Abstract
This paper presents two vector representations proposed by National Chiayi University (NCYU) about phrased-based sentiment detection which was used to compete in dimensional sentiment analysis for Chinese phrases (DSACP) at IJCNLP 2017. The vector-based sentiment phraselike unit analysis models are proposed in this article. E-HowNet-based clustering is used to obtain the values of valence and arousal for sentiment words first. An out-of-vocabulary function is also defined in this article to measure the dimensional emotion values for unknown words. For predicting the corresponding values of sentiment phrase-like unit, a vectorbased approach is proposed here. According to the experimental results, we can find the proposed approach is efficacious.- Anthology ID:
- I17-4018
- Volume:
- Proceedings of the IJCNLP 2017, Shared Tasks
- Month:
- December
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Editors:
- Chao-Hong Liu, Preslav Nakov, Nianwen Xue
- Venue:
- IJCNLP
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 112–117
- Language:
- URL:
- https://aclanthology.org/I17-4018
- DOI:
- Cite (ACL):
- Jui-Feng Yeh, Jian-Cheng Tsai, Bo-Wei Wu, and Tai-You Kuang. 2017. NCYU at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases using Vector Representations. In Proceedings of the IJCNLP 2017, Shared Tasks, pages 112–117, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- NCYU at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases using Vector Representations (Yeh et al., IJCNLP 2017)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/I17-4018.pdf