Fuzzy aggregation of similarity values for electronic health record interoperability
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Schema matching is used for data integration, mediation, and conversion between heterogeneous sources. Nevertheless, mappings identified with an automatic or semi-automatic process can never be completely certain. In a process of concept alignment, it is necessary to manage uncertainty. In this paper, we present a fuzzy-based process of concept alignment for uncertainty management in schema matching problem. The ultimate goal is to enable interoperability between different electronic health records. Data integration of health information is done through the mediation of our ubiquitous user model framework. Results look promising and fuzzy theory proved to be a good fit for modeling uncertain schema matching. Fuzzy combined similarities can handle uncertainty in the schema matching process to enable interoperability between electronic health records improving the quality of mappings and diminishing the human error to verify the mappings. © 2019 - IOS Press and the authors. All rights reserved
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