IncSPADE: An Incremental Sequential Pattern Mining Algorithm Based on SPADE Property

• Main Authors: Omer, Adam, Zailani, Abdullah, Amir, Ngah, Kasypi, Mokhtar, Wan Muhamad Amir, Wan Ahmad, Herawan, Tutut, Noraziah, Ahmad, Mustafa, Mat Deris, Abdul Razak, Hamdan
• Format: Book Section
• Language: English
• Published: Springer International Publishing 2016
• Subjects: QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/13563/1/IncSPADE-%20An%20Incremental%20Sequential%20Pattern%20Mining%20Algorithm%20Based%20on%20SPADE%20Property.pdf; http://umpir.ump.edu.my/id/eprint/13563/; http://dx.doi.org/10.1007/978-3-319-32213-1_8
• Institution: Universiti Malaysia Pahang

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%.