scholarly journals Mining Frequent Itemsets from Data Streams with a Time-Sensitive Sliding Window

2005 ◽  
Author(s):  
Chih-Hsiang Lin ◽  
Ding-Ying Chiu ◽  
Yi-Hung Wu ◽  
Arbee L. P. Chen
Keyword(s):  
Data Streams ◽  
Sliding Window ◽  
Frequent Itemsets ◽  
Mining Frequent Itemsets

Efficient Data Streams Based Closed Frequent Itemsets Mining Algorithm

2012 ◽  
Vol 256-259 ◽  
pp. 2910-2913
Author(s):  
Jun Tan
Keyword(s):  
Data Streams ◽  
Sliding Window ◽  
Frequent Itemsets ◽  
Streaming Data ◽  
Efficient Data ◽  
Closed Itemsets ◽  
Frequent Itemsets Mining ◽  
Synthetic Datasets ◽  
Online Mining ◽  
Mining Data Streams

Online mining of frequent closed itemsets over streaming data is one of the most important issues in mining data streams. In this paper, we proposed a novel sliding window based algorithm. The algorithm exploits lattice properties to limit the search to frequent close itemsets which share at least one item with the new transaction. Experiments results on synthetic datasets show that our proposed algorithm is both time and space efficient.

scholarly journals Finding Frequent Itemsets over Data Streams with Sliding Window

2018 ◽  
Vol 11 (8) ◽  
pp. 85-94
Author(s):  
Jeong Hee Hwang ◽  
Hyeok Kim ◽  
Jeong Hee Chi
Keyword(s):  
Data Streams ◽  
Sliding Window ◽  
Frequent Itemsets
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