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» Mining evolving data streams for frequent patterns
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PODS
2009
ACM
134views Database» more  PODS 2009»
15 years 10 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...
KDD
2003
ACM
156views Data Mining» more  KDD 2003»
15 years 10 months ago
Fast vertical mining using diffsets
A number of vertical mining algorithms have been proposed recently for association mining, which have shown to be very effective and usually outperform horizontal approaches. The ...
Mohammed Javeed Zaki, Karam Gouda
PKDD
2005
Springer
101views Data Mining» more  PKDD 2005»
15 years 3 months ago
A Random Method for Quantifying Changing Distributions in Data Streams
In applications such as fraud and intrusion detection, it is of great interest to measure the evolving trends in the data. We consider the problem of quantifying changes between tw...
Haixun Wang, Jian Pei
ICDE
2005
IEEE
176views Database» more  ICDE 2005»
15 years 3 months ago
LAPIN-SPAM: An Improved Algorithm for Mining Sequential Pattern
Sequence pattern mining is an important research problem because it is the basis of many other applications. Yet how to efficiently implement the mining is difficult due to the ...
Zhenglu Yang, Masaru Kitsuregawa
TKDE
2011
183views more  TKDE 2011»
14 years 4 months ago
Mining Discriminative Patterns for Classifying Trajectories on Road Networks
—Classification has been used for modeling many kinds of data sets, including sets of items, text documents, graphs, and networks. However, there is a lack of study on a new kind...
Jae-Gil Lee, Jiawei Han, Xiaolei Li, Hong Cheng