Mining frequent sequential patterns with first-occurrence forests

Authors:
Erich A. Peterson;Peiyi Tang
Affiliations:
University of Arkansas at Little Rock, Little Rock, AR;University of Arkansas at Little Rock, Little Rock, AR
Venue:
Proceedings of the 46th Annual Southeast Regional Conference on XX
Year:
2008

Citing 4
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Abstract

In this paper, a new pattern-growth algorithm is presented to mine frequent sequential patterns using First-Occurrence Forests (FOF). This algorithm uses a simple list of pointers to the first-occurrences of a symbol in the aggregate tree [1], as the basic data structure for database representation, and does not rebuild aggregate trees for projection databases. The experimental evaluation shows that our new FOF mining algorithm outperforms the PLWAP-tree mining algorithm [2] and the FLWAP-tree mining algorithm [3], both in the mining time and the amount of memory used.