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» Mining evolving data streams for frequent patterns
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DAWAK
2004
Springer
15 years 1 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
DATAMINE
1999
152views more  DATAMINE 1999»
14 years 9 months ago
Discovery of Frequent DATALOG Patterns
Discovery of frequent patterns has been studied in a variety of data mining settings. In its simplest form, known from association rule mining, the task is to discover all frequent...
Luc Dehaspe, Hannu Toivonen
ICDE
2004
IEEE
116views Database» more  ICDE 2004»
15 years 11 months ago
An Efficient Algorithm for Mining Frequent Sequences by a New Strategy without Support Counting
Mining sequential patterns in large databases is an important research topic. The main challenge of mining sequential patterns is the high processing cost due to the large amount ...
Ding-Ying Chiu, Yi-Hung Wu, Arbee L. P. Chen
JIIS
2008
133views more  JIIS 2008»
14 years 9 months ago
Maintaining frequent closed itemsets over a sliding window
In this paper, we study the incremental update of Frequent Closed Itemsets (FCIs) over a sliding window in a high-speed data stream. We propose the notion of semi-FCIs, which is to...
James Cheng, Yiping Ke, Wilfred Ng
ICDE
2010
IEEE
198views Database» more  ICDE 2010»
15 years 3 months ago
Power-aware data analysis in sensor networks
Abstract— Sensor networks have evolved to a powerful infrastructure component for event monitoring in many application scenarios. In addition to simple filter and aggregation op...
Daniel Klan, Katja Hose, Marcel Karnstedt, Kai-Uwe...