Non-redundant rare itemset generation
| aut.conference.type | Paper Published in Proceedings | |
| aut.relation.endpage | 74 | |
| aut.relation.pages | 6 | |
| aut.relation.startpage | 69 | |
| aut.relation.volume | 101 | |
| dc.contributor.author | Koh, YS | |
| dc.contributor.author | Pears, R | |
| dc.contributor.editor | Kennedy, P | |
| dc.contributor.editor | Ong, K-L | |
| dc.contributor.editor | Christen, P | |
| dc.date.accessioned | 2013-02-26T04:31:19Z | |
| dc.date.available | 2013-02-26T04:31:19Z | |
| dc.date.copyright | 2009 | |
| dc.date.issued | 2009 | |
| dc.description.abstract | Rare itemsets are likely to be of great interest because they often relate to high-impact transactions which may give rise to rules of great practical signi cance. Research into the rare association rule mining problem has gained momentum in the recent past. In this paper, we propose a novel approach that captures such rare rules while ensuring that redundant rules are eliminated. Extensive testing on real-world datasets from the UCI repository con rm that our approach outperforms both the Apriori-Inverse(Koh et al. 2006) and Relative Support (Yun et al. 2003) algorithms. | |
| dc.identifier.citation | 2009 Australasian Data Mining Conference , Melbourne, Australia, published in: Proceeding of the 2009 Australasian Data Mining Conference, vol.101, pp.69 - 74 (6) | |
| dc.identifier.roid | 14244 | en_NZ |
| dc.identifier.uri | https://hdl.handle.net/10292/5180 | |
| dc.publisher | Australian Computer Society (ACS) | |
| dc.relation.uri | http://crpit.com/confpapers/CRPITV101Koh.pdf | |
| dc.rights | Copyright © 2009, Australian Computer Society, Inc. This paper appeared at the Eighth Australasian Data Mining Conference (AusDM 2009), Melbourne, Australia. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 101, Paul J. Kennedy, Kok-Leong Ong and Peter Christen, Ed. Reproduction for academic, not-for pro t purposes permitted provided this text is included. | |
| dc.rights.accessrights | OpenAccess | |
| dc.subject | Rare Association Rule Mining | |
| dc.subject | Apriori-Inverse | |
| dc.subject | Non-Redundant Itemset | |
| dc.title | Non-redundant rare itemset generation | |
| dc.type | Conference Contribution | |
| pubs.elements-id | 4878 | |
| pubs.organisational-data | /AUT | |
| pubs.organisational-data | /AUT/Design & Creative Technologies | |
| pubs.organisational-data | /AUT/Design & Creative Technologies/School of Computing & Mathematical Science | |
| pubs.organisational-data | /AUT/PBRF Researchers | |
| pubs.organisational-data | /AUT/PBRF Researchers/Design & Creative Technologies PBRF Researchers | |
| pubs.organisational-data | /AUT/PBRF Researchers/Design & Creative Technologies PBRF Researchers/DCT C & M Computing |