An On-Line Approximation Algorithm for Mining Frequent Closed Itemsets Based on Incremental Intersection
Koji Iwanuma, Yoshitaka Yamamoto, Fukuda, Shoshi · Movebank · 2016
We propose a new on-line e-approximation algorithm for mining closed itemsets from a transactional data stream, which is also based on the incremental/cumulative intersection principle. The proposed algorithm, called LC-CloStream, is constructed by integrating CloStream algorithm and Lossy Counting algorithm. We investigate some behaviors of the LC-CloStream algorithm. Firstly we show the incompleteness and the semi-completeness for mining all frequent closed itemsets in a stream. Next, we give the completeness of eapproximation for extracting frequent itemsets.