Ontology matching with CIDER: evaluation report for the OAEI 2008
Jorge Gracia, Eduardo Mena · 2008
Abstract. CIDER is a schema-based ontology alignment system. Its algorithm compares each pair of ontology terms by, firstly, extracting their ontological contexts up to a certain depth (enriched by using lightweight inference) and, secondly, combining different elementary ontology matching techniques. In its current version, CIDER uses artificial neural networks in order to combine such elementary matchers. In this paper we briefly describe CIDER and comment on its results at the Ontology Alignment Evaluation Initiative 2011 campaign (OAEI’11). In this new approach, the burden of manual selection of weights has been definitely eliminated, while preserving the performance with respect to CIDER’s previous participation in the benchmark track (at OAEI’08). 1 Presentation of the system CIDER (Context and Inference baseD alignER) is a system for ontology alignment that performs semantic similarity computations among terms of two given ontologies. It extracts the ontological context of the compared terms and enriches it by applying