no code implementations • EMNLP 2021 • Han Qin, Guimin Chen, Yuanhe Tian, Yan Song
Aspect-based sentiment analysis (ABSA) predicts the sentiment polarity towards a particular aspect term in a sentence, which is an important task in real-world applications.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2
no code implementations • SemEval (NAACL) 2022 • Weichao Gan, Yuanping Lin, Guangbo Yu, Guimin Chen, Qian Ye
This paper describes our system, which placed third in the Multilingual Track (subtask 11), fourth in the Code-Mixed Track (subtask 12), and seventh in the Chinese Track (subtask 9) in the SemEval 2022 Task 11: MultiCoNER Multilingual Complex Named Entity Recognition.
1 code implementation • ACL 2021 • Han Qin, Guimin Chen, Yuanhe Tian, Yan Song
Arabic diacritization is a fundamental task for Arabic language processing.
1 code implementation • ACL 2021 • Yuanhe Tian, Guimin Chen, Yan Song, Xiang Wan
Syntactic information, especially dependency trees, has been widely used by existing studies to improve relation extraction with better semantic guidance for analyzing the context information associated with the given entities.
Ranked #12 on Relation Extraction on SemEval-2010 Task-8
2 code implementations • NAACL 2021 • Yuanhe Tian, Guimin Chen, Yan Song
It is popular that neural graph-based models are applied in existing aspect-based sentiment analysis (ABSA) studies for utilizing word relations through dependency parses to facilitate the task with better semantic guidance for analyzing context and aspect words.
Ranked #2 on Aspect-Based Sentiment Analysis (ABSA) on MAMS
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA)
1 code implementation • EACL 2021 • Yuanhe Tian, Guimin Chen, Yan Song
Aspect-level sentiment analysis (ASA) has received much attention in recent years.
1 code implementation • COLING 2020 • Guimin Chen, Yuanhe Tian, Yan Song
End-to-end aspect-based sentiment analysis (EASA) consists of two sub-tasks: the first extracts the aspect terms in a sentence and the second predicts the sentiment polarities for such terms.