The Research and Application of Association Rules Algorithm
Shu Juan Zhang, Qing Wang
Abstract
Shu Juan Zhang, Qing Wang
Abstract
Through the research of the association rules mining technology and Apriori algorithm, the defects are found in Apriori algorithm. In view of the deficiencies, an improved algorithm is proposed. The algorithm scans database only once, and efficiently reduces the I/O time. The matrix of frequent itemsets is used to store and reduce the transaction data, which saves the storage space. By comparison of Apriori algorithm and improved algorithm, the results of experiments show that the efficiency of the improved algorithm is increased. Finally, an application example of the association rules is given. The improved algorithm is introduced to book lending deal. The rules among the book-borrowed are discovered and analyzed.
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Through the research of the association rules mining technology and Apriori algorithm, the defects are found in Apriori algorithm. In view of the deficiencies, an improved algorithm is proposed. The algorithm scans database only once, and efficiently reduces the I/O time. The matrix of frequent itemsets is used to store and reduce the transaction data, which saves the storage space. By comparison of Apriori algorithm and improved algorithm, the results of experiments show that the efficiency of the improved algorithm is increased. Finally, an application example of the association rules is given. The improved algorithm is introduced to book lending deal. The rules among the book-borrowed are discovered and analyzed.
Key concepts: Apriori algorithm, Association rule learning, Data mining, Database transaction, GSP Algorithm, Computer science, Algorithm, A priori and a posteriori