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Further reading

This is a list of the important material about data mining we used to encounter working in this field. It is by no means exhaustive, and it may change in future. It includes a list of important books and articles (offline reading), as well as links (online reading) to specific texts, articles, tutorials, and presentations available on WEB.

Offline reading




Online reading

General DM sites - the leading source of information on Data Mining, Web Mining, Knowledge Discovery, and Decision Support Topics.

The Data Mine - a major server of information related to Data Mining. P apers, Conferences, Software, Home pages, Bibliographies ....

Knowledge Discovery Central

Evaluation of Intelligent Systems (EIS) - a server providing guides in experiment design, data analysis and statistics.

DM tutorials

Introduction to Knowledge Discovery and Data Mining
by Tu Bao Ho

CRISP-DM - CRoss Industry Standard Process for Data Mining
result of a project lead by four companies who are leaders in their respective industries

Tutorial on High Performance Data Mining
by Vipin Kumar and Mahesh Joshi

Course on Knowledge Discovery in Databases
by D.H. Hamilton et al.

Data Mining
by Peter Ross

Data mining in molecluar biology

DM Modelling techniques

Association Rules

ARMiner - a client-server data mining application specialized in finding association rules
maintained by L. Cristofor.

Decision trees

Decision Tree Learning Applet

Overview of Decision Trees
by D.H. Hamilton et al.


Data Clustering and Its Applications
by Raza Ali, Usman Ghani , Aasim Saeed

Neural Networks

An introduction to neural networks
by A. Blais and D. Mertz,t=grl,p=NeuralNets

Neural networks
by C. Stergiou and D. Siganos

Neural nets overview
by J. Fröhlich

Mini-tutorial on artificial neural networks
by S. L. Thaler

Artificial neural networks
by F. Rodriguez

Bayesian Networks

B-Course - a WEB based tutorial on Bayesian Networks
hosted by Complex Systems Computation Group, Department of Computer Science, University of Helsinki
(online BN analysis is possible, too)

A Brief Introduction to Graphical Models and Bayesian Networks

Software Packages for Graphical Models / Bayesian Networks

Tutorial on Learning With Bayesian Networks
by D. Heckerman

Peter Clark - Software

© 2001 LIS - Rudjer Boskovic Institute
Last modified: May 21 2019 22:46:57.