WEATHERGOV+
Author:
Affiliation:
1. University of Victoria, Victoria, British Columbia, Canada
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3573128.3604901
Reference57 articles.
1. R. Barzilay and M. Lapata. 2005. Collective content selection for concept-to-text generation. In EMNLP. ACL 331--8. R. Barzilay and M. Lapata. 2005. Collective content selection for concept-to-text generation. In EMNLP. ACL 331--8.
2. Z. Chi H. Huang H.-D. Xu etal 2019. Complicated table structure recognition. arXiv preprint arXiv:1908.04729 (2019). Z. Chi H. Huang H.-D. Xu et al. 2019. Complicated table structure recognition. arXiv preprint arXiv:1908.04729 (2019).
3. B. Coüasnon and A. Lemaitre. 2014. Recognition of tables and forms. In Handb. Doc. Image Process. Recognit. D. Doermann and K. Tombre (Eds.). Springer 647--77. B. Coüasnon and A. Lemaitre. 2014. Recognition of tables and forms. In Handb. Doc. Image Process. Recognit. D. Doermann and K. Tombre (Eds.). Springer 647--77.
4. Y. Deng D. Rosenberg and G. Mann. 2019. Challenges in end-to-end neural scientific table recognition. In ICDAR. IEEE 894--901. Y. Deng D. Rosenberg and G. Mann. 2019. Challenges in end-to-end neural scientific table recognition. In ICDAR. IEEE 894--901.
5. P. A. Duboue and K. R. McKeown. 2003. Statistical acquisition of content selection rules for natural language generation. In EMNLP. 121--8. P. A. Duboue and K. R. McKeown. 2003. Statistical acquisition of content selection rules for natural language generation. In EMNLP. 121--8.
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