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Extraction of Relationship Between Characters in Narrative Summaries

机译:叙事摘要中人物之间关系的提取

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摘要

Distinguishing relationships between people plays a vital role in understanding of narratives. We can experience different kinds of relationships like family, friendship, hostility, romantic love, etc. We know that Narratives are rich reflections of such relationships. Also extraction of relationship between characters is more helpful in understanding the person's actions, goals and behavior. In actual case relationships between people changes over time. So considering the dynamic nature of relationships will provide a better understanding of narratives. Existing research on analysis of people's relationships in the text has been limited Two simple schemes that use traditional machine learning algorithms. Relevant to this context, this paper proposes a system for extracting interpersonal relationships using deep learning concept convolutional neural network (CNN). The proposed approach produces a better performance over the competitive baseline model.
机译:区分人与人之间的关系在理解叙事中起着至关重要的作用。我们可以体验到各种关系,例如家庭,友谊,敌对,浪漫爱情等。我们知道叙事是这种关系的丰富体现。同样,提取人物之间的关系也有助于理解人的行为,目标和行为。在实际情况下,人与人之间的关系会随着时间而改变。因此,考虑关系的动态性质将提供对叙事的更好理解。现有的关于文本中人际关系分析的研究受到限制,这是两个使用传统机器学习算法的简单方案。与此相关,本文提出了一种使用深度学习概念卷积神经网络(CNN)提取人际关系的系统。所提出的方法在竞争基准模型上产生了更好的性能。

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