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KDD
2003
ACM
194views Data Mining» more  KDD 2003»
14 years 6 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee
SAC
2006
ACM
13 years 12 months ago
Induction of compact decision trees for personalized recommendation
We propose a method for induction of compact optimal recommendation policies based on discovery of frequent itemsets in a purchase database, followed by the application of standar...
Daniel Nikovski, Veselin Kulev
DATAMINE
2010
166views more  DATAMINE 2010»
13 years 6 months ago
Optimal constraint-based decision tree induction from itemset lattices
In this article we show that there is a strong connection between decision tree learning and local pattern mining. This connection allows us to solve the computationally hard probl...
Siegfried Nijssen, Élisa Fromont
KDD
2005
ACM
92views Data Mining» more  KDD 2005»
14 years 6 months ago
Summarizing itemset patterns: a profile-based approach
Frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. However, the bottleneck of...
Xifeng Yan, Hong Cheng, Jiawei Han, Dong Xin
ICDM
2006
IEEE
132views Data Mining» more  ICDM 2006»
14 years 2 days ago
High Quality, Efficient Hierarchical Document Clustering Using Closed Interesting Itemsets
High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to...
Hassan H. Malik, John R. Kender