Enhancing Table Retrieval with Dual Graph Representations

Author:

Liu Tianyun,Zhang Xinghua,Zhang Zhenyu,Wang Yubin,Li Quangang,Zhang Shuai,Liu Tingwen

Publisher

Springer Nature Switzerland

Reference26 articles.

1. Cafarella, M.J., Halevy, A., Khoussainova, N.: Data integration for the relational web. Proc. VLDB Endowment 2(1), 1090–1101 (2009)

2. Chen, W., et al.: TabFact: a large-scale dataset for table-based fact verification. In: 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, 26–30 April 2020. OpenReview.net (2020). https://openreview.net/forum?id=rkeJRhNYDH

3. Chen, W., Zha, H., Chen, Z., Xiong, W., Wang, H., Wang, W.Y.: HybridQA: a dataset of multi-hop question answering over tabular and textual data. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online (2020). https://doi.org/10.18653/v1/2020.findings-emnlp.91, https://aclanthology.org/2020.findings-emnlp.91

4. Chen, Z., Trabelsi, M., Heflin, J., Xu, Y., Davison, B.D.: Table search using a deep contextualized language model. In: Huang, J., et al. (eds.) Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, SIGIR 2020, Virtual Event, China, 25–30 July 2020. ACM (2020). https://doi.org/10.1145/3397271.3401044, https://doi.org/10.1145/3397271.3401044

5. Chen, Z., Trabelsi, M., Heflin, J., Yin, D., Davison, B.D.: MGNETS: multi-graph neural networks for table search. In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management, pp. 2945–2949. Association for Computing Machinery, New York, NY, USA (2021), https://doi.org/10.1145/3459637.3482140

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