Joshua Shinavier Networked Graphs Joshua Taylor 1
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- Question is for the Presentation: Joshua Shinavier Networked Graphs
- Question is asked by: Joshua Taylor
- The Question is: In 6. IMPLEMENTATION, the authors describe their algorithm for determining the fixedpoint of a graph/view. They write, "In some more details, the procedure starts with the true statements, which are extensionally lister, or which can be derived from views, which do not use negation. //Though, I thought that views could use negation…// We call this underestimate U1. Statements in U1 are known to be true. U1 is used to compute an overestimate O1 by evaluating all views against this set of true statements. The result will be an overestimate, because U1 was still incomplete and therefore bound negation will succeed in too many cases. //So views can contain negation…//" (emphasis added) I do not see how they can guarantee that O1 will be an overestimate. It is generated based on U1 whose elements are known to be true, but which is not yet the set of all true statements. Then if O1 does not depend on views using negation, it would seem that O1 could be another underestimate. In 5.1 Requirements …, RDF Schema the authors state "that NGs are expressive enough to alternatively model the RDFS inference rules as view definitions." I imagine a a U1 containing "X rdf:type A", "A rdf:subClassOf B", and "B rdf:subClassOf C", which would lead to an O1 containing U1 as a subset, and also "X rdf:type B", and perhaps "X rdf:type C". Yet O1 is clearly not an overestimate. What am I missing here?
Answer
1. Statements in ''U''1 are known to be true. ''U''1 is used to compute an overestimate ''O''1 by evaluating all views against this set of true statements. '''The result will be an overestimate, because ''U''1 was still incomplete and therefore bound negation will succeed in too many cases.''' //So views ''can'' contain negation…//" (emphasis added) I do not see how they can guarantee that ''O''1 will be an overestimate. It is generated based on ''U''1 whose elements are known to be true, but which is not yet the set of all true statements. Then if ''O''1 does not depend on views using negation, it would seem that ''O''1 could be another underestimate. In '''5.1 Requirements …, RDF Schema''' the authors state "that NGs are expressive enough to alternatively model the RDFS inference rules as view definitions." I imagine a a ''U''1 containing "X rdf:type A", "A rdf:subClassOf B", and "B rdf:subClassOf C", which would lead to an ''O''1 containing ''U''1 as a subset, and also "X rdf:type B", and perhaps "X rdf:type C". Yet ''O''1 is clearly not an overestimate. What am I missing here?'>
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| Question asked | In 6. IMPLEMENTATION, the authors de … In 6. IMPLEMENTATION, the authors describe their algorithm for determining the fixedpoint of a graph/view. They write, "In some more details, the procedure starts with the true statements, which are extensionally lister, or which can be derived from views, which do not use negation. //Though, I thought that views could use negation…// We call this underestimate U1. Statements in U1 are known to be true. U1 is used to compute an overestimate O1 by evaluating all views against this set of true statements. The result will be an overestimate, because U1 was still incomplete and therefore bound negation will succeed in too many cases. //So views can contain negation…//" (emphasis added) I do not see how they can guarantee that O1 will be an overestimate. It is generated based on U1 whose elements are known to be true, but which is not yet the set of all true statements. Then if O1 does not depend on views using negation, it would seem that O1 could be another underestimate. In 5.1 Requirements …, RDF Schema the authors state "that NGs are expressive enough to alternatively model the RDFS inference rules as view definitions." I imagine a a U1 containing "X rdf:type A", "A rdf:subClassOf B", and "B rdf:subClassOf C", which would lead to an O1 containing U1 as a subset, and also "X rdf:type B", and perhaps "X rdf:type C". Yet O1 is clearly not an overestimate. What am I missing here? t an overestimate. What am I missing here? |
| Question asked by | Joshua Taylor + |
| Question for the Presentation | Joshua Shinavier Networked Graphs + |
