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» Itemset Materializing for Fast Mining of Association Rules
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IDA
2009
Springer
14 years 8 months ago
Efficient Vertical Mining of Frequent Closures and Generators
Abstract. The effective construction of many association rule bases requires the computation of both frequent closed and frequent generator itemsets (FCIs/FGs). However, only few m...
Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, R...
DAWAK
2001
Springer
15 years 3 months ago
A Theoretical Framework for Association Mining Based on the Boolean Retrieval Model
Data mining has been defined as the non- trivial extraction of implicit, previously unknown and potentially useful information from data. Association mining is one of the important...
Peter Bollmann-Sdorra, Aladdin Hafez, Vijay V. Rag...
PAKDD
2005
ACM
124views Data Mining» more  PAKDD 2005»
15 years 4 months ago
Finding Sporadic Rules Using Apriori-Inverse
We define sporadic rules as those with low support but high confidence: for example, a rare association of two symptoms indicating a rare disease. To find such rules using the w...
Yun Sing Koh, Nathan Rountree
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
15 years 11 months ago
An inductive database prototype based on virtual mining views
We present a prototype of an inductive database. Our system enables the user to query not only the data stored in the database but also generalizations (e.g. rules or trees) over ...
Élisa Fromont, Adriana Prado, Bart Goethals...
FIMI
2004
175views Data Mining» more  FIMI 2004»
15 years 13 days ago
CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure
Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
Yudho Giri Sucahyo, Raj P. Gopalan