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IncSPADE: an incremental sequential pattern mining algorithm based on SPADE property

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posted on 2016-06-19, 00:00 authored by O Adam, Z Abdullah, A Ngah, K Mokhtar, W M A Wan Ahmad, T Herawan, N Ahmad, M Mat Deris, A R Hamdan, Jemal AbawajyJemal Abawajy
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%.

History

Title of book

Advances in machine learning and signal processing

Volume

387

Series

Lecture notes in electrical engineering

Chapter number

8

Pagination

81 - 92

Publisher

Springer

Place of publication

Berlin, Germany

ISSN

1876-1100

ISBN-13

9783319322131

Language

eng

Publication classification

B Book chapter; BN Other book chapter, or book chapter not attributed to Deakin

Copyright notice

2016, Springer International Publishing Switzerland

Extent

27

Editor/Contributor(s)

P Soh, W Woo, H Sulaiman, M Othman, M Saat

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