HCCL at SemEval-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports

Mingming Fu, Xuemin Zhao, Yonghong Yan


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
Editors:
Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/S18-1141.pdf