Tutorial notes of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining

Tutorials have become an integral part of the KDD conference. This is partly because of the interdisciplinary nature of data mining, but also because of the amount and speed of progress in the past decade. Tutorials are an effective way for conference attendees to educate themselves in specific topics and to familiarize themselves with emerging subfields. Traditionally, KDD conferences have offered high-quality tutorials on many aspects of data mining.This year KDD-2001 continues this tradition with six three-hour tutorials. This tutorial set was chosen to serve a broad range of interests, from theoretical to applied, from academic to commercial, and from traditional to innovative. These tutorials also cover a range of depths, some treating an individual topic in detail and others surveying a broad area.b E-Business Enterprise Data Mining (Usama Fayyad, Neal Rothleder and Paul Bradley)b Data Mining for Outliers with Robust Statistics (R. Douglas Martin)b Advances in Decision Tree Construction (Johannes Gehrke and Wei-Yin Loh)b Data Mining To Go: Ubiquitous KDD for Mobile and Distributed Environments (Hillol Kargupta and Anupam Joshi)b Scalable Frequent-Pattern Mining Methods: An Overview (Jiawei Han, Laks V. S. Lakshrnanan and Jian Pei)b Value-based Data Mining and Web Mining for CRM (Steve Gallant, Gregory Piatetsky-Shapiro and Ming Tan)