyad]

                        ANNOUNCEMENT and CALL FOR PAPERS

Below are the contents of the first issue of the new journal: Knowledge
Discovery 
and Data Mining, Kluwer Academic Publishers.

The journal is accepting submissions of works from a wide variety of
fields that 
relate to data mining and knowledge discovery in databases (KDD). We
accept regular
research contributions, survey articles, application details papers, as
well as 
short (2-page) application summaries.  The goal is for Data Mining and
Knowledge 
Discovery to become the premiere forum for publishing high quality
original work 
from the wide variety of fields on which KDD draws, including:
statistics, pattern
recognition, database research and systems, modelling uncertainty and
decision
making, neural networks, machine learning, OLAP, data warehousing,
high-performance
and parallel computing, and visualization.

The goal is to create a reference resource where researchers and
practitioners in
the area can lookup and communicate relevant work from a wide variety of
fields.

The journal's homepage provides detailed call for papers, description of
the
journal and its scope, and a list of the Editorial Board.  Abstracts of
the articles in the first issue and the editorial are also on-line. The
home page
is maintained at:  http://www.research.microsoft.com/research/datamine

   - If you are interested in submitting a paper, please visit the
     homepage: http://www.research.microsoft.com/research/datamine
     to look up instructions.

   - if you would like a free sample issue sent to you, click on
     the link in http://www.research.microsoft.com/research/datamine
     and provide an address via the on-line form.

Usama Fayyad, co-Editor-in-Chief
Data Mining and Knowledge Discovery (datamine at microsoft.com)

=======================================================================

Data Mining and Knowledge Discovery
http://www.research.microsoft.com/research/datamine   

CONTENTS OF: Volume 1, Issue 1
==============================
  For more details, abstracts, and on-line version of Editorial, see
  http://www.research.microsoft.com/research/datamine/vol1-1

              ===========Volume 1, Number 1,  March 1997===========

EDITORIAL by Usama Fayyad  

PAPERS
======

Statistical Themes and Lessons for Data Mining 
      Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth

Data Cube: A Relational Aggregation Operator Generalizing Group-by,
Cross-Tab, and Sub Totals  
      Jim Gray, Surajit Chaudhuri, Adam Bosworth, Andrew Layman, Don
Reichart, 
      Murali Venkatrao, Frank Pellow,  IBM, Toronto, Hamid Pirahesh

On Bias, Variance, 0/1 - loss, and the Curse-of-Dimensionality   
     Jerome H. Friedman

Bayesian Networks for Data Mining  
     David Heckerman

BRIEF APPLICATIONS SUMMARIES:
============================

Advanced Scout: Data Mining and Knowledge Discovery in NBA data  
    Ed Colet, Inderpal Bhandari, Jennifer Parker, Zachary Pines, Rajiv
Pratap, Krishnakumar Ramanujam

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To get a free sample copy of the above issue, visit the web page at
http://www.research.microsoft.com/research/datamine
Those who do not have web access may send their address to Kluwer
by e-mail at: sdelman at wkap.com