SEMA: results for the ontology alignment contest OAEI 2007

To asses the viability of integrating alignment reuse as part of the ontology matching proposal for smart cities, we have used the ontologies of the conference

Most of the tasks in natural language processing and information retrieval, in- cluding search, question answering, and machine transla- tion, are based on matching between

The OMReasoner is unique in that it creates an extensible framework for combination of multiple individual matchers, and reasons about ontology matching by using

The OMReasoner is unique in that it creates an extensible framework for combination of multiple individual matchers, and reasons about ontology matching by using

Existing methods use logical reasoning over computed equivalence relationships or machine learning based on lex- ical and structural features of ontology elements [7, 3].. While

In the current paper, we proposed an evaluation of a novel approach for entity matching that is called Feature Based Entity Matching (FBEM) over datasets provided by the OAEI

In this paper, we have presented different strategies to improve the precision of background knowledge based Ontology Matching systems, by considering the semantics of the terms to

For example, swapping the nodes Cost and Colour in the right tree depicted on Figure 2 does not change the meaning of the corresponding term but allows the correspondence