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» Mining Frequent Itemsets in a Stream
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DAWAK
2010
Springer
13 years 6 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
PKDD
2004
Springer
131views Data Mining» more  PKDD 2004»
13 years 10 months ago
Asynchronous and Anticipatory Filter-Stream Based Parallel Algorithm for Frequent Itemset Mining
Abstract In this paper we propose a novel parallel algorithm for frequent itemset mining. The algorithm is based on the filter-stream programming model, in which the frequent item...
Adriano Veloso, Wagner Meira Jr., Renato Ferreira,...
JIIS
2007
150views more  JIIS 2007»
13 years 4 months ago
Towards a new approach for mining frequent itemsets on data stream
Mining frequent patterns on streaming data is a new challenging problem for the data mining community since data arrives sequentially in the form of continuous rapid streams. In t...
Chedy Raïssi, Pascal Poncelet, Maguelonne Tei...
IDA
2007
Springer
13 years 5 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
ICDM
2005
IEEE
166views Data Mining» more  ICDM 2005»
13 years 11 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