Name
Abstract | ||
|---|---|---|
AbstractAssociation 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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1155/2015/910281 | Periodicals |
Field | DocType | Volume |
Data mining,Dinic's algorithm,Hybrid algorithm,Algorithmics,Computer science,GSP Algorithm,In-place algorithm,Algorithm,FSA-Red Algorithm,Population-based incremental learning,Weighted Majority Algorithm | Journal | 2015 |
Issue | ISSN | Citations |
1 | 1058-9244 | 4 |
PageRank | References | Authors |
0.51 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yi Zeng | 1 | 192 | 30.94 |
| Shiqun Yin | 2 | 18 | 5.45 |
| Jiangyue Liu | 3 | 4 | 0.51 |
| Miao Zhang | 4 | 38 | 7.75 |