The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Automatic Keyword Extraction from Individual Documents
Abstract
Keywords are widely used to define queries within information retrieval (IR) systems as they are easy to define, revise, remember, and share. This chapter describes the rapid automatic keyword extraction (RAKE), an unsupervised, domain-independent, and language-independent method for extracting keywords from individual documents. It provides details of the algorithm and its configuration parameters, and present results on a benchmark dataset of technical abstracts, showing that RAKE is more computationally efficient than TextRank while achieving higher precision and comparable recall scores. The chapter then describes a novel method for generating stoplists, which is used to configure RAKE for specific domains and corpora. Finally, it applies RAKE to a corpus of news articles and defines metrics for evaluating the exclusivity, essentiality, and generality of extracted keywords, enabling a system to identify keywords that are essential or general to documents in the absence of manual annotations. Controlled Vocabulary Terms benchmark polls
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A vector space model for automatic indexing
Salton, G., Wong, A., & Yang, C. S. (1975) · Communications of the ACM · doi:10.1145/361219.361220 · Cited by 7,521
Cited by
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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
Hutchins, B. I., Yuan, X., Anderson, J. M., & Santangelo, G. M. (2016) · PLoS Biology · doi:10.1371/journal.pbio.1002541 · Cited by 500
Where to Hide a Stolen Elephant: Leaps in Creative Writing with Multimodal Machine Intelligence
Singh, N., Bernal, G., Savchenko, D., & Glassman, E. L. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3511599 · Cited by 119
Can Children Learn Creativity from a Social Robot?
Ali, S., Moroso, T., & Breazeal, C. (2019) · Proceedings of the 2019 on Creativity and Cognition · doi:10.1145/3325480.3325499 · Cited by 93
Unsupervised Paraphrasing by Simulated Annealing
Liu, X., Mou, L., Meng, F., Zhou, H., Zhou, J., & Song, S. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2020.acl-main.28 · Cited by 75
Metadata
- Authors
- Rose, S., Engel, D., Cramer, N., & Cowley, W.
- Venue
- Text Mining
- Publisher
- Wiley
- Published
- 2010-03-04
- Pages
- 1-20
- OpenAlex
- W2133286915
- Cited by
- 1,095
- References
- 1
- Type
- other
- Language
- en
- Open access
- closed
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
