Provenance-and machine learning-based recommendation of parameter values in scientific workflows.

Silva Junior D, Pacitti E, Paes A, de Oliveira D

DOI: 10.7717/peerj-cs.606
Published: 2021
Container: PeerJ. Computer science
Publisher: Not recorded
Open access: yes

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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

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Cite this work

BibTeX

@article{allodium:10.7717/peerj-cs.606,
  title = {Provenance-and machine learning-based recommendation of parameter values in scientific workflows.},
  author = {Silva Junior D and Pacitti E and Paes A and de Oliveira D},
  year = {2021},
  journal = {PeerJ. Computer science},
  doi = {10.7717/peerj-cs.606},
  url = {https://doi.org/10.7717/peerj-cs.606}
}

RIS

TY  - JOUR
TI  - Provenance-and machine learning-based recommendation of parameter values in scientific workflows.
AU  - Silva Junior D
AU  - Pacitti E
AU  - Paes A
AU  - de Oliveira D
PY  - 2021
JO  - PeerJ. Computer science
DO  - 10.7717/peerj-cs.606
UR  - https://doi.org/10.7717/peerj-cs.606
ER  -

APA

D, S. J., E, P., A, P., & D, D. O. (2021). Provenance-and machine learning-based recommendation of parameter values in scientific workflows.. PeerJ. Computer science. https://doi.org/10.7717/peerj-cs.606

Source records

pubmed · retrieved 2026-09-25T02:31:52.801Z