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» A new classification of datasets for frequent itemsets
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ICDE
2003
IEEE
146views Database» more  ICDE 2003»
14 years 10 months ago
Generalized Closed Itemsets for Association Rule Mining
The output of boolean association rule mining algorithms is often too large for manual examination. For dense datasets, it is often impractical to even generate all frequent items...
Vikram Pudi, Jayant R. Haritsa
CIKM
2006
Springer
14 years 15 days ago
TRIPS and TIDES: new algorithms for tree mining
Recent research in data mining has progressed from mining frequent itemsets to more general and structured patterns like trees and graphs. In this paper, we address the problem of...
Shirish Tatikonda, Srinivasan Parthasarathy, Tahsi...
KDD
2008
ACM
246views Data Mining» more  KDD 2008»
14 years 9 months ago
Direct mining of discriminative and essential frequent patterns via model-based search tree
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Y...
ADMA
2007
Springer
159views Data Mining» more  ADMA 2007»
14 years 3 months ago
A Novel Text Classification Approach Based on Enhanced Association Rule
The current research on association rule based text classification neglected several key problems. First, weights of elements in profile vectors may have much impact on generating ...
Jiangtao Qiu, Changjie Tang, Tao Zeng, Shaojie Qia...
KDD
2007
ACM
177views Data Mining» more  KDD 2007»
14 years 9 months ago
Mining optimal decision trees from itemset lattices
We present DL8, an exact algorithm for finding a decision tree that optimizes a ranking function under size, depth, accuracy and leaf constraints. Because the discovery of optimal...
Élisa Fromont, Siegfried Nijssen