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Martinez-Villaseñor, Lourdes
Enrichment of Learner Profile with Ubiquitous User Model Interoperability
Fuzzy aggregation of similarity values for electronic health record interoperability
2014
,
Martinez-Villaseñor, Lourdes
,
González-Mendoza, Miguel
,
Danvila Del Valle, Ignacio
Nowadays, there is a constant need of acquiring new knowledge and skills to keep up with the demands of changing environment. The design and development of training and educational systems that enable effective personalized learning help obtaining changing skills and fill competence gaps. The computational effort to create a user model that represents user’s knowledge, characteristics, interests, goals, background and preferences is repeatedly done by many systems and applications in several domains. Each system ends up with a partial view of the user. Researchers in user modeling foresee the need of sharing and reusing user model information in order to obtain a better understanding of the user and be able to provide personalized and proactive services. In this paper we present an application scenario of sharing and reusing information scattered in most commonly used applications to enhance learner profiles. ©Instituto Politécnico Nacional
2019
,
Martinez-Villaseñor, Lourdes
,
Ponce, Hiram
,
González-Mendoza, Miguel
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