scholarly journals Mining Frequent Itemsets over Recent Data Stream Based on Genetic Algorithm

10.5772/38445 ◽  
2012 ◽  
Author(s):  
Zhou Yong ◽  
Han Jun ◽  
Guo He
Keyword(s):  
Genetic Algorithm ◽  
Data Stream ◽  
Frequent Itemsets ◽  
Mining Frequent Itemsets

Maximal Frequent Itemsets in Data Stream Mining Based on Orderly-Compound Policy

2010 ◽  
Vol 26-28 ◽  
pp. 113-117
Author(s):  
Pei Shuai Chen ◽  
Chong Huan Xu
Keyword(s):  
Data Stream ◽  
Frequent Itemsets ◽  
Space Efficiency ◽  
Time Space ◽  
Algorithm Construct ◽  
Closed Itemsets ◽  
Maximal Frequent Itemsets ◽  
Mining Frequent Itemsets ◽  
Basic Window ◽  
Pruning Technique

Mining maximal frequent itemsets get the advantage of a relatively small number of itemsets. Compared to mining frequent itemsets and mining frequent closed itemsets, such algorithm has higher time and space efficiency. According to the features of data streams and combined sliding window, a new algorithm E-FPMFI which is based on orderly-compound policy for mining maximal frequent itemsets in data stream is proposed. The algorithm based on basic window updates information from data stream flow fragment and scans the stream only once to gain and store it in frequent itemsets list. The algorithm construct FP-tree, then compress orderly FP-tree by merging nodes which has equal minsup in same branch, also uses subset mix pruning technique, avoid superset checking. The experimental results show the algorithm has higher time, space efficiency and good scalability.

scholarly journals Mining Frequent Itemsets Using Genetic Algorithm

2010 ◽  
Vol 1 (4) ◽  
pp. 133-143 ◽  
Author(s):  
S Ghosh ◽  
S Biswas ◽  
D Sarkar ◽  
P.P Sarkar
Keyword(s):  
Genetic Algorithm ◽  
Frequent Itemsets ◽  
Mining Frequent Itemsets

scholarly journals Towards a new approach for mining frequent itemsets on data stream

2006 ◽  
Vol 28 (1) ◽  
pp. 23-36 ◽  
Author(s):  
Chedy Raïssi ◽  
Pascal Poncelet ◽  
Maguelonne Teisseire
Keyword(s):  
Data Stream ◽  
Frequent Itemsets ◽  
New Approach ◽  
Mining Frequent Itemsets
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