Modified BitApriori Algorithm: An Intelligent Approach for Mining Frequent Item-Set
نویسندگان
چکیده
In data mining frequent item-sets mining is one of the important tasks. Apriori is used to mine the frequent item-sets but, Apriori also has some problem as in Apriori finding of support count is very time consuming procedure. To overcome this problem of Apriori, BitApriori algorithm is proposed for mining frequent item-sets, but the BitApriori also suffer the problem of memory scarcity when the database is large, and BitApriori is also not effective when Trie data structure has many nodes from the root nodes .To improve the efficiency of BitApriori a Modified BitApriori for mining frequent item-sets is proposed. In Modified BitAprioriTrie data structure is used to find the frequent item-sets. The support count can be calculated by performing the Bitwise “or” operation on the binary string. If two items have equal support then pruning is used in Modified BitApriori. In this paper Modified BitApriori has more performance then BitApriori, Modified BitApriori performs the better Experimental results.
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