4.2 Article

Research of Improved FP-Growth Algorithm in Association Rules Mining

Journal

SCIENTIFIC PROGRAMMING
Volume 2015, Issue -, Pages -

Publisher

HINDAWI LTD
DOI: 10.1155/2015/910281

Keywords

-

Funding

  1. Fundamental Research Funds for the Central Universities [XDJK2009C027]
  2. Science & Technology Project [2013001287]

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

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