Association Rule Mining

Models and Algorithms
2002
ISBN: 978-3-540-43533-4
Verlag: Springer Berlin Heidelberg

Buch, Englisch, 244 Seiten, Format (B × H): 155 mm x 233 mm, Gewicht: 391 g

Reihe: Lecture Notes in Artificial Intelligence

Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professionals, association rule mining is receiving increasing attention.
The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.

Zielgruppe

Research

Autoren/Hrsg.

Zhang, Shichao

Zhang, Chengqi

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenkompression, Dokumentaustauschformate
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Zeichen- und Zahlendarstellungen
• Mathematik | Informatik EDV | Informatik Informatik Logik, formale Sprachen, Automaten
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme

Inhaltsverzeichnis

Association Rule.- Negative Association Rule.- Causality in Databases.- Causal Rule Analysis.- Association Rules in Very Large Databases.- Association Rules in Small Databases.- Conclusion and Future Work.