Hierarchical Multilabel Classification for Fine-Level Event Extraction from Aviation Accident Reports

References

• Abedin M, Ng V, Khan L (2010) Cause identification from aviation safety incident reports via weakly supervised semantic lexicon construction. J. Artificial Intelligence Res. 38:569–631.Google Scholar
• Agarwal A, Gite R, Laddha S, Bhattacharyya P, Kar S, Ekbal A, Thind P, Zele R, Shankar R (2022) Knowledge graph–deep learning: A case study in question answering in aviation safety domain. Preprint, submitted June 9, https://arxiv.org/pdf/2205.15952.Google Scholar
• Cai L, Hofmann T (2004) Hierarchical document categorization with support vector machines. Proc. Thirteenth ACM Internat. Conf. Inform. Knowledge Management (Association for Computing Machinery, New York), 78–87.Google Scholar
• Cerri R, Barros RC, de Carvalho AC (2012) A genetic algorithm for hierarchical multi-label classification. Proc. 27th Annual ACM Sympos. Applied Comput. (Association for Computing Machinery, New York), 250–255.Google Scholar
• Costa EP, Lorena AC, Carvalho AC, Freitas AA, Holden N (2007) Comparing several approaches for hierarchical classification of proteins with decision trees. Brazilian Sympos. Bioinformatics (Springer, Berlin, Heidelberg), 126–137.Google Scholar
• Devlin J, Chang MW, Lee K, Toutanova K (2019a) BERT: Pre-training of deep bidirectional transformers for language understanding. Preprint, submitted May 24, https://arxiv.org/pdf/1810.04805.Google Scholar
• Devlin J, Chang MW, Lee K, Toutanova K (2019b) BERT: Pre-training of deep bidirectional transformers for language understanding. Burstein J, Doran C, Solorio T, eds. Proc. 2019 Conf. North Amer. Chapter Assoc. Comput. Linguistics Human Language Tech. NAACL-HLT 2019, vol. 1 (long and short papers) (Association for Computational Linguistics, Kerrville, TX), 4171–4186.Google Scholar
• Dong T, Yang Q, Ebadi N, Luo XR, Rad P (2021) Identifying incident causal factors to improve aviation transportation safety: Proposing a deep learning approach. J. Adv. Transportation 2021:5540046.Google Scholar
• Ferryman TA, Posse C, Rosenthal LJ, Srivastava AN, Statler IC (2006) What happened, and why: Toward an understanding of human error based on automated analyses of incident reports—vol. II. Technical Report No. NASA/TP–2006-213490, National Aeronautics and Space Administration, Washington, DC.Google Scholar
• Fuller JG, Hook LR (2020) Understanding general aviation accidents in terms of safety systems. 2020 AIAA/IEEE 39th Digital Avionics Systems Conf. (DASC) (IEEE, Piscataway, NJ), 1–9.Google Scholar
• Gan L, Ye B, Huang Z, Xu Y, Chen Q, Shu Y (2023) Knowledge graph construction based on ship collision accident reports to improve maritime traffic safety. Ocean Coastal Management 240:106660.Google Scholar
• Geng X (2016) Label distribution learning. IEEE Trans. Knowledge Data Engrg. 28(7):1734–1748.Google Scholar
• Gopal S, Yang Y (2013) Recursive regularization for large-scale classification with hierarchical and graphical dependencies. Proc. 19th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (Association for Computing Machinery, New York), 257–265.Google Scholar
• Huang W, Chen E, Liu Q, Chen Y, Huang Z, Liu Y, Zhao Z, Zhang D, Wang S (2019) Hierarchical multi-label text classification: An attention-based recurrent network approach. Proc. 28th ACM Internat. Conf. Inform. Knowledge Management (Association for Computing Machinery, New York), 1051–1060.Google Scholar
• Karamanolakis G, Ma J, Dong XL (2020) Txtract: Taxonomy-aware knowledge extraction for thousands of product categories. Preprint, submitted May 1, https://arxiv.org/pdf/2004.13852.Google Scholar
• Kierszbaum S, Lapasset L (2020) Applying distilled BERT for question answering on ASRS reports. 2020 New Trends Civil Aviation (NTCA) (IEEE, Piscataway, NJ), 33–38.Google Scholar
• Kiritchenko S, Matwin S, Famili AF (2004) Hierarchical text categorization as a tool of associating genes with gene ontology codes. Eur. Workshop Data Mining Text Mining Bioinformatics (Pisa, Italy), 30–34.Google Scholar
• Koller D, Sahami M (1997) Hierarchically classifying documents using very few words. Technical report, Stanford InfoLab, Stanford, CA.Google Scholar
• Li A, Luo T, Lu Z, Xiang T, Wang L (2019) Large-scale few-shot learning: Knowledge transfer with class hierarchy. Proc. IEEE/CVF Conf. Comput. Vision Pattern Recognition (IEEE, Piscataway, NJ), 7212–7220.Google Scholar
• Liu L, Zhou T, Long G, Jiang J, Zhang C (2022) Many-class few-shot learning on multi-granularity class hierarchy. IEEE Trans. Knowledge Data Engrg. 34(5):2293–2305.Google Scholar
• National Transportation Safety Board (2008) Aviation coding manual. Accessed September 15, 2021, https://www.ntsb.gov/GILS/Documents/codman.pdf.Google Scholar
• Peng H, Li J, He Y, Liu Y, Bao M, Wang L, Song Y, Yang Q (2018) Large-scale hierarchical text classification with recursively regularized deep graph-CNN. Proc. 2018 World Wide Web Conf. (International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE), 1063–1072.Google Scholar
• Pereira RM, Costa YM, Silla CN Jr (2021) Toward hierarchical classification of imbalanced data using random resampling algorithms. Inform. Sci. 578:344–363.Google Scholar
• Pereira FC, Rodrigues F, Ben-Akiva M (2013) Text analysis in incident duration prediction. Transportation Res. Part C Emerging Tech. 37:177–192.Google Scholar
• Rao AH, Marais K (2020) A state-based approach to modeling general aviation accidents. Reliability Engrg. System Safety 193:106670.Google Scholar
• Rath S, Chow JY (2022) Worldwide city transport typology prediction with sentence-BERT based supervised learning via Wikipedia. Transportation Res. Part C Emerging Tech. 139:103661.Google Scholar
• Robinson SD (2018) Multi-label classification of contributing causal factors in self-reported safety narratives. Safety 4(3):30.Google Scholar
• Ruggero CJ, Kotov R, Hopwood CJ, First M, Clark LA, Skodol AE, Mullins-Sweatt SN, et al. (2019) Integrating the hierarchical taxonomy of psychopathology (HiTOP) into clinical practice. J. Consulting Clinical Psych. 87(12):1069–1084.Google Scholar
• Shi D, Guan J, Zurada J, Manikas A (2017) A data-mining approach to identification of risk factors in safety management systems. J. Management Inform. Systems 34(4):1054–1081.Google Scholar
• Silla CN, Freitas AA (2011) A survey of hierarchical classification across different application domains. Data Mining Knowledge Discovery 22(1):31–72.Google Scholar
• Srinivasan P, Nagarajan V, Mahadevan S (2019) Mining and classifying aviation accident reports. AIAA Aviation 2019 Forum (American Institute of Aeronautics and Astronautics, Reston, VA), 2938.Google Scholar
• Tanguy L, Tulechki N, Urieli A, Hermann E, Raynal C (2016) Natural language processing for aviation safety reports: From classification to interactive analysis. Comput. Indust. 78:80–95.Google Scholar
• Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser Ł, Polosukhin I (2017) Attention is all you need. Advances in Neural Information Processing Systems (Curran Associates Inc., Red Hook, NY), 5998–6008.Google Scholar
• Wang Y, Yao Q, Kwok JT, Ni LM (2020) Generalizing from a few examples: A survey on few-shot learning. ACM Comput. Surveys 53(3):1–34.Google Scholar
• Wu TY, Morgado P, Wang P, Ho CH, Vasconcelos N (2020) Solving long-tailed recognition with deep realistic taxonomic classifier. Eur. Conf. Comput. Vision (Springer, Cham, Switzerland), 171–189.Google Scholar
• Xu C, Geng X (2019) Hierarchical classification based on label distribution learning. Proc. Conf. AAAI Artificial Intelligence 33:5533–5540.Google Scholar
• Yang P, Sun X, Li W, Ma S, Wu W, Wang H (2018) SGM: Sequence generation model for multi-label classification. Preprint, submitted June 15, https://arxiv.org/abs/1806.04822.Google Scholar
• Yao W, Qian S (2021) From Twitter to traffic predictor: Next-day morning traffic prediction using social media data. Transportation Res. Part C Emerging Tech. 124:102938.Google Scholar
• Yelundur A, Giannella C, Megerdoomian K, Pfeifer C (2016) Event classification in foreign language aviation reports. Internat. J. Knowledge Engrg. Data Mining 4(1):54–73.Google Scholar
• Zhang X, Mahadevan S (2020) Bayesian neural networks for flight trajectory prediction and safety assessment. Decision Support Systems 131:113246.Google Scholar
• Zhang X, Srinivasan P, Mahadevan S (2021) Sequential deep learning from NTSB reports for aviation safety prognosis. Safety Sci. 142:105390.Google Scholar
• Zhao X, Yan H, Liu Y (2022) Event extraction for aviation accident reports through attention-based multi-label classification. AIAA AVIATION 2022 Forum (American Institute of Aeronautics and Astronautics, Reston, VA), 3831.Google Scholar