A max-min approach for hiding frequent itemsets
dc.creator | Moustakides, G. V. | en |
dc.creator | Verykios, V. S. | en |
dc.date.accessioned | 2015-11-23T10:39:59Z | |
dc.date.available | 2015-11-23T10:39:59Z | |
dc.date.issued | 2006 | |
dc.identifier.isbn | 769527027 | |
dc.identifier.issn | 15504786 | |
dc.identifier.uri | http://hdl.handle.net/11615/31168 | |
dc.description.abstract | In this paper we are proposing a new algorithmic approach for sanitizing raw data from sensitive knowledge in the context of mining of association rules. The new approach (a) relies on the maxmin criterion which is a method in decision theory for maximizing the minimum gain and (b) builds upon the border theory of frequent itemsets. © 2006 IEEE. | en |
dc.source.uri | http://www.scopus.com/inward/record.url?eid=2-s2.0-48649086773&partnerID=40&md5=7d854f2dc61e41401fe858a2087e8c9c | |
dc.subject | Algorithmic approach | en |
dc.subject | Frequent Itemsets | en |
dc.subject | Max-min | en |
dc.subject | Maxmin criteria | en |
dc.subject | New approaches | en |
dc.subject | Associative processing | en |
dc.subject | Data mining | en |
dc.subject | Decision theory | en |
dc.subject | Technical presentations | en |
dc.title | A max-min approach for hiding frequent itemsets | en |
dc.type | conferenceItem | en |
Dateien zu dieser Ressource
Dateien | Größe | Format | Anzeige |
---|---|---|---|
Zu diesem Dokument gibt es keine Dateien. |