Construction of a Dataset for Extracting the Relationship between Text and Tables for Securities Reports
Author:
Affiliation:
1. Fukuoka University
2. Otaru University of Commerce
3. RIKEN
4. The Japan Research Institute, Limited
Publisher
Japanese Society for Artificial Intelligence
Link
https://www.jstage.jst.go.jp/article/tjsai/39/4/39_39-4_FIN23-A/_pdf
Reference20 articles.
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2. [Bentabet 20] Bentabet, N.-I., Juge, R., El Maarouf, I., Mouilleron, V., Valsamou-Stanislawski, D., and El-Haj, M.: The Financial Document Structure Extraction Shared task (FinToc 2020), in Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation, pp. 13–22, Barcelona, Spain (Online) (2020)
3. [Campbell 14] Campbell, J., Chen, H., Dhaliwal, D., Lu, H., and Steele, L.: The Information Content of Mandatory Risk Factor Disclosures in Corporate Filings, Review of Accounting Studies, Vol. 19, No. 1, pp. 396–455 (2014)
4. [Chen 20] Chen, K., Xu, W., Cheng, X., Xiaochuan, Z., Zhang, Y., Song, L., Wang, T., Qi, Y., and Chu, W.: Question Directed Graph Attention Network for Numerical Reasoning over Text, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 6759–6768, Online (2020)
5. [Cohen 60] Cohen, J.: A Coefficient of Agreement for Nominal Scales, Educational and Psychological Measurement, Vol. 20, No. 1, p. 37 (1960)
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