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@@ -8,14 +8,41 @@ In the context of this package, modal logic helps us highlight complex relations
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The idea is to discretize complex data into relational objects called *Kripke models*, each of which consists of many propositional models called *worlds*, and expliciting the relations between worlds. In this way, it is possible to mine complex [`Itemset`](@ref), including a certain subset of [`Item`](@ref) that are true on a target world, but also *modally enhanced* items that are true on related worlds.
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A picture is worth a thousand words. Here you are a slightly more complex example, with respect to the one at the top of [`Getting started`](@ref getting-started) section.
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A picture is worth a thousand words. Here you are a slightly more complex example, with respect to the one at the top of [`Getting started`](@ref getting-started) section. We consider this monovariate time series:
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We want to encode a graph-like structure from the data above. We could think of various strategies, one of which is to consider every contiguous subsequence in the time series and model it as a set of intervals.
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# [Association rule mining with modal logic](@id man-modal-generalization)
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At this point, we can see every resulting blue signal as a propositional model, on which items may be evaluated as true or false. In the modal logic jargon, this is exactly a Kripke model.
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After fixing a set of suitable relations, we express them with arcs in the structure. Without defining them, we graphically present some possible relations between intervals. The one below is the *begins* relation.
Every relation $R$ can be declined in an *existential* or a *universal* way. In the former (latter) case, given an item $p$, we say that $<R>p$ is true on $w$ if at least one world (all worlds) $w'$ is such that $wRw'$ and $p$ is true on $w'$. Such relations can be encoded thanks to SoleLogics.jl; in particular, we use `diamond(relation_name)` to indicate an *existential modality* while `box(relation_name)` to indicate universal ones:
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