Acknowledgement
본 연구는 국토교통과학기술진흥원의 "빅데이터 기반 항공안전관리 기술개발 및 플랫폼 구축"(20BDAS-B158275-01)의 일환으로 수행되었으며, 지원에 감사드립니다.
References
- Paek. H., Kim. J. H., Lim. J. J, Jeon. S., and Choi. Y. J., "Quantitative safety risk assessment using aviation safety data", Journal of the Korean Society for Aviation and Aeronautics, 30(4), 2022, pp.145-158. https://doi.org/10.12985/ksaa.2022.30.4.145
- ICAO, "Annex 13 - Aircraft Accident and Incident Investigation 12th Edition", 2020.
- MOLIT, "Aviation Safety Act, Article 59", 2021.
- de Vries, V., "Classification of aviation safety reports using machine learning", 2020 International Conference on Artificial Intelligence and Data Analytics for Air Transportation, IEEE, Singapore, 2020, pp.1-6.
- Karanikas, N., Nederend, J., "The controllability classification of safety events and its application to aviation investigation reports", Safety Science, 108, 2018, pp.89-103. https://doi.org/10.1016/j.ssci.2018.04.025
- MOLIT, "Aviation Safety Enforcement, Article 26", 2023.
- MOLIT, "Aviation Safety Regulation, Enclosure No.65", 2023.
- Blei, D. M., Ng, A. Y., and Jordan, M. I., "Latent dirichlet allocation", Journal of Machine Learning Research, 3, 2003, pp.993-1022.
- Nam, S., Ha, C., and Lee, H. C., "Redesigning in-flight service with service blueprint based on text analysis", Sustainability, 10(12), 2018, Online Published.
- Bastani, K., Namavari, H., and Shaffer, J., "Latent dirichlet allocation (LDA) for topic modeling of the CFPB consumer complaints", Expert Systems with Applications, 127, 2019, pp.256-271. https://doi.org/10.1016/j.eswa.2019.03.001
- Bao, S., Xu, S., Zhang, L., Yan, R., Su, Z., Han, D., and Yu, Y., "Mining social emotions from affective text", IEEE Transactions on Knowledge and Data Engineering, 24(9), 2011, pp.1658-1670. https://doi.org/10.1109/TKDE.2011.188
- Rao, Y., Lei, J., Wenyin, L., Li, Q., and Chen, M., "Building emotional dictionary for sentiment analysis of online news", World Wide Web, 17, 2014, pp.723-742. https://doi.org/10.1007/s11280-013-0221-9
- Kozareva, Z., "Everyone likes shopping! multi-class product categorization for e-commerce" In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2015, pp. 1329-1333.
- Kim, S. W., and Gil, J. M., "Research paper classification systems based on TF-IDF and LDA schemes. Human-centric", Computing and Information Sciences, 9, 2019, pp.1-21. https://doi.org/10.1186/s13673-019-0192-7
- Hasan, M., Rahman, A., Karim, M. R., Khan, M. S. I., and Islam, M. J., "Normalized approach to find optimal number of topics in Latent Dirichlet Allocation (LDA)", Proceedings of International Conference on Trends in Computational and Cognitive Engineering, TCCE, Singapore, 2021, pp.341-354.
- Aletras, N., Stevenson, M., "Evaluating topic coherence using distributional semantics", 10th International Conference on Computational Semantics, IWCS, 2013, pp.13-22.
- Mimno, D., Wallach, H., Talley, E., Leenders, M., and McCallum, A., "Optimizing semantic coherence in topic models", 2011 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, Scotland, 2011, pp.262-272.
- Newman, D., Lau, J. H., Grieser, K., and Baldwin, T., "Automatic evaluation of topic coherence", The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Association for Computational Linguistics, California, 2010, pp.100-108.
- Stevens, K., Kegelmeyer, P., Andrzejewski, D., and Buttler, D., "Exploring topic coherence over many models and many topics", 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Association for Computational Linguistics, Korea, 2012, pp.952-961.
- Nam, S., and Lee, H. C., "A text analytics-based importance performance analysis and its application to airline service", Sustain- ability, 11(21), 2019, Online Published.
- Bi, J. W., Liu, Y., Fan, Z. P., and Zhang, J., "Wisdom of crowds: Conducting importance-performance analysis (IPA) through online reviews", Tourism Management, 70, 2019, pp.460-478. https://doi.org/10.1016/j.tourman.2018.09.010