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

• Published in: International journal of technology and human interaction Vol. 16; no. 1; pp. 94 - 104
• Main Authors: Shakeel, P Mohamed, Baskar, S
• Format: Journal Article
• Language: English
• Published: Hershey IGI Global 01.01.2020
• Subjects: Analysis; Blogs; Boredom; Classification; Communication; Computational linguistics; Data mining; Electronic documents; Emotions; Feature selection; Information retrieval; Knowledge discovery; Labels; Language processing; Machine learning; Man-machine interfaces; Methods; Natural language interfaces; Natural language processing; Online instruction; Sentiment analysis; Support vector machines; Web 2.0
• ISSN: 1548-3908; 1548-3916
• DOI: 10.4018/IJTHI.2020010107

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.