Integrating fuzziness into OLAP for multidimensional fuzzy association rules mining
| dc.contributor.author | Alhajj, Reda | |
| dc.contributor.author | Kaya, Mehmet | |
| dc.date.accessioned | 2026-08-12T16:08:54Z | |
| dc.date.issued | 2003 | |
| dc.department | Fırat Üniversitesi | |
| dc.description | 3rd IEEE International Conference on Data Mining, ICDM '03 -- 19 November 2003 through 22 November 2003 -- Melbourne, FL -- 82450 | |
| dc.description.abstract | This paper contributes to the ongoing research on multidimensional online association rules mining by proposing a general architecture that utilizes a fuzzy data cube for knowledge discovery. Three different methods are introduced to mine fuzzy association rules in the constructed fuzzy data cube, namely single dimension, multidimensional and hybrid association rules mining. Experimental results obtained for each of the three methods on the adult data of the United States census in 2000 show their effectiveness and applicability. © 2003 IEEE. | |
| dc.description.sponsorship | IEEE Comput. Soc. Tech. Comm. Comput. Intell. (TCCI); IEEE Comput. Soc. Tech. Comm. Pattern; Anal. Mach. Intell. (TCPAMI) | |
| dc.identifier.endpage | 472 | |
| dc.identifier.isbn | 0769519784 | |
| dc.identifier.isbn | 978-076951978-4 | |
| dc.identifier.issn | 1550-4786 | |
| dc.identifier.scopus | 2-s2.0-33644935351 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.startpage | 469 | |
| dc.identifier.uri | https://hdl.handle.net/11508/41479 | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.relation.ispartof | Proceedings - IEEE International Conference on Data Mining, ICDM | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_Scopus_20260511 | |
| dc.title | Integrating fuzziness into OLAP for multidimensional fuzzy association rules mining | |
| dc.type | Conference Object |
