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        <title>Lexicon Guided Attentive Neural Network Model for Argument Mining</title>
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        <namePart type="given">Jian-Fu</namePart>
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            <title>Proceedings of the 6th Workshop on Argument Mining</title>
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    <abstract>Identification of argumentative components is an important stage of argument mining. Lexicon information is reported as one of the most frequently used features in the argument mining research. In this paper, we propose a methodology to integrate lexicon information into a neural network model by attention mechanism. We conduct experiments on the UKP dataset, which is collected from heterogeneous sources and contains several text types, e.g., microblog, Wikipedia, and news. We explore lexicons from various application scenarios such as sentiment analysis and emotion detection. We also compare the experimental results of leveraging different lexicons.</abstract>
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%0 Conference Proceedings
%T Lexicon Guided Attentive Neural Network Model for Argument Mining
%A Lin, Jian-Fu
%A Huang, Kuo Yu
%A Huang, Hen-Hsen
%A Chen, Hsin-Hsi
%Y Stein, Benno
%Y Wachsmuth, Henning
%S Proceedings of the 6th Workshop on Argument Mining
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F lin-etal-2019-lexicon
%X Identification of argumentative components is an important stage of argument mining. Lexicon information is reported as one of the most frequently used features in the argument mining research. In this paper, we propose a methodology to integrate lexicon information into a neural network model by attention mechanism. We conduct experiments on the UKP dataset, which is collected from heterogeneous sources and contains several text types, e.g., microblog, Wikipedia, and news. We explore lexicons from various application scenarios such as sentiment analysis and emotion detection. We also compare the experimental results of leveraging different lexicons.
%R 10.18653/v1/W19-4508
%U https://aclanthology.org/W19-4508
%U https://doi.org/10.18653/v1/W19-4508
%P 67-73

Markdown (Informal)

[Lexicon Guided Attentive Neural Network Model for Argument Mining](https://aclanthology.org/W19-4508) (Lin et al., ArgMining 2019)

• Lexicon Guided Attentive Neural Network Model for Argument Mining (Lin et al., ArgMining 2019)

ACL

• Jian-Fu Lin, Kuo Yu Huang, Hen-Hsen Huang, and Hsin-Hsi Chen. 2019. Lexicon Guided Attentive Neural Network Model for Argument Mining. In Proceedings of the 6th Workshop on Argument Mining, pages 67–73, Florence, Italy. Association for Computational Linguistics.