Using unknowns to prevent discovery of association rules
| dc.citation.epage | 54 | en_US |
| dc.citation.issueNumber | 4 | en_US |
| dc.citation.spage | 45 | en_US |
| dc.citation.volumeNumber | 30 | en_US |
| dc.contributor.author | Saygin, Y. | en_US |
| dc.contributor.author | Verykios V.S. | en_US |
| dc.contributor.author | Clifton, C. | en_US |
| dc.date.accessioned | 2016-02-08T10:34:03Z | |
| dc.date.available | 2016-02-08T10:34:03Z | |
| dc.date.issued | 2001 | en_US |
| dc.department | Department of Computer Engineering | en_US |
| dc.description.abstract | Data mining technology has given us new capabilities to identify correlations in large data sets. This introduces risks when the data is to be made public, but the correlations are private. We introduce a method for selectively removing individual values from a database to prevent the discovery of a set of rules, while preserving the data for other applications. The efficacy and complexity of this method are discussed. We also present an experiment showing an example of this methodology. | en_US |
| dc.description.provenance | Made available in DSpace on 2016-02-08T10:34:03Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2001 | en |
| dc.identifier.issn | 1635808 | |
| dc.identifier.uri | http://hdl.handle.net/11693/24765 | |
| dc.language.iso | English | en_US |
| dc.source.title | SIGMOD Record | en_US |
| dc.title | Using unknowns to prevent discovery of association rules | en_US |
| dc.type | Article | en_US |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Using unknowns to prevent discovery of association rules.pdf
- Size:
- 948.72 KB
- Format:
- Adobe Portable Document Format
- Description:
- Full printable version