This page contains numerous papers and white papers about Data Mining and Knowledge Discovery.

A Bayesian Approach to Filtering Junk Email (Sahami et al, 1998)

Cached Sufficient Statistics (Moore et al., 2000) : white papers and some more Artificial Intelligence papers

Clustering and Visualization of Navigation Patterns on a Web Site ( Cadez et al, 2000)

Data Mining and Statistics: What is the Connection (Jerome Friedman)

Data Mining at the Interface of Computers and Statistics (Padhraic Smith)

Data Mining Techniques and Algorithms (Dunham, 2000)

Data Mining Tools - A Classification (Decision Framework, DF-07-7020, K. Strange, A. Linden, Research Note, 17 March 1999)

Data Mining with Graphical Methods - Dissertation (Doktoringenieur, 2000)

Designing and Mining Multi-Terabyte Astronomy Archives (Szalay et al, 1999)

How Much Information is There in the World (Michael Lesk, 1997):

Introduction to Data Mining and Knowledge Discovery - Two Crows Paper

Jerome H. Friedman: A few papers of Statistics and Data Mining. Some of them are

Tips for Successful Data Mining: An Oracle Technical White Paper (June, 1999)

Web Document Clustering (Zamir and Etzioni, 1998)

Giga-Mining (Cortes and Pregibon, 1997)

Detecting Group Differences:  Mining Contrast Sets (Bay and Pazzani, 2001)

Mining the Network Value of Customers (Richardson and Domingos, 2001)

Some more Data Mining papers from Domingos

Web Mining: Information and Pattern Discovery on the World Wide Web (Cooley et al.,1997)

The Page Rank Citation Ranking: Bringing Order to the Web (Brin et al., 1998): This paper is on page rank algorithm

Split Procedure

Growing Trees for Stratified Modeling (Padraic G. Neville)

Decision Trees for Predictive Modeling (Padraic G. Neville, 1999)

Alternative Neural Architectures (Will Dwinnel)

On Bagging and Non-Linear Estimation (Jerome H. Friedman et al, 2000)

Gene Expression Informatics (Bassett et al, 1999)

A Tutorial on Learning With Bayesian Networks (David Heckerman, 1996)

A Tutorial on Bayesian Model Averaging (Hoeting et al, 1999)

Learning Bayes Nets from Data (David Heckerman)

A Complete Tutorial on Bayesian Statistics (Bernardo)

Clustering Large Datasets in Arbitrary Metric Spaces (Ganti, Ramakrishnan, Gehrke)

Additive Logistic Regression: A Statistical View of Boosting (Friedman et al, 1999)

Neural Network Models for Breast Cancer Prognosis (Ruth M. Ripley, 1998)

Predictive Multivariate Responses in Multiple Linear Regression ( Friedman, Brieman, 1997)- Journal of Royal Statistical Society

Salford Systems - Critical Features of High Performance Decision Trees

The Customer Relationship Management Primer - What You Need To Get Started (From CRMguru.com)

On Bias, Variability, 0/1 - Loss, and the Curse of Dimensionality (Friedman, 1996)

Darwin: A Scalable Integrated System for Data Mining (Tamayo et al, 1997)

Data Dictionary (Dr. Hardin)

Designing and Mining Multi-Terabyte Astronomy Archives: The Sloan Digital Sky Survey (Alexander S. Szalay, 2000)

Data Mining and Visualization (Ron Kohavi, 2000)

Data Mining to Measure and Improve the Success of Websites (Pohle, 2000)

Applications of Data Mining to Electronic Commerce (Kohavi et al, 2001)

Which Visits Lead to Purchases? Dynamic Conversion Behavior at e-Commerce Sites (Wendy W. Moe, 2001)

Finding the Solution to Data Mining - Exploring the features and components of Enterprise Miner (SAS)

Tutorial on e-Commerce and Clickstream Mining Vendor Sites (Becher et al, 2001) - First SIAM International Conference on data Mining

The EMMIX Software for the Fitting of Mixtures of Normal and t-Components (McLachlan)

Adaptive Fraud Detection (Foster Provost et al, 1997)

Generalization of Boosting Algorithms and Applications of Bayesian Inference for Massive Datasets (Ridgeway, 1999) - A PHD dissertation from the university of Wisconsin at Department of Statistics.

Decision Support in the Booming e- world (James Goodnight, CEO)

Model-Based Clustering and Visualization of Navigation Patterns on a Web Site (Cadez et al, 2001)

How Much Can Data Analysis Be Automated? (Will Dwinnell)

Hugin Expert - A White Paper                                                                                                            

IBM DB2 Intelligent Miner for Data V6R1, Greater Competitiveness Through Informed Decision Making (IBM, 1999)