FGC: an efficient constraint-based frequent set miner
| aut.conference.type | Paper Published in Proceedings | |
| aut.relation.endpage | 431 | |
| aut.relation.startpage | 424 | |
| dc.contributor.author | Pears, R | |
| dc.contributor.author | Kutty, S | |
| dc.date.accessioned | 2013-02-26T04:37:34Z | |
| dc.date.available | 2013-02-26T04:37:34Z | |
| dc.date.copyright | 2007 | |
| dc.date.issued | 2007 | |
| dc.description.abstract | Despite advances in algorithmic design, association rule mining remains problematic from a performance viewpoint when the size of the underlying transaction database is large. The well-known a priori approach, while reducing the computational effort involved still suffers from the problem of scalability due to its reliance on generating candidate itemsets. In this paper we present a novel approach that combines the power of preprocessing with the application of user-defined constraints to prune the itemset space prior to building a compact FP-tree. Experimentation shows that that our algorithm significantly outperforms the current state of the art algorithm, FP-bonsai. | |
| dc.identifier.citation | 2007 ACS/IEEE International Conference on Computer Systems and Applications. AICCSA , Amman, Jordan, published in: Proceedings of the 2007 ACS/IEEE International Conference on Computer Systems and Applicationsm AICCSA, pp.424 - 431 | |
| dc.identifier.doi | 10.1109/AICCSA.2007.370916 | |
| dc.identifier.roid | 5871 | en_NZ |
| dc.identifier.uri | https://hdl.handle.net/10292/5184 | |
| dc.publisher | IEEE | |
| dc.rights | Copyright © 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
| dc.rights.accessrights | OpenAccess | |
| dc.title | FGC: an efficient constraint-based frequent set miner | |
| dc.type | Conference Contribution | |
| pubs.elements-id | 6063 | |
| 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 |