Improvement for the Apriori Algorithm
Zhun Zhou
Abstract
Zhun Zhou
Abstract
Data mining is the process of discovering hidden structure or patterns in large quantities of data by using kinds of analytic tools. The paper provides a survey of the study in association rule generation. On the basis of mining association rules theory,Apriori algorithm is analyzed,and an improved Apriori algorithm is proposed. The new Apriori algorithm has the advantages of less record numbers,high efficiency and certain practical significance.
OpenAlex reports 1 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.
Data mining is the process of discovering hidden structure or patterns in large quantities of data by using kinds of analytic tools. The paper provides a survey of the study in association rule generation. On the basis of mining association rules theory,Apriori algorithm is analyzed,and an improved Apriori algorithm is proposed. The new Apriori algorithm has the advantages of less record numbers,high efficiency and certain practical significance.
Key concepts: Apriori algorithm, Association rule learning, Computer science, A priori and a posteriori, Data mining, GSP Algorithm, Process (computing), Algorithm