Smart frequent itemsets mining algorithm based on FP-tree and DIFFset data   structures

George GATUHA; Tao JIANG

Makale detayları

Smart frequent itemsets mining algorithm based on FP-tree and DIFFset data structures

Yazarlar:

George GATUHA | Tao JIANG

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 3, pp.2096-2107

Belge Tipi:

Makale

Yayın Tarihi:

5/2017

Belge Dili:

Türkçe

Document ID (Org No.):

2000740847

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

Association rule data mining is an important technique   for finding important relationships in large datasets. Several frequent   itemsets mining techniques have been proposed using a prefix-tree structure,   FP-tree, a compressed data structure for database representation. The   DIFFset data structure has also been shown to significantly reduce the run   time and memory utilization of some data mining algorithms. Experimental   results have demonstrated the efficiency of the two data structures in   frequent itemsets mining. This work proposes FDM, a new algorithm based on   FP-tree and DIFFset data structures for efficiently discovering frequent   patterns in data. FDM can adapt its characteristics to efficiently mine long   and short patterns from both dense and sparse datasets. Several optimization   techniques are also outlined to increase the efficiency of FDM. An   evaluation of FDM against three frequent itemset data mining algorithms,   dEclat, FP-growth, and FDM* (FDM without optimization), was performed using   datasets having both long and short frequent patterns. The experimental   results show significant improvement in performance compared to the   FP-growth, dEclat, and FDM* algorithms.

Makale detayları

Smart frequent itemsets mining algorithm based on FP-tree and DIFFset data structures

Yazarlar: George GATUHA | Tao JIANG

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 3, pp.2096-2107

Belge Tipi: Makale

Yayın Tarihi: 5/2017

Belge Dili: Türkçe

Document ID (Org No.): 2000740847

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

George GATUHA | Tao JIANG

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 3, pp.2096-2107

Belge Tipi:

Makale

Yayın Tarihi:

5/2017

Belge Dili:

Türkçe

Document ID (Org No.):

2000740847

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632