Name
Abstract | ||
|---|---|---|
We propose a data warehousing architecture for effective risk analysis in a banking scenario. The core of the architecture consists in two data mining tools for improving the quality of consolidated data during the acquisition process. Specifically, we deal with schema reconciliation, i.e. segmentation of a string sequence according to fixed attribute schema. To this purpose we present the RecBoost methodology which pursuits effective reconciliation via multiple, stages of classification. In addition, we propose a hash-based technique for data reconciliation, i.e. the recognition of apparently different records that, as a matter of fact, refer to the same real-world entity. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICDEW.2007.4401083 | ICDE Workshops |
Keywords | Field | DocType |
effective risk analysis,data reconciliation,schema reconciliation,fixed attribute schema,bank intelligence scenario,data mining tool,acquisition process,recboost methodology,data mining,pursuits effective reconciliation,data warehousing architecture,consolidated data,data warehousing,multidimensional systems,risk management,cryptography,warehousing,history,decision support systems,risk analysis,data warehouses | Data warehouse,Data mining,Architecture,Risk analysis (business),Computer science,Cryptography,Decision support system,Risk management,Hash function,Schema (psychology),Database | Conference |
ISSN | ISBN | Citations |
1943-2895 | 978-1-4244-0832-0 | 2 |
PageRank | References | Authors |
0.46 | 9 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gianni Costa | 1 | 235 | 24.04 |
| Francesco Folino | 2 | 202 | 21.57 |
| Antonio Locane | 3 | 18 | 1.45 |
| Giuseppe Manco | 4 | 918 | 68.94 |
| Riccardo Ortale | 5 | 282 | 27.46 |