Title :
Research on improving Apriori algorithm based on interested table
Author :
Wu, Libing ; Gong, Kui ; Guo, Fuliang ; Ge, Xiaohua ; Shan, Yilei
Author_Institution :
Sch. of Comput., Wuhan Univ., Wuhan, China
Abstract :
The Apriori algorithm is a most influential one to excavate association rules. The basic idea of the algorithm is: identify all the frequent itemsets to get association rule. This paper presents the improved Apriori algorithm based on interested items, which mainly construct an ordered interested table and traverse it to excavate frequent itemsets quickly. The paper also by writing c# code achieves the improved algorithm. Confirmed by many experiments, this algorithm is better than traditional algorithms in time consuming.
Keywords :
data mining; Apriori algorithm; excavate association rules; excavate frequent itemsets; Itemsets; Apriori algorithm; association rules; frequent itemsets; interested itemsets;
Conference_Titel :
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5537-9
DOI :
10.1109/ICCSIT.2010.5564134