AN IMPROVED APRIORI ALGORITHM BY REORDERING ITEMSETS
Meiling Liu
Abstract
Meiling Liu
Abstract
The Apriori algorithm is a classical algorithm for mining association rules.In this paper,we deeply study the idea of the Apriori algorithm,and present an improved algorithm by reordering itemsets,called ImpApri.The number of candidate itemsets can be largely reduced,and its efficiency is higher than that of the original Apriori algorithm.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The Apriori algorithm is a classical algorithm for mining association rules.In this paper,we deeply study the idea of the Apriori algorithm,and present an improved algorithm by reordering itemsets,called ImpApri.The number of candidate itemsets can be largely reduced,and its efficiency is higher than that of the original Apriori algorithm.
Key concepts: Apriori algorithm, Association rule learning, A priori and a posteriori, Computer science, Data mining, Algorithm, GSP Algorithm, Philosophy