Title :
An improved Apriori algorithm based on pruning optimization and transaction reduction
Author :
Chen, Zhuang ; Cai, Shibang ; Song, Qiulin ; Zhu, Chonglai
Author_Institution :
Coll. of Comput. Sci. & Eng., Chongqing Univ. of Technol., Chongqing, China
Abstract :
The paper analyzes the basic ideas and the shortcomings of Apriori algorithm, studies the current major improvement strategies of it. In order to solve the low performance and efficiency of the algorithm caused by its generating lots of candidate sets and scanning the transaction database repeatedly, it studies the pruning optimization and transaction reduction strategies, and on this basis, the improved Apriori algorithm based on pruning optimization and transaction reduction is put forward. According to the performance comparison in the simulation experiment, by using the improved algorithm, the number of frequent item sets is much less and the running time is significantly shortened as well as the performance is enhanced then finally the algorithm is improved.
Keywords :
data mining; optimisation; Apriori algorithm improvement; data mining; pruning optimization reduction; pruning transaction reduction; transaction database; Algorithm design and analysis; Association rules; Itemsets; Optimization; Apriori; frequent itemsets; pruning optimization; transaction reduction;
Conference_Titel :
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location :
Deng Leng
Print_ISBN :
978-1-4577-0535-9
DOI :
10.1109/AIMSEC.2011.6010883
