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ICDM
2006
IEEE
227views Data Mining» more  ICDM 2006»
13 years 9 months ago
Incremental Mining of Sequential Patterns over a Stream Sliding Window
Incremental mining of sequential patterns from data streams is one of the most challenging problems in mining data streams. However, previous work of mining sequential patterns fr...
Chin-Chuan Ho, Hua-Fu Li, Fang-Fei Kuo, Suh-Yin Le...
DAWAK
2006
Springer
13 years 7 months ago
An Approximate Approach for Mining Recently Frequent Itemsets from Data Streams
Recently, the data stream, which is an unbounded sequence of data elements generated at a rapid rate, provides a dynamic environment for collecting data sources. It is likely that ...
Jia-Ling Koh, Shu-Ning Shin
ICDE
2008
IEEE
192views Database» more  ICDE 2008»
14 years 5 months 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
STACS
2010
Springer
13 years 10 months ago
Continuous Monitoring of Distributed Data Streams over a Time-based Sliding Window
The past decade has witnessed many interesting algorithms for maintaining statistics over a data stream. This paper initiates a theoretical study of algorithms for monitoring distr...
Ho-Leung Chan, Tak Wah Lam, Lap-Kei Lee, Hing-Fung...
JIIS
2008
133views more  JIIS 2008»
13 years 3 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