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

fYear

2011

fDate

8-10 Aug. 2011

Firstpage

1908

Lastpage

1911

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/AIMSEC.2011.6010883

Filename

6010883