Name
Abstract | ||
|---|---|---|
Mining generalized frequent item sets is one of important research area in data mining. Because not only the taxonomy data is widely exist, but also the information provided by the generalized frequent item sets is richer and valuable than the traditional frequent item sets. Like the traditional mining, the number of the generalized frequent item set is also very large, which make it difficult to do further analysis. We propose a new method called CGIP-summary, which represent the whole frequent generalized item sets by a set profiles and the profiles used to more concise. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICCSE.2012.21 | C3S2E |
Keywords | Field | DocType |
traditional frequent item set,new concise representation method,profile summary,set profile,concise representation method,cgip-summary method,taxonomy data,frequent item set,set theory,generalized frequent itemsets,generalized frequent itemset mining,important research area,generalized frequent itemset,data mining,taxnomy,closed generalized itemset profile summary,whole frequent generalized item,generalized frequent item set,traditional mining,new method | Set theory,Data mining,Computer science | Conference |
ISSN | ISBN | Citations |
1949-0828 | 978-0-7695-4914-9 | 0 |
PageRank | References | Authors |
0.34 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu-xing Mao | 1 | 16 | 2.65 |
| Zhang Chenghong | 2 | 22 | 7.07 |
| Hong Ling | 3 | 118 | 11.94 |