Abstract:
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The discovery of frequent sequential patterns in an ordered collection
of data, such as sequential databases or time-series data, is an important issue
in several contexts. In this paper, we employ formal concept
analysis to develop the notion of closure for these sequential
patterns and to characterize the concept lattice of the ordered
contexts. The proposed concept lattice will serve as a model
for the patterns extracted in the context of sequential databases
by a recent algorithm (CloSpan, cite{Clospan}). Finally,
we will show how we can also use our model to derive other kind of
structured patterns, like the closed
set of episodes in the context of time-series data cite{Toivonen}.
So, the convenient transformation of the sequential patterns
in the concepts of the lattice will give rise to the most representative
set of parallel and serial closed episodes. |