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 |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
ICEIS_2019___Fuzzy_Approach_for_Data_Quality_Assessment.pdf | 262,26 kB | Adobe PDF | Ver/Abrir |
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