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Bootstrapping Technique + Embeddings = Emotional Corpus Annotated Automatically

机译:引导技术+嵌入=自动注释情感语料库

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Detecting depression or personality traits, tutoring and student behaviour systems, or identifying cases of cyber-bulling are a few of the wide range of the applications, in which the automatic detection of emotion is crucial. This task can contribute to the benefit of business, society, politics or education. The main objective of our research is focused on the improvement of the supervised emotion detection systems developed so far, through the definition and implementation of a technique to annotate large scale English emotional corpora automatically and with high standards of reliability. Our proposal is based on a bootstrapping process made up two main steps: the creation of the seed using NRC Emotion Lexicon and its extension employing the distributional semantic similarity through words embeddings. The results obtained are promising and allow us to confirm the soundness of the bootstrapping technique combined with the word embedding to label emotional corpora automatically.
机译:检测抑郁症或人格特质,辅导和学生行为系统,或识别网络欺凌的情况是广泛的应用程序中的一些,在这些应用程序中,自动检测情绪至关重要。这项任务可以促进商业,社会,政治或教育的利益。我们研究的主要目标是通过定义和实现一种自动注释大型英语情绪语料库并具有高可靠性标准的技术,来改进迄今开发的监督式情绪检测系统。我们的建议基于一个引导过程,该过程由两个主要步骤组成:使用NRC Emotion词典创建种子,以及通过词嵌入使用分布语义相似性对其进行扩展。所获得的结果是有希望的,并且使我们能够确定自举技术与嵌入单词自动标记情感语料相结合的正确性。

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