OMReasoner: combination of multi-matchers for ontology matching: results for OAEI 2014

Ontology matching produces correspondences between entities of two ontologies. The OMReasoner is unique in that it creates an extensible framework for combination of multiple individual matchers, and reasons about ontology matching by using external dictionary WordNet and description logic reasoner. It handles ontology matching in both literal and semantic level, and it makes use of the semantic part of OWL-DL as well as structure. This paper describes the result of OMReasoner in the OAEI 2014 competition in three tracks: benchmark, conference, and MultiFarm. 1 Presentation of the system Ontology matching finds correspondences between semantically related entities of the ontologies. It plays a significant role in many application domains. Many approaches to ontology matching have been proposed: the implementation of match may use multiple match algorithms or matchers, and the following largelyorthogonal classification criteria are considered [1-3]: schema-level and instance-level, element-level and structure-level, syntactic and semantic, language-based and constraint-based. Many approaches focus on syntactic aspects instead of semantic ones. OMReasoner achieves the matching by means of some external dictionary and reasoning techniques. Still, this approach includes strategy of combination of (mainly syntactical) multi-matchers (e.g., EditDistance matcher) before match reasoning. 1.1 State, purpose, general statement The matching process can be defined as a function f. A’=f(O1, O2, A, p, r) Where O1 and O2 are a pair of ontologies as input to match, A is the input alignment between these ontologies and A’ is new alignment returned, p is a set of parameters (e.g., weight w and threshold τ) and r is a set of oracles and resources. Alignments express correspondences between two entities. A correspondence must express two corresponding entities and the relation that is supposed to hold between them. Given two ontologies, a correspondence is a 5-tuple:, where . id is a unique identifier of the given correspondence; . e1 and e2 are the entities of the first and the second ontology respectively; . R is a relation (e.g., equivalence(=), more general(>), less general(<), disjointness  )) holding between e1 and e2. In OAEI campaign, equivalence is mainly considered; . n is a confidence measure (typically in the [0 1] range) for the correspondence between e1 and e2. C1’,C2’, R1’,R2’ p ( w,τ) r dictionary