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CIKM
2001
Springer
13 years 11 months ago
Sliding-Window Filtering: An Efficient Algorithm for Incremental Mining
We explore in this paper an effective sliding-window filtering (abbreviatedly as SWF) algorithm for incremental mining of association rules. In essence, by partitioning a transact...
Chang-Hung Lee, Cheng-Ru Lin, Ming-Syan Chen
PKDD
1998
Springer
123views Data Mining» more  PKDD 1998»
13 years 12 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, ...
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
14 years 8 months ago
Predicting customer shopping lists from point-of-sale purchase data
This paper describes a prototype that predicts the shopping lists for customers in a retail store. The shopping list prediction is one aspect of a larger system we have developed ...
Chad M. Cumby, Andrew E. Fano, Rayid Ghani, Marko ...
IDA
2005
Springer
14 years 1 months ago
From Local Pattern Mining to Relevant Bi-cluster Characterization
Clustering or bi-clustering techniques have been proved quite useful in many application domains. A weakness of these techniques remains the poor support for grouping characterizat...
Ruggero G. Pensa, Jean-François Boulicaut
ICCS
2004
Springer
14 years 1 months ago
Iceberg Query Lattices for Datalog
In this paper we study two orthogonal extensions of the classical data mining problem of mining association rules, and show how they naturally interact. The first is the extension...
Gerd Stumme