The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Applying deep learning to answer selection: A study and an open task
Open accessAbstract
We apply a general deep learning framework to address the non-factoid question answering task. Our approach does not rely on any linguistic tools and can be applied to different languages or domains. Various architectures are presented and compared. We create and release a QA corpus and setup a new QA task in the insurance domain. Experimental results demonstrate superior performance compared to the baseline methods and various technologies give further improvements. For this highly challenging task, the top-1 accuracy can reach up to 65.3% on a test set, which indicates a great potential for practical use.
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LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
Gradient-based learning applied to document recognition
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Distributed Representations of Words and Phrases and their Compositionality
Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1310.4546 · Cited by 24,533
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Cited by
A Structured Self-attentive Sentence Embedding
Lin, Z., Feng, M., Santos, C. N. D., Yu, M., Xiang, B., Zhou, B., & Bengio, Y. (2017) · arXiv · doi:10.48550/arxiv.1703.03130 · Cited by 1,743
“…networks (Kalchbren-ner et al., 2014; dos Santos & Gatti, 2014; Kim, 2014) as an intermediate step in creating sentence representations to solve a wide variety of tasks including classification and ranking (Yin & Sch¨utze, 2015; Palangi et al., 2016; Tan et al., 2016; Feng et al., 2015).”
BackgroundSelf-citationemrQA: A Large Corpus for Question Answering on Electronic Medical Records
Pampari, A., Raghavan, P., Liang, J., & Peng, J. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d18-1258 · Cited by 191
Jiang, J., Lu, W., Chen, J., Lin, Q., Zhao, P., Kang, Y., Zhang, H., Xiong, Y., Gao, F., Xu, Z., et al. (2020) · Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering · doi:10.1145/3368089.3417054 · Cited by 56
Personalized chatbot trustworthiness ratings
Srivastava, B., Rossi, F., Usmani, S., & Bernagozzi, M. (2020) · IEEE Transactions on Technology and Society · doi:10.1109/tts.2020.3023919 · Cited by 40
Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System
Liu, Y., Zhang, C., Yan, X., Chang, Y., & Yu, P. S. (2019) · Proceedings of the 28th ACM International Conference on Information and Knowledge Management · doi:10.1145/3357384.3358046 · Cited by 15
Metadata
- Authors
- Feng, M., Xiang, B., Glass, M. R., Wang, L., & Zhou, B.
- Venue
- 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)
- Publisher
- IEEE
- Published
- 2015-12
- Pages
- 813-820
- OpenAlex
- W2964154091
- Cited by
- 357
- References
- 4
- FWCI
- 26.14
- Type
- conference paper
- Language
- en
- Open access
- green
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