The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Automatic Keyphrase Extraction: A Survey of the State of the Art
Abstract
While automatic keyphrase extraction has been examined extensively, state-of-the-art performance on this task is still much lower than that on many core natural lan-guage processing tasks. We present a sur-vey of the state of the art in automatic keyphrase extraction, examining the major sources of errors made by existing systems and discussing the challenges ahead. 1
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The anatomy of a large-scale hypertextual Web search engine
Brin, S., & Page, L. (1998) · Computer Networks and ISDN Systems · doi:10.1016/s0169-7552(98)00110-x · Cited by 16,004
Cited by
YAKE! Keyword extraction from single documents using multiple local features
Campos, R., Mangaravite, V., Pasquali, A., Jorge, A., Nunes, C., & Jatowt, A. (2020) · Information Sciences · doi:10.1016/j.ins.2019.09.013 · Cited by 668
PositionRank: An Unsupervised Approach to Keyphrase Extraction from Scholarly Documents
Florescu, C., & Caragea, C. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/p17-1102 · Cited by 331
Citation-Enhanced Keyphrase Extraction from Research Papers: A Supervised Approach
Caragea, C., Bulgarov, F. A., Godea, A., & Das Gollapalli, S. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1150 · Cited by 134
Seeing Things from a Different Angle:Discovering Diverse Perspectives about Claims
Chen, S., Khashabi, D., Yin, W., Callison-Burch, C., & Roth, D. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · doi:10.18653/v1/n19-1053 · Cited by 104
Metadata
- Authors
- Hasan, K. S., & Ng, V.
- Venue
- Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Published
- 2014
- Pages
- 1262-1273
- OpenAlex
- W2167329753
- Cited by
- 518
- References
- 1
- FWCI
- 22.73
- Type
- conference paper
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
