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PPOPP
2005
ACM
14 years 4 months ago
A sampling-based framework for parallel data mining
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
Shengnan Cong, Jiawei Han, Jay Hoeflinger, David A...
VLDB
1998
ACM
112views Database» more  VLDB 1998»
14 years 3 months ago
Incremental Clustering for Mining in a Data Warehousing Environment
Data warehouses provide a great deal of opportunities for performing data mining tasks such as classification and clustering. Typically, updates are collected and applied to the d...
Martin Ester, Hans-Peter Kriegel, Jörg Sander...
ICDE
2008
IEEE
120views Database» more  ICDE 2008»
15 years 7 days ago
Direct Discriminative Pattern Mining for Effective Classification
The application of frequent patterns in classification has demonstrated its power in recent studies. It often adopts a two-step approach: frequent pattern (or classification rule) ...
Hong Cheng, Xifeng Yan, Jiawei Han, Philip S. Yu
ICDE
2007
IEEE
161views Database» more  ICDE 2007»
15 years 7 days ago
Mining Colossal Frequent Patterns by Core Pattern Fusion
Extensive research for frequent-pattern mining in the past decade has brought forth a number of pattern mining algorithms that are both effective and efficient. However, the exist...
Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, H...
KDD
2012
ACM
217views Data Mining» more  KDD 2012»
12 years 1 months ago
The long and the short of it: summarising event sequences with serial episodes
An ideal outcome of pattern mining is a small set of informative patterns, containing no redundancy or noise, that identifies the key structure of the data at hand. Standard freq...
Nikolaj Tatti, Jilles Vreeken