Cargando…
Automatic transparency evaluation for open knowledge extraction systems
BACKGROUND: This paper proposes Cyrus, a new transparency evaluation framework, for Open Knowledge Extraction (OKE) systems. Cyrus is based on the state-of-the-art transparency models and linked data quality assessment dimensions. It brings together a comprehensive view of transparency dimensions fo...
Autores principales: | Basereh, Maryam, Caputo, Annalina, Brennan, Rob |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10468861/ https://www.ncbi.nlm.nih.gov/pubmed/37653549 http://dx.doi.org/10.1186/s13326-023-00293-9 |
Ejemplares similares
-
Transparency and openness in science
por: Sanders, Jeremy, et al.
Publicado: (2017) -
Design of Automatic Extraction Algorithm of Knowledge Points for MOOCs
por: Chen, Haijian, et al.
Publicado: (2015) -
Refining Automatically Extracted Knowledge Bases Using Crowdsourcing
por: Li, Chunhua, et al.
Publicado: (2017) -
Unlocking digital archives: cross-disciplinary perspectives on AI and born-digital data
por: Jaillant, Lise, et al.
Publicado: (2022) -
Basic self-knowledge and transparency
por: Borgoni, Cristina
Publicado: (2016)