基于自然语言处理和机器学习的文本数据情感检测新方法

Subhodeep Banerjee, Shrivasta Goswami, A. Das, Neeloy Saha, Soumyashree Seth, Sagnik Bhattacharya, Sandip Mandal, Uem Kolkata
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引用次数: 0

摘要

摘要:情感可以通过许多可以看到的方式来表达,比如面部表情、手势、语言和书面文字。文本文档中的情感检测本质上是一个基于内容的分类问题,涉及自然语言处理和机器学习领域的概念。本文提出了一种基于文本数据的情感识别解决方案。在博客、评论或任何类型的文本内容中表达的情感直到文本被分析并从数据中检索到情感之前都不会被使用。人工分析海量数据并从中获取信息是不可能的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Approach for Emotion Detection from Text Data using Natural Language Processing and Machine Learning
Abstract - Emotion can be expressed in many ways that can be seen such as facial expression and gestures, speech and by written text. Emotion Detection in text documents is essentially a content– based classification problem involving concepts from the domains of Natural Language Processing as well as Machine Learning. In this paper we are proposing a solution for emotion recognition based on textual data. The emotion expressed in a blog, review or any kind of textual content remains unused until the text is analyzed and the emotion is retrieved from the data. It is impossible to analyze the huge amount of data manually and gain information from it.
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