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        <title>NCYU at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases using Vector Representations</title>
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        <namePart type="given">Jui-Feng</namePart>
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        <namePart type="given">Jian-Cheng</namePart>
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        <namePart type="given">Bo-Wei</namePart>
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    <name type="personal">
        <namePart type="given">Tai-You</namePart>
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            <namePart type="given">Chao-Hong</namePart>
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            <namePart type="given">Nianwen</namePart>
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    <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.</abstract>
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%0 Conference Proceedings
%T NCYU at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases using Vector Representations
%A Yeh, Jui-Feng
%A Tsai, Jian-Cheng
%A Wu, Bo-Wei
%A Kuang, Tai-You
%Y Liu, Chao-Hong
%Y Nakov, Preslav
%Y Xue, Nianwen
%S Proceedings of the IJCNLP 2017, Shared Tasks
%D 2017
%8 December
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F yeh-etal-2017-ncyu
%X 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.
%U https://aclanthology.org/I17-4018
%P 112-117

Markdown (Informal)

[NCYU at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases using Vector Representations](https://aclanthology.org/I17-4018) (Yeh et al., IJCNLP 2017)

• NCYU at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases using Vector Representations (Yeh et al., IJCNLP 2017)

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.