@inproceedings{fu-etal-2018-hccl,
title = "{HCCL} at {S}em{E}val-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports",
author = "Fu, Mingming and
Zhao, Xuemin and
Yan, Yonghong",
editor = "Apidianaki, Marianna and
Mohammad, Saif M. and
May, Jonathan and
Shutova, Ekaterina and
Bethard, Steven and
Carpuat, Marine",
booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S18-1141",
doi = "10.18653/v1/S18-1141",
pages = "874--877",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T HCCL at SemEval-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports
%A Fu, Mingming
%A Zhao, Xuemin
%A Yan, Yonghong
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Bethard, Steven
%Y Carpuat, Marine
%S Proceedings of the 12th International Workshop on Semantic Evaluation
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F fu-etal-2018-hccl
%X 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.
%R 10.18653/v1/S18-1141
%U https://aclanthology.org/S18-1141
%U https://doi.org/10.18653/v1/S18-1141
%P 874-877
Markdown (Informal)
[HCCL at SemEval-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports](https://aclanthology.org/S18-1141) (Fu et al., SemEval 2018)
ACL