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

Adam, Omer, Abdullah, Zailani, Ngah, Amir, Mokhtar, Kasypi, Wan Ahmad, Wan Muhamad Amir, Herawan, Tutut, Ahmad, Noraziah, Mat Deris, Mustafa, Hamdan, Abdul Razak and Abawajy, Jemal 2016, IncSPADE: an incremental sequential pattern mining algorithm based on SPADE property. In Soh, Ping Jack, Woo, Wai Lok, Sulaiman, Hamzah Asyrani, Othman, Mohd Azlishah and Saat, Mohd Shakir (ed), Advances in machine learning and signal processing, Springer, Berlin, Germany, pp.81-92, doi: 10.1007/978-3-319-32213-1_8.

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Title IncSPADE: an incremental sequential pattern mining algorithm based on SPADE property
Author(s) Adam, Omer
Abdullah, Zailani
Ngah, Amir
Mokhtar, Kasypi
Wan Ahmad, Wan Muhamad Amir
Herawan, Tutut
Ahmad, Noraziah
Mat Deris, Mustafa
Hamdan, Abdul Razak
Abawajy, JemalORCID iD for Abawajy, Jemal orcid.org/0000-0001-8962-1222
Title of book Advances in machine learning and signal processing
Editor(s) Soh, Ping Jack
Woo, Wai Lok
Sulaiman, Hamzah Asyrani
Othman, Mohd Azlishah
Saat, Mohd Shakir
Publication date 2016
Series Lecture notes in electrical engineering
Chapter number 8
Total chapters 27
Start page 81
End page 92
Total pages 12
Publisher Springer
Place of Publication Berlin, Germany
Keyword(s) sequential pattern
incremental
updatable
database
Summary 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%.
Notes Proceedings of MALSIP 2015
ISBN 9783319322131
9783319322124
ISSN 1876-1100
Language eng
DOI 10.1007/978-3-319-32213-1_8
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category B1 Book chapter
ERA Research output type B Book chapter
Copyright notice ©2016, Springer International Publishing Switzerland
Persistent URL http://hdl.handle.net/10536/DRO/DU:30084448

Document type: Book Chapter
Collection: School of Information Technology
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