P. Cotofrei and K. Stoffel (Switzerland)
data mining, temporal reasoning,
classification trees, C4.5, temporal rules
Due to the wide availability of huge data collection
comprising multiple sequences that evolve over time, the
process of adapting the classical data-mining techniques,
making them capable to work into this new context,
becomes today a strong necessity. Having as final goal the
extraction of temporal rules from time series databases,
we proposed in this article a methodology permitting the
application of a classification tree on sequential raw data
by the use of a flexible approach of the main terms as
“classification class”, “training set”, “attribute set”, etc.
We described also a first implementation of this
methodology and presented some results on a synthetic
time series database.