Database Reference
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6
Conclusions
In this chapter we provided an overview of classes of constraints, algorithms for
solving constraint-based mining problems and languages for specifying contraint-
based mining tasks.
The trend in constraint-based mining has been to build increasingly generic sys-
tems. While initially constraint-based mining systems provided special purpose
languages that only supported slightly more constraints than specialized frequent
itemset mining algorithms did, in recent years the range of constraints has ex-
panded, as well as the genericity of the languages supporting constraint-based
mining, culminating in the integration with generic constraint satisfaction systems
and languages.
Several open challenges remain. These include a closer integration of constraint-
based mining with pattern set mining, getting a better understanding of how to
integrate statistical requirements in constraint-based mining systems, and mining
structured databases such as graph or sequence databases using sufficiently generic
languages.
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