![](bg8.png)
have applied the constraint programming models to
the MSNBC database from the UCI repository, hav-
ing successful results.
Our models where simple enough to work with
academic examples, but further experimentation is re-
quired, focussing on escalation (both: length of trans-
action and database size). In this sense, our research
is directed towards the use of reified constraints that
optimize the constraint programming model.
Note that we have presented two independent
models: one for mining item repetitions within item-
sets and another one or mining the itemsets with or-
der relations. The combination of both can lead us
into a complete sequence patter mining. Once the
combination is done, this model will be equiparable
to classical algorithms used nowadays like prefixspan
or clospan with the advantage of being declarative and
easily extensible.
ACKNOWLEDGEMENTS
This work is supported by the research projects
CTQ2008-06865-C02-02 and DPI2011-24929, and
the grant FPU-AP2009-2831, all of them funded
by the Spanish Government. The MSNBC dataset
has been extracted from the UCI Machine Reposi-
tory (Frank and Asuncion, 2010).
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