1. CFP-tree: A compact disk-based structure for storing and querying frequent itemsets
- Author
-
Guimei Liu, Hongjun Lu, and Jeffrey Xu Yu
- Subjects
Structure (mathematical logic) ,Decision support system ,Computer science ,Compact disc ,Process (computing) ,InformationSystems_DATABASEMANAGEMENT ,Construct (python library) ,computer.software_genre ,Tree (data structure) ,Task (computing) ,ComputingMethodologies_PATTERNRECOGNITION ,Hardware and Architecture ,Redundancy (engineering) ,Data mining ,computer ,Software ,Information Systems - Abstract
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.
- Published
- 2007