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IncSPADE: an incremental sequential pattern mining algorithm based on SPADE property
conference contribution
posted on 2016-01-01, 00:00 authored by O Adam, Z Abdullah, A Ngah, K Mokhtar, W M A W Ahmad, T Herawan, N Ahmad, M M Deris, A R Hamdan, Jemal AbawajyJemal AbawajyIn this paper we propose Incremental Sequential PAttern Discovery using Equivalence classes (IncSPADE) algorithm to mine the dynamic database without the requirement of re-scanning the database again. In order to evaluate this algorithm, we conducted the experiments against three different artificial datasets. The result shows that IncSPADE outperformed the benchmarked algorithm called SPADE up to 20%.
History
Event
Malaysia Technical Scientist Association. Conference (2015 : Ho Chi Minh City, Vietnam)Volume
387Series
Malaysia Technical Scientist Association ConferencePagination
81 - 92Publisher
SpringerLocation
Ho Chi Minh City, VietnamPlace of publication
Cham, SwitzerlandPublisher DOI
Start date
2015-12-15End date
2015-12-17ISSN
1876-1100eISSN
1876-1119ISBN-13
9783319322124Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2016, Springer International Publishing SwitzerlandEditor/Contributor(s)
P Soh, W Woo, H Sulaiman, M Othman, M SaatTitle of proceedings
2015 International Conference on Machine Learning and Signal ProcessingUsage metrics
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