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APPINF
2003
15 years 1 months ago
Fast Frequent Itemset Mining using Compressed Data Representation
Discovering association rules by identifying relationships among sets of items in a transaction database is an important problem in Data Mining. Finding frequent itemsets is compu...
Raj P. Gopalan, Yudho Giri Sucahyo
RSFDGRC
2005
Springer
110views Data Mining» more  RSFDGRC 2005»
15 years 5 months ago
A Rough Set Based Model to Rank the Importance of Association Rules
Abstract. Association rule algorithms often generate an excessive number of rules, many of which are not significant. It is difficult to determine which rules are more useful, int...
Jiye Li, Nick Cercone
VLDB
2004
ACM
115views Database» more  VLDB 2004»
15 years 5 months ago
Semantic Mining and Analysis of Gene Expression Data
Association rules can reveal biological relevant relationship between genes and environments / categories. However, most existing association rule mining algorithms are rendered i...
Xin Xu, Gao Cong, Beng Chin Ooi, Kian-Lee Tan, Ant...
ICDM
2002
IEEE
93views Data Mining» more  ICDM 2002»
15 years 4 months ago
Learning from Order Examples
We advocate a new learning task that deals with orders of items, and we call this the Learning from Order Examples (LOE) task. The aim of the task is to acquire the rule that is u...
Toshihiro Kamishima, Shotaro Akaho
PKDD
1998
Springer
123views Data Mining» more  PKDD 1998»
15 years 4 months ago
Querying Inductive Databases: A Case Study on the MINE RULE Operator
Knowledge discovery in databases (KDD) is a process that can include steps like forming the data set, data transformations, discovery of patterns, searching for exceptions to a pat...
Jean-François Boulicaut, Mika Klemettinen, ...