A Hybrid Solution of Mining Frequent Itemsets from Uncertain Database

2014 ◽  
pp. 581-590
Author(s):  
Xiaomei Yu ◽  
Hong Wang ◽  
Xiangwei Zheng
Keyword(s):  
Frequent Itemsets ◽  
Hybrid Solution ◽  
Uncertain Database ◽  
Mining Frequent Itemsets

scholarly journals Mining Frequent Itemsets Over Uncertain Database using Matrix

2020 ◽  
Vol 9 (4) ◽  
pp. 2048-2052
Keyword(s):  
Data Mining ◽  
Frequent Itemsets ◽  
Frequent Itemset ◽  
Apriori Algorithm ◽  
Computation Complexity ◽  
Support Count ◽  
Frequent Items ◽  
Uncertain Database ◽  
Modern Era ◽  
Mining Frequent Itemsets

In the area of data mining for finding frequent itemset from huge database, there exist a lot of algorithms, out of all Apriori algorithm is the base of all algorithms. In Uapriori algorithm each items existential probability is examined with a given support count, if it is greater or equal then these items are known as frequent items, otherwise these are known as infrequent itemsets. In this paper matrix technology has been introduced over Uapriori algorithm which reduces execution time and computational complexity for finding frequent itemset from uncertain transactional database. In the modern era, volume of data is increasing exponentially and highly optimized algorithm is needed for processing such a large amount of data in less time. The proposed algorithm can be used in the field of data mining for retrieving frequent itemset from a large volume of database by taking very less computation complexity.

Improved Mining Frequent Itemsets Algorithm Based on Sim

2013 ◽  
Vol 12 (11) ◽  
pp. 2246-2250 ◽  
Author(s):  
Jiang Yongchun ◽  
Li Xiaona ◽  
Cui Hairong ◽  
Xun Jiao ◽  
Wang Yingchun
Keyword(s):  
Frequent Itemsets ◽  
Mining Frequent Itemsets
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