Improving Efficiency of Sequence Mining by Combining First Occurrence Forest (FOF) Strategy and Sibling Principle

Date

2014-06-04

Author

Onal, Kezban Dilek
Karagöz, Pınar

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Sequential pattern mining is one of the basic problems in data mining and it has many applications in web mining. The WAP-Tree (Web Access Pattern Tree) data structure provides a compact representation of single-item sequence databases. WAP-Tree based algorithms have shown notable execution time and memory consumption performance on mining single-item sequence databases. We propose a new algorithm FOF-SP, a WAP-Tree based algorithm which combines an early prunning strategy called "Sibling Principle" from the literature and FOF (First Occurrence Forest) strategy. Experimental results revealed that FOF-SP finds patterns faster than previous WAP-Tree based algorithms PLWAP and FOF. Moreover, FOF-SP can mine patterns faster than PrefixSpan and as fast as LAPIN on real sequence databases from web usage mining and bioinformatics.

Subject Keywords

WAP-Tree, Sequence mining, Sibling principle, FOF, FOF-SP

URI

https://hdl.handle.net/11511/34430

Collections

Department of Computer Engineering, Conference / Seminar