no code implementations • ROCLING 2021 • Po-Han Chen, Yu-Xiang Zeng, Lung-Hao Lee
Due to the lack of publicly available datasets for multi-label classification of Chinese medical questions, we crawled questions from medical question/answer forums and manually annotated them using eight predefined classes: persons and organizations, symptom, cause, examination, disease, information, ingredient, and treatment.
no code implementations • ROCLING 2022 • Lung-Hao Lee, Chao-Yi Chen, Liang-Chih Yu, Yuen-Hsien Tseng
This paper describes the ROCLING-2022 shared task for Chinese healthcare named entity recognition, including task description, data preparation, performance metrics, and evaluation results.
Chinese Named Entity Recognition named-entity-recognition +1
no code implementations • ROCLING 2022 • Szu-Chi Huang, Cheng-Fu Cao, Po-Hsun Liao, Lung-Hao Lee, Po-Lei Lee, Kuo-Kai Shyu
It’s difficult to optimize individual label performance of multi-label text classification, especially in those imbalanced data containing long-tailed labels.
no code implementations • ROCLING 2021 • Hao-Chuan Kao, Man-Chen Hung, Lung-Hao Lee, Yuen-Hsien Tseng
We use Hypergraph Attention Networks (HyperGAT) to recognize multiple labels of Chinese humor texts.
no code implementations • ROCLING 2021 • Man-Chen Hung, Chao-Yi Chen, Pin-Jung Chen, Lung-Hao Lee
On ROCLING-2021 test set, our used MacBERT model achieves 0. 611 of MAE and 0. 904 of r in the valence dimensions; and 0. 938 of MAE and 0. 549 of r in the arousal dimension.
no code implementations • ROCLING 2021 • Yuh-Shyang Wang, Chao-Yi Chen, Lung-Hao Lee
We propose the mixed-attention-based Generative Adversarial Network (named maGAN), and apply it for citation intent classification in scientific publication.
no code implementations • SemEval (NAACL) 2022 • Lung-Hao Lee, Chien-Huan Lu, Tzu-Mi Lin
This study describes the model design of the NCUEE-NLP system for the Chinese track of the SemEval-2022 MultiCoNER task.
Chinese Named Entity Recognition named-entity-recognition +2
no code implementations • SMM4H (COLING) 2022 • Tzu-Mi Lin, Chao-Yi Chen, Yu-Wen Tzeng, Lung-Hao Lee
This study describes our proposed system design for the SMM4H 2022 Task 8.
no code implementations • NAACL (BioNLP) 2021 • Lung-Hao Lee, Po-Han Chen, Yu-Xiang Zeng, Po-Lei Lee, Kuo-Kai Shyu
This study describes the model design of the NCUEE-NLP system for the MEDIQA challenge at the BioNLP 2021 workshop.
no code implementations • SMM4H (COLING) 2020 • Lung-Hao Lee, Po-Han Chen, Hao-Chuan Kao, Ting-Chun Hung, Po-Lei Lee, Kuo-Kai Shyu
This study describes our proposed model design for the SMM4H 2020 Task 1.
no code implementations • NAACL (SMM4H) 2021 • Lung-Hao Lee, Man-Chen Hung, Chien-Huan Lu, Chang-Hao Chen, Po-Lei Lee, Kuo-Kai Shyu
This study describes our proposed model design for SMM4H 2021 shared tasks.
no code implementations • WS 2019 • Lung-Hao Lee, Yi Lu, Po-Han Chen, Po-Lei Lee, Kuo-Kai Shyu
This study describes the model design of the NCUEE system for the MEDIQA challenge at the ACL-BioNLP 2019 workshop.
no code implementations • WS 2018 • Yuen-Hsien Tseng, Lung-Hao Lee, Yu-Ta Chien, Chun-Yen Chang, Tsung-Yen Li
Text clustering is a powerful technique to detect topics from document corpora, so as to provide information browsing, analysis, and organization.
no code implementations • IJCNLP 2017 • Liang-Chih Yu, Lung-Hao Lee, Jin Wang, Kam-Fai Wong
This paper presents the IJCNLP 2017 shared task on Dimensional Sentiment Analysis for Chinese Phrases (DSAP) which seeks to identify a real-value sentiment score of Chinese single words and multi-word phrases in the both valence and arousal dimensions.
no code implementations • IJCNLP 2017 • Gaoqi Rao, Baolin Zhang, Endong Xun, Lung-Hao Lee
This paper presents the IJCNLP 2017 shared task for Chinese grammatical error diagnosis (CGED) which seeks to identify grammatical error types and their range of occurrence within sentences written by learners of Chinese as foreign language.
no code implementations • SEMEVAL 2017 • Lung-Hao Lee, Kuei-Ching Lee, Yuen-Hsien Tseng
This study describes the design of the NTNU system for the ScienceIE task at the SemEval 2017 workshop.
no code implementations • WS 2016 • Lung-Hao Lee, Gaoqi Rao, Liang-Chih Yu, Endong Xun, Baolin Zhang, Li-Ping Chang
This paper presents the NLP-TEA 2016 shared task for Chinese grammatical error diagnosis which seeks to identify grammatical error types and their range of occurrence within sentences written by learners of Chinese as foreign language.
no code implementations • LREC 2012 • Chieh-Jen Wang, Shuk-Man Cheng, Lung-Hao Lee, Hsin-Hsi Chen, Wen-shen Liu, Pei-Wen Huang, Shih-Peng Lin
This paper proposes a method to construct an evaluation dataset from microblogs for the development of recommendation systems.