The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Automatic Summarization
Abstract
It has now been 50 years since the publication of Luhn’s seminal paper on automatic summarization. During these years the practical need for automatic summarization has become increasingly urgent and numerous papers have been published on the topic. As a result, it has become harder to find a single reference that gives an overview of past efforts or a complete view of summarization tasks and necessary system components. This article attempts to fill this void by providing a comprehensive overview of research in summarization, including the more traditional efforts in sentence extraction as well as the most novel recent approaches for determining important content, for domain and genre specific summarization and for evaluation of summarization. We also discuss the challenges that remain open, in particular the need for language generation and deeper semantic understanding of language that would be necessary for future advances in the field.
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Citations
Cites
The Pyramid Method: Incorporating human content selection variation in summarization evaluation
Nenkova, A., Passonneau, R., & McKeown, K. (2007) · ACM Transactions on Speech and Language Processing · doi:10.1145/1233912.1233913 · Cited by 307
Self-citation
Cited by
Processing Social Media Messages in Mass Emergency: A Survey
Imran, M., Castillo, C., Diaz, F., & Vieweg, S. (2015) · ACM Computing Surveys · doi:10.1145/2771588 · Cited by 804
Benchmarking Large Language Models for News Summarization
Zhang, T., Ladhak, F., Durmus, E., Liang, P., McKeown, K., & Hashimoto, T. B. (2024) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00632 · Cited by 415
Self-citationBenchmarking Large Language Models for News Summarization
Zhang, T., Ladhak, F., Durmus, E., Liang, P., McKeown, K., & Hashimoto, T. B. (2023) · arXiv · doi:10.48550/arxiv.2301.13848 · Cited by 415
Self-citationAssessing sentence scoring techniques for extractive text summarization
Ferreira, R., de Souza Cabral, L., Lins, R. D., Pereira e Silva, G., Freitas, F., Cavalcanti, G. D. C., Lima, R., Simske, S. J., & Favaro, L. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.04.023 · Cited by 318
The linguistic patterns and rhetorical structure of citation context: An approach using n-grams
Bertin, M., Atanassova, I., Sugimoto, C. R., & Lariviere, V. (2016) · Scientometrics · doi:10.1007/s11192-016-2134-8 · Cited by 50
Metadata
- Authors
- Nenkova, A., & McKeown, K.
- Venue
- Foundations and Trends® in Information Retrieval
- Publisher
- Emerald
- Published
- 2011-06-30
- Volume
- 5
- Issue
- 2–3
- Pages
- 103-233
- ISSN
- 1554-0669 (ISSN-L)
- 1554-0677
- OpenAlex
- W4206584443
- Cited by
- 301
- References
- 1
- FWCI
- 8.87
- Type
- journal article
- Language
- en
- Open access
- closed
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