Data Mining and Knowledge Discovery

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 Vance Bell wrote:
 From: vbell@dept.english.upenn.edu (Vance Bell)
 Subject: Data Mining and Knowledge Discovery
 Date: Fri, 13 Jun 1997 15:31:42 -0400 (EDT)
 
 Data Mining and Knowledge Discovery
 
 http://www.research.microsoft.com/datamine/
 (Link inactive 27 April 2004)

 http://www.kluweronline.com/issn/1384-5810/
 (Link active 27 April 2004)
 
 Data Mining and Knowledge Discovery is a peer reviewed journal publishing
 articles on all aspects of Knowledge Discovery in Databases (KDD) and data
 mining methods for extracting high-level representations (patterns and
 models) from data.  KDD Draws on techniques and theories from a multitude
 of fields, including statistics, pattern recognition, learning, databases,
 OLAP, optimization, uncertainty modeling, visualization, and
 high-performance and parallel computing. We aim to make this journal into
 a unified place where relevant works from all related fields are
 presented.  Submissions of high-quality original research or technical
 survey articles of related fields and techniques are welcome. We also
 publish application papers as well as short (2-page) application summary
 articles. The first issue provides examples of accepted articles.  See the
 call for papers for more details and requirements. 
 
 Recent Contents:
 
 	* Statistical Themes and Lessons for Data Mining
 	* Data Cube: A Relational Aggregation Operator Generalizing
 	   Group-by, Cross-Tab, and Sub Totals
 	* On Bias, Variance, 0/1 - loss, and the Curse-of-Dimensionality
 	* Bayesian Networks for Data Mining
 	* Advanced Scout: Data Mining and Knowledge Discovery in NBA data
 
 Contact:
 
 Editors-in-Chief
                         
 Usama Fayyad, Microsoft Research, USA, fayyad@microsoft.com
 Heikki Mannila, University of Helsinki, Department of Computer Science,
 	Heikki.Mannila@cs.Helsinki.FI 
 Gregory Piatetsky-Shapiro, Knowledge Stream, gps@genevecon.com
 

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