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

Automatic Human Emotion Classification in Web Document Using Fuzzy Inference System (FIS): Human Emotion Classification
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Author(s): P Mohamed Shakeel (Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia) and S Baskar (Department of Electronics and Communication Engineering, Karpagam Academy of Higher Education, Coimbatore, India)
Copyright: 2020
Volume: 16
Issue: 1
Pages: 11
Source title: International Journal of Technology and Human Interaction (IJTHI)
Editor(s)-in-Chief: Anabela Mesquita (ISCAP/IPP and Algoritmi Centre, University of Minho, Portugal) and Chia-Wen Tsai (Ming Chuan University, Taiwan)
DOI: 10.4018/IJTHI.2020010107

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Abstract

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.

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