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» Mining top-K frequent itemsets from data streams
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DATAMINE
2006
230views more  DATAMINE 2006»
13 years 11 months ago
Mining top-K frequent itemsets from data streams
Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu
DIS
2007
Springer
14 years 3 months ago
Efficient Incremental Mining of Top-K Frequent Closed Itemsets
In this work we study the mining of top-K frequent closed itemsets, a recently proposed variant of the classical problem of mining frequent closed itemsets where the support thresh...
Andrea Pietracaprina, Fabio Vandin
ICDE
2008
IEEE
192views Database» more  ICDE 2008»
15 years 16 days ago
Verifying and Mining Frequent Patterns from Large Windows over Data Streams
Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...
Barzan Mozafari, Hetal Thakkar, Carlo Zaniolo
IEAAIE
2009
Springer
14 years 5 months ago
An Efficient Algorithm for Maintaining Frequent Closed Itemsets over Data Stream
Data mining refers to the process of revealing unknown and potentially useful information from a large database. Frequent itemsets mining is one of the foundational problems in dat...
Show-Jane Yen, Yue-Shi Lee, Cheng-Wei Wu, Chin-Lin...
JCIT
2010
174views more  JCIT 2010»
13 years 6 months ago
Efficient Ming of Top-K Closed Sequences
Sequence mining is an important data mining task. In order to retrieve interesting sequences from a large database, a minimum support threshold is needed to be specified. Unfortun...
Panida Songram