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Research of Association Rule Mining Algorithm Based on Improved FP-Tree
Author(s) -
Zhuo Chen,
Lu nannan,
Shiqi Li,
Tao Han
Publication year - 2012
Publication title -
international journal of engineering and manufacturing
Language(s) - English
Resource type - Journals
eISSN - 2306-5982
pISSN - 2305-3631
DOI - 10.5815/ijem.2012.05.10
Subject(s) - association rule learning , data mining , gsp algorithm , computer science , tree (set theory) , set (abstract data type) , process (computing) , algorithm , tree structure , binary tree , interval tree , apriori algorithm , mathematics , mathematical analysis , programming language , operating system
Mining algorithm of FP-Tree is one of the most effective mining algorithms in association rule mining. It must produce large amounts of the candidate set and scan database repeatedly, but it generates conditional FPTree recursively in the process of mining frequent pattern and wastes the storage space greatly using the common tree's memory structure. It proposed an algorithm for mining frequent patterns by constructing reverse FP-tree with a binary tree storage structure. In mining process, it mines left son tree recursively, but gets frequent pattern not by generating conditional FP-Tree, so it greatly reduces the storage space and running time. The experiments show that the improved algorithm can realize effective mining on the time and space.

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