An Improvement of Apriori Algorithm Based on Matrix
Zhou Xing-bin
Abstract
Zhou Xing-bin
Abstract
Mining association rule is a very important facet for data mining,while Apriori algorithm is classic algorithm for association rule.The paper analyzes the classic Apriori algorithm first,then modifies it based on matrix and compresses the matrix based on transaction compression.The modified algorithm obviously improves the efficency of 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.
Mining association rule is a very important facet for data mining,while Apriori algorithm is classic algorithm for association rule.The paper analyzes the classic Apriori algorithm first,then modifies it based on matrix and compresses the matrix based on transaction compression.The modified algorithm obviously improves the efficency of Apriori algorithm.
Key concepts: Apriori algorithm, Association rule learning, Computer science, Data mining, Database transaction, A priori and a posteriori, Algorithm, Matrix (chemical analysis)