Quick mining in dense data: applying probabilistic support prediction in depth-first order.

Sadeequllah M, Rauf A, Rehman SU, Alnazzawi N

DOI: 10.7717/peerj-cs.2334
Published: 2024
Container: PeerJ. Computer science
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.7717/peerj-cs.2334,
  title = {Quick mining in dense data: applying probabilistic support prediction in depth-first order.},
  author = {Sadeequllah M and Rauf A and Rehman SU and Alnazzawi N},
  year = {2024},
  journal = {PeerJ. Computer science},
  doi = {10.7717/peerj-cs.2334},
  url = {https://doi.org/10.7717/peerj-cs.2334}
}

RIS

TY  - JOUR
TI  - Quick mining in dense data: applying probabilistic support prediction in depth-first order.
AU  - Sadeequllah M
AU  - Rauf A
AU  - Rehman SU
AU  - Alnazzawi N
PY  - 2024
JO  - PeerJ. Computer science
DO  - 10.7717/peerj-cs.2334
UR  - https://doi.org/10.7717/peerj-cs.2334
ER  -

APA

M, S., A, R., SU, R., & N, A. (2024). Quick mining in dense data: applying probabilistic support prediction in depth-first order.. PeerJ. Computer science. https://doi.org/10.7717/peerj-cs.2334

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pubmed · retrieved 2026-09-25T02:33:13.438Z