abstract
- © 2017, Springer International Publishing AG. The need to share and reuse information has grown in the new era of Internet of things and ubiquitous computing. Researchers in ontology and schema matching use mapping approaches in order to achieve interoperability between heterogeneous sources. The use of multiple similarity measures that take into account lexical, structural and semantic properties of the concepts is often found in schema matching for the purpose of data integration, sharing and reusing. Mappings identified by automatic or semi-automatic tools can never be certain. In this paper, we present a fuzzy-based approach to combine different similarity measures to deal with scenarios where ambiguity of terms hinder the process of alignment and add uncertainty to the match.