Rare association rule mining and knowledge discovery technologies for infrequent and critical event detection
Title:
Rare association rule mining and knowledge discovery technologies for infrequent and critical event detection
Author:
Koh, Yun Sing, 1978-
ISBN:
9781605667553
Publication Information:
Hershey, Pa. : IGI Global (701 E. Chocolate Ave., Hershey, PA, 17033, USA), c2010.
Physical Description:
electronic texts (xix, 299 p. : ill.) : digital files.
Series:
Advances in data warehousing and mining series
Advances in data warehousing and mining.
Contents:
1. Rare association rule mining / Yun Koh, Nathan Rountree -- 2. Association rule and quantitative association rule mining among infrequent items / Ling Zhou, Stephen Yau -- 3. Replacing support in association rule mining / Rosa Meo, Dino Ienco -- 4. Effective mining of weighted Fuzzy association rules / Maybin Muyeba, M. Khan, Frans Coenen -- 5. Rare class association rule mining with multiple imbalanced attributes / Huaifeng Zhang ... [et al.] -- 6. A multi-methodological approach to rare association rule mining / Yun Koh, Russel Pears -- 7. Finding minimal infrequent elements in multi-dimensional data defined over partially ordered sets and its applications / Khaled Elbassioni -- 8. Discovering interesting patterns in numerical data with background knowledge / Szymon Jaroszewicz -- 9. Mining rare association rules by discovering quasi-functional dependencies / Giulia Bruno, Paolo Garza, Elisa Quintarelli -- 10. Mining unexpected sequential patterns and implication rules / Dong Li, Anne Laurent, Pascal Poncelet -- 11. Mining hidden association rules from real-life data / Marco-Antonio Balderas Cepeda -- 12. Strong symmetric association rules and interestingness measures / Agathe Merceron -- 13. He wasn't there again today / Richard O'Keefe, Nathan Rountree -- 14. Filtering association rules by their semantics and structures / Rangsipan Marukatat -- 15. Creating risk-scores in very imbalanced datasets / Markus Breitenbach ... [et al.] -- 16. Boosting prediction accuracy of bad payments in financial credit applications / Russel Pears, Raymond Oetama.
Abstract:
"This book provides readers with an in-depth compendium of current issues, trends, and technologies in association rule mining"--Provided by publisher.
Added Corporate Author:
Electronic Access:
Chapter PDFs via platform: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-60566-754-6