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ICDM
2005
IEEE
166views Data Mining» more  ICDM 2005»
13 years 10 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
IEAAIE
2009
Springer
13 years 11 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...
KAIS
2008
150views more  KAIS 2008»
13 years 4 months ago
A survey on algorithms for mining frequent itemsets over data streams
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
James Cheng, Yiping Ke, Wilfred Ng
ICDE
2008
IEEE
192views Database» more  ICDE 2008»
14 years 6 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
DAWAK
2010
Springer
13 years 5 months ago
Mining Closed Itemsets in Data Stream Using Formal Concept Analysis
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
Anamika Gupta, Vasudha Bhatnagar, Naveen Kumar