An Efficient Algorithm for Mining Association Rules in Large Databases 论文

1995引用 1600
Data Mining Algorithms and ApplicationsRough Sets and Fuzzy LogicAlgorithms and Data Compression

摘要

Mining for a.ssociation rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an effi-cient algorithm for mining association rules that is fundamentally different from known al-gorithms. Compared to previous algorithms, our algorithm not only reduces the I/O over-head significantly but also has lower CPU overhead for most cases. We have performed extensive experiments and compared the per-formance of our algorithm with one of the best existing algorithms. It was found that for large databases, the CPU overhead was re-duced by as much as a factor of four and I/O was reduced by almost an order of magnitude. Hence this algorithm is especially suitable for very large size databases. 1