Utilize este identificador para referenciar este registo: http://hdl.handle.net/11144/4315
Título: A Fuzzy Approach for Data Quality Assessment of Linked Datasets
Autor: Arruda, Narciso
Alcântara, João
Vidal, Vânia
Brayner, Ângelo
Casanova, Marco
Pequeno, Valéria
Franco, Wellington
Palavras-chave: Quality Assessment
Linked Data Mashup
Fuzzy Inference System
Data Quality
Logic Fuzzy
Data: Mai-2019
Editora: SciTePress
Resumo: For several applications, an integrated view of linked data, denoted linked data mashup, is a critical requirement. Nonetheless, the quality of linked data mashups highly depends on the quality of the data sources. In this sense, it is essential to analyze data source quality and to make this information explicit to consumers of such data. This paper introduces a fuzzy ontology to represent the quality of linked data source. Furthermore, the paper shows the applicability of the fuzzy ontology in the process of evaluating data source quality used to build linked data mashups.
Revisão por Pares: yes
URI: http://hdl.handle.net/11144/4315
metadata.dc.identifier.doi: 10.5220/0007718803990406
ISBN: 978-989-758-372-8
Aparece nas colecções:AUTONOMA TECHLAB - Artigos/Papers

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