The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
PositionRank: An Unsupervised Approach to Keyphrase Extraction from Scholarly Documents
Open accessAbstract
The large and growing amounts of online scholarly data present both challenges and opportunities to enhance knowledge discovery.One such challenge is to automatically extract a small set of keyphrases from a document that can accurately describe the document's content and can facilitate fast information processing.In this paper, we propose PositionRank, an unsupervised model for keyphrase extraction from scholarly documents that incorporates information from all positions of a word's occurrences into a biased PageRank.Our model obtains remarkable improvements in performance over PageRank models that do not take into account word positions as well as over strong baselines for this task.Specifically, on several datasets of research papers, PositionRank achieves improvements as high as 29.09%.
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Introduction to information retrieval
(2009) · Choice Reviews Online · doi:10.5860/choice.46-2715 · Cited by 12,278
TextRank: Bringing Order into Text
Mihalcea, R. F., & Tarau, P. (2004) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · Cited by 3,631
Topic-sensitive pagerank: A context-sensitive ranking algorithm for web search
Haveliwala, T. H. (2003) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2003.1208999 · Cited by 1,052
CiteSeer: an automatic citation indexing system
Giles, C. L., Bollacker, K. D., & Lawrence, S. (1998) · Proceedings of the third ACM conference on Digital libraries - DL '98 · doi:10.1145/276675.276685 · Cited by 1,040
Improved automatic keyword extraction given more linguistic knowledge
Hulth, A. (2003) · Proceedings of the 2003 conference on Empirical methods in natural language processing - · doi:10.3115/1119355.1119383 · Cited by 951
Learning Algorithms for Keyphrase Extraction
Turney, P. D. (2000) · Information Retrieval · doi:10.1023/a:1009976227802 · Cited by 889
Domain-specific keyphrase extraction
Frank, E., Paynter, G. W., Witten, I. H., Gutwin, C. A., & Nevill-Manning, C. G. (1999) · Research Commons (University of Waikato) · Cited by 647
Automatic Keyphrase Extraction: A Survey of the State of the Art
Hasan, K. S., & Ng, V. (2014) · Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.3115/v1/p14-1119 · Cited by 518
Single document keyphrase extraction using neighborhood knowledge
Wan, X., & Xiao, J. (2008) · Cited by 393
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
Metadata
- Authors
- Florescu, C., & Caragea, C.
- Venue
- Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Published
- 2017
- Pages
- 1105-1115
- OpenAlex
- W2740811004
- Cited by
- 331
- References
- 31
- FWCI
- 12.45
- Type
- conference paper
- Language
- en
- Open access
- hybrid
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- Florescu, C., & Caragea, C. (2017). PositionRank: An Unsupervised Approach to Keyphrase Extraction from Scholarly Documents. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). https://doi.org/10.18653/v1/p17-1102
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
