英文摘要 |
Mining association rules is one of the most important problems in data mining. Its aim is to discover the associations between items in a large database of sales transactions. In the past, a large number of algorithms for mining association rules have been proposed, and the FP-tree algorithm is one of the most famous ones, known for its efficiency. Unlike the traditional approach that requires many phases of candidate itemsets generation and database scan, the FP-tree algorithm compresses and stores the entire database into a sophisticated tree structure, called FP-tree, by which all the associations can be found by two database scans. In this paper, we attempt to further improve the standard structure of the FP-tree such that the mining performance can be improved. To this end, three variants of the improved FP-tree algorithm are proposed. The first variant is called FP-tree+tail, which adds a tail pointer into the head table of the original FP-tree structure. The second is named as FP-tree hash, which adds a hash table into every node of the FP-tree. Finally, we call the last FP-treel1ash+tail, which is a combination of the first two improvements. Finally, a performance evaluation is done to compare their performances. The result indicates that the three proposed algorithms are about 20-50 times faster than the original FP-tree algorithm. |