Title :
An improved association rule algorithm based on trie and inverted index
Author :
Wei, Zhao ; Jinzhe, Jin
Author_Institution :
Jilin Agric. Univ., Changchun, China
Abstract :
Because of the rapid growth in worldwide information, efficiency of association rules mining has been concerned for several years. In this paper, based on the original Apriori algorithm, an improved algorithm TIIA (Trie-Inverted-Index-Apriori) is proposed. TIIA adopts trie and inverted index structure to store the whole transactions with one scanning of transactions, generate frequent itemsets rapidly and also directly find frequent k itemsets. Experiments demonstrate that TIIA outperforms the original Apriori.
Keywords :
data mining; Apriori algorithm; TIIA; association rule algorithm; association rules mining; frequent itemset generation; transaction scanning; trie-inverted index structure; trie-inverted-index-apriori; Algorithm design and analysis; Association rules; Data structures; Indexes; Itemsets; apriori algorithm; association rule; frequent itemset; inverted index; trie;
Conference_Titel :
Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4577-1700-0
DOI :
10.1109/TMEE.2011.6199532
