Abstract
This paper describes HCCL team systems that participated in SemEval 2018 Task 8: SecureNLP (Semantic Extraction from cybersecurity reports using NLP). To solve the problem, our team applied a neural network architecture that benefits from both word and character level representaions automatically, by using combination of Bi-directional LSTM, CNN and CRF (Ma and Hovy, 2016). Our system is truly end-to-end, requiring no feature engineering or data preprocessing, and we ranked 4th in the subtask 1, 7th in the subtask2 and 3rd in the SubTask2-relaxed.- Anthology ID:
- S18-1141
- Volume:
- Proceedings of the 12th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 874–877
- Language:
- URL:
- https://aclanthology.org/S18-1141
- DOI:
- 10.18653/v1/S18-1141
- Cite (ACL):
- Mingming Fu, Xuemin Zhao, and Yonghong Yan. 2018. HCCL at SemEval-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 874–877, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- HCCL at SemEval-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports (Fu et al., SemEval 2018)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/S18-1141.pdf