FAST DISCOVERY OF LONG PATTERNS FOR ASSOCIATION RULES
Authors:
N. Mustapha a;
M. N. Sulaiman a;
M. Othman a;
M. H. Selamat a
| Affiliation: | a Faculty of Computer Science and Information Technology, University Putra Malaysia, 43400 Serdang, Selangor, Malaysia. |
DOI:
10.1080/0020716031000112376
Publication Frequency:
12 issues per year
Published in:
International Journal of Computer Mathematics,
Volume
80,
Issue
8
August
2003
, pages 967
- 976
Subjects:
Analysis - Mathematics;
Bioinformatics;
Computer Mathematics;
Discrete Mathematics;
Mathematical Finance;
Mathematical Logic;
Mathematical Numerical Analysis;
Systems & Computer Architecture;
Number of References: 12
Formats available:
PDF
(English)
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Abstract
The most time consuming process in discovering association rules is identifying the frequent patterns especially in the cases when the database contains long patterns. An algorithm called Flex for identifying frequent patterns especially efficient when the patterns are long is proposed by successive construction of the nodes lexicographic tree. The vertical counting strategy to facilitate fast discovery is used in support computation. The experimental result shows that Flex outperform Apriori, a well-known and widely used algorithm for patterns discovery.
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| Keywords: Data Mining; Frequent Patterns; Association Rules; Market Basket Analysis |
| view references (12) |

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