Abstract
The nagoy team participated in the NTCIR-14 QA Lab-PoliInfo’s summarization subtask. This paper describes our summarization system for assembly member speeches using random forest classifiers. Since we encountered an imbalance in the data, we were unable to achieve good results in this subtask when training on all data. To solve this problem, we developed a new summarization system that applies multiple random forest classifiers training on different-sized data sets step by step. As a result, our system achieved good performance, especially in the evaluation by ROUGE scores. In this paper, we also compare our system with a single random forest classifier using probability.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
Two speeches have no sentences.
References
Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001)
Carbonell, J., Goldstein, J.: The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: Proceedings of ACM-SIGIR 1998, pp. 335–336 (1998)
Hirao, T., Isozaki, H., Maeda, E., Matsumoto, Y.: Extracting important sentences with support vector machines. In: Proceedings of the 19th International Conference on Computational Linguistics, vol. 1, pp. 1–7 (2002)
Kimura, Y., et al.: Overview of the NTCIR-14 QA Lab-PoliInfo task. In: Proceedings of the 14th NTCIR Conference (2019)
Kudo, T., Matsumoto, Y.: Japanese dependency analysis using cascaded chunking. In: Proceedings of the 6th Conference on Natural Language Learning 2002 (COLING 2002 Post-Conference Workshops), CoNLL 2002, pp. 63–69 (2002)
Lin, C.-Y.: ROUGE: a package for automatic evaluation of summaries. In: Proceedings of the ACL 2004 Workshop, vol. 8, pp. 74–81 (2004)
Ogawa, Y., Satou, M., Komamizu, T., Toyama, K.: Extracting important sentences with random forest for statute summarization. In: Proceedings of the Annual Conference of JSAI 2019 (2019). (In Japanese)
Acknowledgments
This work was partly supported by JSPS KAKENHI Grant Number 17K00460.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Ogawa, Y., Satou, M., Komamizu, T., Toyama, K. (2019). nagoy Team’s Summarization System at the NTCIR-14 QA Lab-PoliInfo. In: Kato, M., Liu, Y., Kando, N., Clarke, C. (eds) NII Testbeds and Community for Information Access Research. NTCIR 2019. Lecture Notes in Computer Science(), vol 11966. Springer, Cham. https://doi.org/10.1007/978-3-030-36805-0_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-36805-0_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-36804-3
Online ISBN: 978-3-030-36805-0
eBook Packages: Computer ScienceComputer Science (R0)