| Questions for Distributed Reasoning Ankesh |
- authors are working within the OWL Horst semantics and in section III-B they mention of Rule-base partitioning. I believe rules in OWL Horst are of the type {p a owl:TransitiveProperty, s1 p o1, o1 p o2 --> s1 p o2}. This rule can be re-written for each transitive property as {s1 tp o1, s2 tp o2 --> s1, tp, o2}, where tp is declared to be transitive in the KB. I couldn't clearly interpret the kind of rules the authors are referring. First of all does it matter? Although from the sole example they present it looks like they take the latter approach, and I believe rule base partitioning makes sense only in the latter approach. (Please correct me). Although latter approach means that rule base is comparatively huge because corresponding to each instance of the axiom they would have a rule.
- I am concerned of the choice of data sets. First of all authors do not mention anything about the OWL expressivity of LUBM, UOBM or MDC (UOBM uses a more expressive OWL). Secondly, LUBM (similarly UOBM) is a benchmark for traditional OWL reasoning. By nature the individual university data sets are totally unrelated, and therefore speed-up on data partitioning is not a surprise. I do not mean to say that real life data sets are any different. Do you think that it would have been helpful if authors could have referred to some study that discussed characteristics of real-life rdf graphs (owl data) in terms of connectedness/ partitions etc. or at least give some sense of real rdf graphs?
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Ankesh Khandelwal |
