OwlEd for MaMaS

An OWL Manager for the Match Maker Service

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Supported Inference Services
OwlEd supports standard inference services of DL reasoners, namely subsumption, satisfiability, equivalence and disjointness for concept expressions, instance checking, retrieval and realization. Furthermore, as its design has been specifically oriented towards semantic matchmaking services it also features non-standard services supported by MaMaS-tng. Such services are hereafter briefly described.
  • Match type detection. Given an ontology T, it allows to determine the match category between a request D and a resource S. In particular, matches are classified within the following categories, which have been defined -sometimes with different names- by various authors:
    • exact match
    • full match
    • plug-in match
    • potential match
    • partial match
  • Rank Potential. Given an ontology Tand two concept expressions representing a request D(for demand) and the resource S to be matched with D, both satisfiable with respect to T. If D is compatible with S - Potential Match, i.e., their conjunction is satisfiable with respect to T - then Rank Potential returns a score measuring the semantic distance of S from D (D is classified with respect to S) taking into account the information modeled in T.
  • Rank Partial. Given an ontology T and two concept expressions representing a request D (for Demand) and the resource S to be matched with D, both satisfiable with respect to T. If Dis NOT compatible with S - Partial Match, i.e., their conjunction is NOT satisfiable with respect to T - then Rank Partial returns a score measuring the semantic incompatibility of D and S.
  • Concept Abduction. Given an ontology Tand two concept expressions representing a request D (for Demand) and the resource S to be matched with D, both satisfiable with respect to T. If Dis compatible with S - Potential/Full/Exact Match - with Concept Abduction it is possible to compute a concept expression H representing what is underspecified in S in order to completely satisfy D - S is classified by D with respect to T - taking into account the information modeled in T. In other words, H represents an explanation on why S is not classified by D with respect to T. Notice that rank potential can be used as a numerical measure of H for the related Concept Abduction Problem.
    In Figure 3 results to requests of Concept Abduction are depicted, in case of Potential match (Request ID:10) and Full match (Request ID:11). In the former case, an explanation hypothesis of what is missed in S (Supply) in order to completely satisfy - be more specific than - D(Demand) is computed. In the latter case, no explanation is provided because a Full match occurs.
  • Concept Contraction. Given an ontology Tand two concept expressions representing a request D (for Demand) and the resource S to be matched with D, both satisfiable with respect to T. If Dis NOT compatible with S -Partial Match - then with Concept Contraction it is possible to compute a contraction K (for Keep) of D which is compatible with § taking into account the information modeled in T. The solution computed for the Concept Contraction problem is a pair of concept expressions G (for Give up) and K (for Keep) whose conjunction is equivalent to S with respect to T. In other words, G represents an explanation on what in Dis not compatible with S (causing a Partial Match). In Figure 4, an example of Concept Contraction is depicted.
  • Concept Covering. Given an ontology T, a concept expressions representing a request D(for Demand) and a set of resources R = {Ri} all satisifiable with respect to T. Find a subset of R such that the conjunction of all the elements in such subset is both satisfiable with respect to Tand is more specific than D. If the conjunction is not more specific than D - Potential Match - the remaining/uncovered part of D is also returned. A Concept Covering, can be performed either allowing to contract D - Extended Concept Covering - or not - Basic Concept Covering.
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