no no no ... SPARQL is a query language and not a machine learning algorithm.
RDF dataset D -> SPARQL query Q -> Q(D) = part of the data by means of graph pattern matching. there is no induction, confidence values, etc. define "most appropriate", then write the query to select those "features" - to repeate myself, your query just returns facts from the RDF dataset. nothing more, nothing less. which facts has to be defined by yourself. On 09.08.2018 09:08, javed khan wrote: > Hello Lorenz sorry for inconvenience. > > Suppose we have a dataset about software effort estimation which have about > 100 attributes (line of code, complexity etc). To extract the subset of > features (as all 100 attributes are not important), we usually used some > data mining algorithms (Genetic algorithm etc). Now I want to make these > attributes as Ontology and get the attributes via SPARQL but not sure how > can I select the most appropriate features using SPARQL (because the > Genetic algorithm and other select the most appropriate features > automatically). > > Best regards > > On Thu, Aug 9, 2018 at 7:53 AM, Lorenz Buehmann < > [email protected]> wrote: > >> Javed...I don't know how many mails you wrote to this list (and the >> Protege Users list), but shouldn't you already have learned that you >> have to provide more information, data, code, queries, use case, etc. in >> order to get help?! >> >> What do you expect as an answer on a question "can we ..." - my answer >> is, "yes, you can". And now? >> >> Just to clarify, SPARQL is a query language for RDF data, thus, you can >> query any explicit information that is contained in an RDF dataset. >> >> >> On 08.08.2018 21:56, javed khan wrote: >>> Hello >>> >>> For instance, we have to select some features ( for data mining) , can we >>> do it using Semantic Web technologies like Ontology and SPARQL. ? >>> >>> Thanks >>> >>
