CFP-tree: A compact disk-based structure for storing and querying frequent itemsets
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摘要
Frequent itemset mining is an important problem in the data mining area with a wide range of applications. Many decision support systems need to support online interactive frequent itemset mining, which is a challenging task because frequent itemset mining is a computation intensive repetitive process. One solution is to precompute frequent itemsets. In this paper, we propose a compact disk-based data structure—CFP-tree to store precomputed frequent itemsets on a disk to support online mining requests. The CFP-tree structure effectively utilizes the redundancy in frequent itemsets to save space. The compressing ratio of a CFP-tree can be as high as several thousands or even higher. Efficient algorithms for retrieving frequent itemsets from a CFP-tree, as well as efficient algorithms to construct and maintain a CFP-tree, are developed. Our performance study demonstrates that with a CFP-tree, frequent itemset mining requests can be responded to promptly.
论文关键词:Frequent itemset mining,Online interactive mining
论文评审过程:Received 24 October 2005, Accepted 2 November 2005, Available online 5 December 2005.
论文官网地址:https://doi.org/10.1016/j.is.2005.11.004