I am sorry but I have no idea about it.
On Sun, Nov 13, 2016 at 4:24 PM, Lorenz B. < [email protected]> wrote: > You don't know what exactly? > > > Hello Lorenz, kindly if you can suggest me how to avoid this situation. > > Recent data property value can be achieved using Jena but I dont know how > > to do it in this case because Student is a class here. > > > > On Sat, Nov 12, 2016 at 4:55 PM, Lorenz B. < > > [email protected]> wrote: > > > >> And what is the question now? > >> > >> By the way, those rules do not overwrite any value, the logic is > >> supposed to be monotonic, i.e. only additional triples are inferred. > >> Replacement has to be done in the application code. > >> > >>> The students have to appear multiple time in the exam. When student > >> appears > >>> first time, he scored 80% and got in the category of Excellent Students > >>> list. Second time he appears, he scored 60% and thus appeared in > Average > >>> Student. > >>> Now after two exams, the Student in the owl file should be in the > Average > >>> Student list but both Excellent and Average Student appears and thus > the > >>> first value of first exam also there. > >>> > >>> On Sun, Oct 16, 2016 at 9:16 PM, Dave Reynolds < > >> [email protected]> > >>> wrote: > >>> > >>>> On 14/10/16 14:53, javed khan wrote: > >>>> > >>>>> I have divided Students into ExcellentStudents and AverageStudents > >> based > >>>>> on > >>>>> some criteria via Jena rules: if student got 75% or more, he/she will > >> be > >>>>> in > >>>>> "ExcellentStudents" else "AverageStudents". > >>>>> In first exam, if some one takes 75% and put into ExcellentStudents > >> but > >>>>> next time if he scores less than 75%, he will be AverageStudents. > >>>>> > >>>>> The problem is that when I store it in the file, the previous value > >> does > >>>>> not overwrite the new one and I see both categories in the owl file > >> like: > >>>>> John > >>>>> AverageStudents > >>>>> ExcellentStudents > >>>>> > >>>>> How can we cope with this issue? > >>>>> > >>>> If in your data there is only ever one exam result for a given student > >>>> then you it might make sense to have AverageStudents/ExcellentStudent > >>>> classes. However, if you have multiple exam results in the same data > >> then > >>>> naturally some will be average on some and excellent on others. > >>>> > >>>> So you have to decide what your semantics are. Do you want > >>>> ExcellentStudent to mean that the student averages 75% or more across > >> all > >>>> exams? Or you you want an n-relationship between students, exams and > >>>> classifications? > >>>> > >>>> Once you've decided what you semantics are and how the answers should > >> look > >>>> then you can figure out an implementation. > >>>> > >>>> Dave > >>>> > >>>> > >>>> > >>>>> The rules are: > >>>>> > >>>>> String rule = "[rule1:(?x http://www.w3.org/1999/02/22- > >> rdf-syntax-ns#type > >>>>> http://www.semanticweb.org#Student) " > >>>>> + "( ?x http://www.semanticweb.org#score ?marks )" > >>>>> + "greaterThan(?marks, 70) " > >>>>> + " -> (?x http://www.w3.org/1999/02/22-r > >>>>> df-syntax-ns#type > >>>>> http://www.semanticweb.org#ExcellentStudents )]" > >>>>> > >>>>> + "[rule2:(?x http://www.w3.org/1999/02/22-rdf-syntax-ns#type > >>>>> http://www.semanticweb.org#Student) " > >>>>> + "( ?x http://www.semanticweb.org#score ?marks )" > >>>>> + "lessThan(?marks, 70) " > >>>>> + " -> (?x http://www.w3.org/1999/02/22-r > >>>>> df-syntax-ns#type > >>>>> http://www.semanticweb.org#AverageStudents )]"; > >>>>> > >>>>> > >>>>> for (Iterator i = inf.listResourcesWithProperty(RDF.type,stutype1 ); > >>>>> i.hasNext();) { > >>>>> inf.listStatements(null,RDF.type, "ExcellentStudents"); > >>>>> > >>>>> } > >>>>> for (Iterator i = inf.listResourcesWithProperty(RDF.type, > >> stutype2); > >>>>> i.hasNext();) { > >>>>> inf.listStatements(null,RDF.type, "AverageStudents"); > >>>>> > >>>>> } > >>>>> > >>>>> I also tried with SPARQL but same result. > >>>>> SELECT * " + > >>>>> " WHERE { ?x rdf:type std:ExcellentStudents . ?x > >>>>> rdf:type > >>>>> std:AverageStudents}"; > >>>>> > >>>>> > >> -- > >> Lorenz Bühmann > >> AKSW group, University of Leipzig > >> Group: http://aksw.org - semantic web research center > >> > >> > -- > Lorenz Bühmann > AKSW group, University of Leipzig > Group: http://aksw.org - semantic web research center > >
