Applications for Future Internet. International Summit, AFI 2016, Puebla, Mexico, May 25-28, 2016, Revised Selected Papers

Research Article

Overview of a Framework for Ubiquitous User Models Interoperability

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  • @INPROCEEDINGS{10.1007/978-3-319-49622-1_20,
        author={Mar\^{\i}a Lourdes Mart\^{\i}nez-Villase\`{o}or and Miguel Gonz\^{a}lez-Mendoza},
        title={Overview of a Framework for Ubiquitous User Models Interoperability},
        proceedings={Applications for Future Internet. International Summit, AFI 2016, Puebla, Mexico, May 25-28, 2016, Revised Selected Papers},
        proceedings_a={AFI360},
        year={2017},
        month={1},
        keywords={User modeling interoperability User modeling Schema matching},
        doi={10.1007/978-3-319-49622-1_20}
    }
    
  • María Lourdes Martínez-Villaseñor
    Miguel González-Mendoza
    Year: 2017
    Overview of a Framework for Ubiquitous User Models Interoperability
    AFI360
    Springer
    DOI: 10.1007/978-3-319-49622-1_20
María Lourdes Martínez-Villaseñor1,*, Miguel González-Mendoza2,*
  • 1: Universidad Panamericana Campus México
  • 2: Tecnológico de Monterrey
*Contact email: lmartine@up.edu.mx, mgonza@itesm.mx

Abstract

Researchers in the user modeling community have been interested in sharing and reuse profile information from heterogeneous sources. Ubiquitous user model interoperability allows enrichment of adaptive systems obtaining a better understanding of the user, and decreases the effort associated with creating a user model. We present a framework that enables the interoperability between profile suppliers and consumers with a mixed approach that consist in central ubiquitous user model ontology and a process of concept alignment. The central ontology is a flexible representation of a ubiquitous user model to cope with the dynamicity of a distributed multi-application environment that provides mediation between profile suppliers and consumers. The process of concept alignment automatically discovers the semantic mappings in order to interpret the information from heterogeneous sources and integrate them into a ubiquitous user model.