Research of Improved FP-Growth Algorithm in Association Rules Mining

Abstract EN

Association rules mining is an important technology in data mining.

FP-Growth(frequent-pattern growth) algorithm is a classical algorithm in association rules mining.

But the FP-Growth algorithm in mining needs two times to scan database, which reduces the efficiency of algorithm.

Through the study of association rules mining and FP-Growth algorithm, we worked out improvedalgorithms of FP-Growth algorithm—Painting-Growth algorithm and N (not) Painting-Growth algorithm(removes the painting steps, and uses another way to achieve).

We compared two kinds of improved algorithmswith FP-Growth algorithm.

Experimental results show that Painting-Growth algorithm is more than 1050 and NPainting-Growth algorithm is less than 10000 in data volume; the performance of the two kinds of improvedalgorithms is better than that of FP-Growth algorithm.