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ICDM
2005
IEEE
166views Data Mining» more  ICDM 2005»
15 years 9 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
149
Voted
ICDM
2007
IEEE
254views Data Mining» more  ICDM 2007»
15 years 10 months ago
Sampling for Sequential Pattern Mining: From Static Databases to Data Streams
Sequential pattern mining is an active field in the domain of knowledge discovery. Recently, with the constant progress in hardware technologies, real-world databases tend to gro...
Chedy Raïssi, Pascal Poncelet
IEAAIE
2009
Springer
15 years 10 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...
IDA
2007
Springer
15 years 4 months ago
Approximate mining of frequent patterns on streams
Abstract. This paper introduces a new algorithm for approximate mining of frequent patterns from streams of transactions using a limited amount of memory. The proposed algorithm co...
Claudio Silvestri, Salvatore Orlando
IDEAS
2007
IEEE
128views Database» more  IDEAS 2007»
15 years 10 months ago
Streaming Random Forests
Many recent applications deal with data streams, conceptually endless sequences of data records, often arriving at high flow rates. Standard data-mining techniques typically assu...
Hanady Abdulsalam, David B. Skillicorn, Patrick Ma...