Name
Abstract | ||
|---|---|---|
Most approaches to mining association rules implicitly consider the utilities of the itemsets to be equal. We assume that the utilities of itemsets may differ, and identify the high utility itemsets based on information in the transaction database and external information about utilities. Our theoretical analysis of the resulting problem lays the foundation for future utility mining algorithms. |
Year | Venue | Keywords |
|---|---|---|
2004 | SIAM Proceedings Series | association rule |
Field | DocType | Citations |
Utility mining,Data mining,Information retrieval,Computer science,Association rule learning,Database transaction | Conference | 147 |
PageRank | References | Authors |
6.10 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hong Yao | 1 | 342 | 17.23 |
| Howard J. Hamilton | 2 | 1501 | 145.55 |
| Cory J. Butz | 3 | 383 | 40.80 |