DocumentCode
2076467
Title
An improved association rule algorithm based on trie and inverted index
Author
Wei, Zhao ; Jinzhe, Jin
Author_Institution
Jilin Agric. Univ., Changchun, China
fYear
2011
fDate
16-18 Dec. 2011
Firstpage
1669
Lastpage
1672
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on
Conference_Location
Changchun
Print_ISBN
978-1-4577-1700-0
Type
conf
DOI
10.1109/TMEE.2011.6199532
Filename
6199532
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