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» Mining evolving data streams for frequent patterns
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KDD
2010
ACM
300views Data Mining» more  KDD 2010»
15 years 1 months ago
Mining top-k frequent items in a data stream with flexible sliding windows
We study the problem of finding the k most frequent items in a stream of items for the recently proposed max-frequency measure. Based on the properties of an item, the maxfrequen...
Hoang Thanh Lam, Toon Calders
PKDD
2005
Springer
138views Data Mining» more  PKDD 2005»
15 years 3 months ago
Indexed Bit Map (IBM) for Mining Frequent Sequences
Sequential pattern mining has been an emerging problem in data mining. In this paper, we propose a new algorithm for mining frequent sequences. It processes only one scan of the da...
Lionel Savary, Karine Zeitouni
ICDM
2005
IEEE
166views Data Mining» more  ICDM 2005»
15 years 3 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
2009
IEEE
139views Data Mining» more  ICDM 2009»
14 years 7 months ago
Frequent Pattern Discovery from a Single Graph with Quantitative Itemsets
In this paper, we focus on a single graph whose vertices contain a set of quantitative attributes. Several networks can be naturally represented in this complex graph. An example i...
Yuuki Miyoshi, Tomonobu Ozaki, Takenao Ohkawa
ICDM
2007
IEEE
175views Data Mining» more  ICDM 2007»
15 years 4 months ago
gApprox: Mining Frequent Approximate Patterns from a Massive Network
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, deman...
Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han