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SDM
2003
SIAM
134views Data Mining» more  SDM 2003»
13 years 6 months ago
Hierarchical Document Clustering using Frequent Itemsets
A major challenge in document clustering is the extremely high dimensionality. For example, the vocabulary for a document set can easily be thousands of words. On the other hand, ...
Benjamin C. M. Fung, Ke Wang, Martin Ester
PODS
2009
ACM
134views Database» more  PODS 2009»
14 years 5 months ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...
ICDM
2005
IEEE
166views Data Mining» more  ICDM 2005»
13 years 11 months ago
An Algorithm for In-Core Frequent Itemset Mining on Streaming Data
Frequent itemset mining is a core data mining operation and has been extensively studied over the last decade. This paper takes a new approach for this problem and makes two major...
Ruoming Jin, Gagan Agrawal
ICDM
2006
IEEE
135views Data Mining» more  ICDM 2006»
13 years 11 months ago
Discovering Frequent Poly-Regions in DNA Sequences
The problem of discovering arrangements of regions of high occurrence of one or more items of a given alphabet in a sequence, is studied, and two efficient approaches are propose...
Panagiotis Papapetrou, Gary Benson, George Kollios
DAWAK
2004
Springer
13 years 9 months ago
PROWL: An Efficient Frequent continuity Mining Algorithm on Event Sequences
Mining association rule in event sequences is an important data mining problem with many applications. Most of previous studies on association rules are on mining intra-transaction...
Kuo-Yu Huang, Chia-Hui Chang, Kuo-Zui Lin