基于贝叶斯和支持向量机的英语文本情感挖掘

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引用次数: 0

摘要

多年来,情感一直吸引着研究人员,这在心理特征、语言、社会主义和互动领域与情感相关的大量研究工作中是显而易见的。人类的情感表现为面部表情、言语、文字以及手势和动作。因此,情感的技术研究沿着几个比例进行,并借鉴了来自各个领域的研究。本文通过尝试从文本中机器学习情感,产生了情感感恩的苦差事。本文介绍了一种从英语文本中挖掘情感的新方法。我们使用了10个类别,从中我们可以提取运动。提出了一种基于支持向量机(SVM)的系统方法来执行给定任务。与现有系统相比,该系统的精度更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EMOTION MINING IN ENGLISH TEXT USING BAYES & SVM APPROACH
Emotions have captivated researchers for years, as is obvious in the huge body of research work related to emotion in area of mental characteristics, language, socialism, and interaction. Human emotion manifests itself in the form of facial expressions, speech utterances, writings, and in gestures and actions. As a result, technical research in emotion has been pursued along several proportions and has drawn upon research from various areas. This paper results in the chore of emotion gratitude by attempting to robotically learn emotions from text. In this paper, a new technique to mine the emotions from an English text has been introduced. We have used 10 categories from which we can extract the motions. Proposed system use bays and SVM approach to perform the given task. The accuracy of the proposed system is better as compared to the existing system.
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