IncSPADE
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Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
Springer International Publishing Switzerland
Abstract
In 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%.
Description
Keywords
Sequential pattern, Incremental, Updatable, Database