文档介绍：Knowledge discovery & data mining Tools, methods, and experiences
Fosca Giannotti and
Dino Pedreschi
Pisa KDD R & Univ. Pisa
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A tutorial @ EDBT2000
EDBT2000 tutorial
1
Konstanz, March 2000
Contributors and acknowledgements
The people @ Pisa KDD Lab: Francesco BONCHI, Giuseppe MANCO, Mirco NANNI, Chiara RENSO, Salvatore RUGGIERI, Franco TURINI and many students
The many KDD tutorialists and teachers which made their slides available on the web (all of them listed in bibliography) ;-)
In particular:
Jiawei HAN, Simon Fraser University, whose ing book Data mining: concepts and techniques has influenced the whole tutorial
Rajeev RASTOGI and Kyuseok SHIM, Lucent Bell Labs
Daniel A. KEIM, University of Halle
Daniel Silver, CogNova Technologies
The EDBT2000 board who accepted our tutorial proposal
Konstanz, 27-
2
EDBT2000 tutorial - Intro
Tutorial goals
Introduce you to major aspects of the Knowledge Discovery Process, and theory and applications of Data Mining technology
Provide a systematization to the many many concepts around this area, according the following lines
the process
the methods applied to paradigmatic cases
the support environment
the research challenges
Important issues that will be not covered in this tutorial:
methods: time series, exception detection, s
systems: parallel implementations
Konstanz, 27-
3
EDBT2000 tutorial - Intro
Tutorial Outline
Introduction and basic concepts
Motivations, applications, the KDD process, the techniques
Deeper into DM technology
Decision Trees and Fraud Detection
Association Rules and Market Basket Analysis
Clustering and Customer Segmentation
Trends in technology
Knowledge Discovery Support Environment
Tools, Languages and Systems
Research challenges
Konstanz, 27-
4
EDBT2000 tutorial - Intro
Introduction - module outline
Motivations
Application Areas
KDD Decisional Context
KDD Process
Architecture of a KDD system
The KDD steps in short
Konstanz, 27-