Name
Abstract | ||
|---|---|---|
Association rule is one of the data mining techniques involved in discovering information that represents the association among data. Data in the database sometimes appear infrequent but highly associated with a specific data. This paper proposes a technique for significant rare data by introducing second support in discovering the association rules of such data. We show that the proposed approach provides better performance as compared to standard association rules techniques. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1080/00207160500113330 | INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS |
Keywords | Field | DocType |
association rules, significant rare data, data mining, second support | Data mining,Association rule learning,Mathematics,K-optimal pattern discovery | Journal |
Volume | Issue | ISSN |
83 | 1 | 0020-7160 |
Citations | PageRank | References |
7 | 0.65 | 2 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. D. Mustafa | 1 | 7 | 0.65 |
| N. F. Nabila | 2 | 7 | 0.65 |
| D. J. Evans | 3 | 634 | 247.93 |
| M. Y. Mohd-Saman | 4 | 9 | 2.79 |
| A. Mamat | 5 | 7 | 0.99 |