SRM-CSR: unsupervised aspect category detection based on semantic-aware relevance modeling and contextual sentence representation.

Xu Y, Mu X, Liu K, Li D

DOI: 10.1038/s41598-026-55299-x
Published: 2026 Jun 1
Container: Scientific reports
Publisher: Not recorded
Open access: yes

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BibTeX

@article{allodium:10.1038/s41598-026-55299-x,
  title = {SRM-CSR: unsupervised aspect category detection based on semantic-aware relevance modeling and contextual sentence representation.},
  author = {Xu Y and Mu X and Liu K and Li D},
  year = {2026},
  journal = {Scientific reports},
  doi = {10.1038/s41598-026-55299-x},
  url = {https://doi.org/10.1038/s41598-026-55299-x}
}

RIS

TY  - JOUR
TI  - SRM-CSR: unsupervised aspect category detection based on semantic-aware relevance modeling and contextual sentence representation.
AU  - Xu Y
AU  - Mu X
AU  - Liu K
AU  - Li D
PY  - 2026
JO  - Scientific reports
DO  - 10.1038/s41598-026-55299-x
UR  - https://doi.org/10.1038/s41598-026-55299-x
ER  -

APA

Y, X., X, M., K, L., & D, L. (2026). SRM-CSR: unsupervised aspect category detection based on semantic-aware relevance modeling and contextual sentence representation.. Scientific reports. https://doi.org/10.1038/s41598-026-55299-x

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pubmed · retrieved 2026-09-27T00:22:19.659Z