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Automatic Human Emotion Classification in Web Document Using Fuzzy Inference System (FIS): Human Emotion Classification

机译:使用模糊推理系统(FIS)在Web文档中自动进行人类情感分类:人类情感分类

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摘要

Textual information mining deals with various information extraction methods that can be evolved from the rapid growth of textual information through human machine interface for analyzing emotions which are taken by a facial expression. The problem of emotions in text is concerned with the fast development of web 2.0 documents that are assigned by users with emotion labels, namely: sadness, surprise, happiness, empathy, anger, warmness, boredom, and amusement. Such emotions can give a new characteristic for document categorization. Textual information mining deals with various information extraction methods that can evolved from the rapid growth of textual information through a human machine interface for analyzing emotions, which are taken by a facial expression. The problem of emotions from text is concerned with the fast development of web 2.0 documents that are assigned by users with emotion labels. Such emotions can give a new characteristic for document categorization.
机译:文本信息挖掘处理各种信息提取方法,这些方法可以从文本信息的快速增长通过人机界面演变而来,以分析面部表情所产生的情感。文本中的情感问题与用户分配了带有情感标签的Web 2.0文档的快速开发有关,这些标签包括:悲伤,惊奇,幸福,同情,愤怒,热情,无聊和娱乐。这样的情绪可以为文档分类提供新的特征。文本信息挖掘处理各种信息提取方法,这些方法可以从文本信息的快速增长,通过人机界面来分析面部表情所采用的情感,从而演变而来。来自文本的情感问题与用户为情感标签分配的Web 2.0文档的快速开发有关。这样的情绪可以为文档分类提供新的特征。

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