Authors:
Lorena Otero-Cerdeira
;
Francisco J. Rodríguez Martínez
;
Tito Valencia-Requejo
and
Alma Gómez Rodríguez
Affiliation:
University of Vigo, Spain
Keyword(s):
Ontology Matching, Ontology Alignment, Similarity Measure, Lexical Measure.
Related
Ontology
Subjects/Areas/Topics:
Applications and Case-studies
;
Artificial Intelligence
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Ontology Matching and Alignment
;
Symbolic Systems
Abstract:
In this paper a new ontology matching algorithm, OntoPhil is presented. The algorithm relies on the exploitation of some initial correspondences or binding points that connect the two ontologies used as input. First, these binding points are computed using a new lexical similarity measure which combines the information from a terminological matcher and an external one. Next, by taking these binding points as basis and by exploiting the specific features of the external structure of the ontologies matched, new binding points are discovered. Finally, the binding points are automatically sifted out and the final alignment is provided. The proposed algorithm was tested on the benchmarks provided by the well known evaluation initiative OAEI, and also compared to other matching algorithms. Our experimental results show that OntoPhil is an effective approach and outperforms other algorithms that share the same principles.