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Bayesian query-focused summarization
Open accessAbstract
We present BAYESUM (for "Bayesian summarization"), a model for sentence extraction in query-focused summarization.BAYESUM leverages the common case in which multiple documents are relevant to a single query.Using these documents as reinforcement for query terms, BAYESUM is not afflicted by the paucity of information in short queries.We show that approximate inference in BAYESUM is possible on large data sets and results in a stateof-the-art summarization system.Furthermore, we show how BAYESUM can be understood as a justified query expansion technique in the language modeling for IR framework.
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Cited by
A Survey of Text Summarization Extractive Techniques
Gupta, V., & Lehal, G. S. (2010) · Journal of Emerging Technologies in Web Intelligence · doi:10.4304/jetwi.2.3.258-268 · Cited by 616
QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization
Zhong, M., Yin, D., Yu, T., Zaidi, A., Mutuma, M., Jha, R., Awadallah, A. H., Celikyilmaz, A., Liu, Y., Qiu, X., et al. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · doi:10.18653/v1/2021.naacl-main.472 · Cited by 178
ChestXRayBERT: A Pretrained Language Model for Chest Radiology Report Summarization
Cai, X., Liu, S., Han, J., Yang, L., Liu, Z., & Liu, T. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3132724 · Cited by 72
Surveyor: A System for Generating Coherent Survey Articles for Scientific Topics
Jha, R., Coke, R., & Radev, D. (2015) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v29i1.9495 · Cited by 19
QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization
Zhong, M., Yin, D., Yu, T., Zaidi, A., Mutuma, M., Jha, R., Awadallah, A. H., Celikyilmaz, A., Liu, Y., Qiu, X., et al. (2021) · arXiv · doi:10.48550/arxiv.2104.05938
Metadata
- Authors
- Daumé, H., & Marcu, D.
- Venue
- Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL - ACL '06
- Published
- 2006
- Pages
- 305-312
- OpenAlex
- W2103339462
- Cited by
- 255
- References
- 0
- FWCI
- 5.76
- Type
- conference paper
- Language
- en
- Open access
- gold
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- Daumé, H., & Marcu, D. (2006). Bayesian query-focused summarization. Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL - ACL '06. https://doi.org/10.3115/1220175.1220214
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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.
