Monolingual and Cross-lingual Ontology Matching with CIDER-CL: evaluation report for OAEI 2013
Jorge Gracia, Kartik Asooja · 2014
Abstract. CIDER-CL is the evolution of CIDER, a schema-based ontology alignment system. Its algorithm compares each pair of ontology entities by analysing their similarity at different levels of their ontological context (linguistic description, superterms, subterms, related terms, etc.). Then, such elementary similarities are combined by means of artificial neural networks. In its current version, CIDER-CL uses SoftTFIDF for monolingual comparisons and Cross-Lingual Explicit Semantic Analysis for comparisons between entities documented in different natural languages. In this paper we briefly describe CIDER-CL and comment its results at the Ontology Alignment Evaluation Initiative 2013 campaign (OAEI’13). 1 Presentation of the system CIDER-CL is the evolution of CIDER (Context and Inference baseD alignER) [7], now incorporating cross-lingual capabilities. In order to match ontology entities, CIDER-CL extracts their ontological context and enriches it by applying lightweight inference rules. Then, elementary similarity comparisons are performed to compare different features