Dave,
"Alternatively, Jena rules has the notion of a "functor" (bad name) which
is essentially a structured literal. So you can represent your Y/C pairs
as certainty(Y,C) and write rules which generate and match triples whose
object is a certainty(?x,?y) pair"
You are saying something like:
(?x exa:p1 certainty(?y, ?c)) <- (?x exa:p11 certainty(?y, ?c)).
(?x exa:p1 certainty(?y, ?c)) <- (?x exa:p12 certainty(?y, ?c)).
(?x exa:p11 certainty(exa:o1, 0.8)) <- (?x exa:qvalue ?v), lessThan(?v,
10).
(?x exa:p12 certainty(exa:o2, 0.7)) <- (?x exa:qvalue ?v), ge(?v, 100).
?
Is this possible? How can I invoke a "structured literal” in a Sparql
command?
MBA
On 12/11/13 14:31, "Dave Reynolds" <[email protected]> wrote:
>On 12/11/13 11:54, Miguel Bento Alves wrote:
>> Dear Dave,
>>
>> Can I express myself in Prolog?
>>
>> I want something like:
>>
>> v(s1, 8).
>> v(s2, 120).
>>
>> p1(X, Y, C):-
>> p11(X, Y, C).
>>
>>
>> p1(X, Y, C):-
>> p12(X, Y, C).
>>
>>
>> p11(X, o1, 0.8):-
>> v(X, V),
>> V < 10.
>>
>>
>> p12(X, o1, 0.7):-
>> v(X, V),
>> V >= 100.
>>
>>
>> p1(s1, Y, C)?
>> Y = o1, C = 0.8
>>
>> p1(s2, Y, C)?
>> Y = o1, C = 0.7
>>
>>
>>
>> In best of my knowledge, is not possible what I want. But I¹m new in
>>Jena
>> and perhaps there are a solution that I can¹t figure out. I think that
>>is
>> not possible because I need a quad: Subject, Property, Object,
>>Confidence.
>> I tried with blank nodes but I didn¹t had success.
>
>If that's really what you want then that is more or less possible,
>however I think you'll find you need more.
>
>The issue is that in your example there is no overlap of rules. So p11
>and p12 never occur together, indeed for values of V between 10 and 99
>there's no value for p1. Normally once you have uncertainty measures you
>find cases where there are multiple routes to a conclusion, each of
>which contributes some confidence/certainty/belief/whatever. In which
>case you need to trace out all the possible routes and combine the
>confidence measures from each route, which in turn requires dependency
>assumptions. If that's where you are headed them I would start with a
>tool designed for that job, not start with a rule based system and hope
>to extend it.
>
>However, if there are *really* no overlaps, and only ever a single
>deduction path for a single conclusion, and that won't change, then you
>could do something in Jena.
>
>There are two options for handling n-ary relations in Jena rules.
>
>First you can represent them as groups of triples. To deduce an instance
>of an n-ary relationship from a rule then you need to create a bNode to
>represent the instance. For this you can use makeTemp (which a guard to
>prevent multiple instantiation) or makeSkolem. The latter is probably
>the better choice.
>
>Alternatively, Jena rules has the notion of a "functor" (bad name) which
>is essentially a structured literal. So you can represent your Y/C pairs
>as certainty(Y,C) and write rules which generate and match triples whose
>object is a certainty(?x,?y) pair. By default these literals are kept
>internal to the inference engine but there is an option to make them
>visible to external queries (PROPenableFunctorFiltering).
>
>Dave
>
>
>>
>> MBA
>>
>>
>> On 12/11/13 11:19, "Dave Reynolds" <[email protected]> wrote:
>>
>>> Depending on exactly what semantics you want for confidence
>>>coefficients
>>> then you probably want to look at a Bayesian network software.
>>>
>>> Dave
>>>
>>> On 12/11/13 09:04, Miguel Bento Alves wrote:
>>>>
>>>>
>>>> I want to introduce a confidence coefficient in my rules. For
>>>>instance,
>>>> in
>>>> the example below, let's consider that p11 has a confidence
>>>>coefficient
>>>> of
>>>> 0.8 while p12 has a confidence coefficient of 0.7. When ?x exa:p1 ?y
>>>> happens
>>>> I want to know the confidence of this conclusion. Any ideas? I have
>>>>been
>>>> study but I couldn't figure out a good solution.
>>>>
>>>> (?x exa:p1 ?y) <- (?x exa:p11 ?y).
>>>>
>>>> (?x exa:p1 ?y) <- (?x exa:p12 ?y).
>>>>
>>>> (?x exa:p11 exa:o1) <- (?x exa:qvalue ?v), lessThan(?v, 10).
>>>>
>>>> (?x exa:p12 exa:o2) <- (?x exa:qvalue ?v), ge(?v, 100).
>>>>
>>>> MBA
>>>>
>>>>
>>>>
>>>
>>
>>
>
