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Human Abnormality Detection Based on Bengali Text by Mridha, M. F. ;Mridha, M. F. ;Rahman, Md Saifur ;Rahman, Md. Saifur ;Ohi, Abu Quwsar ;Ohi, Abu Quwsar is a scholarly article available to read on EtoBox.

What is Human Abnormality Detection Based on Bengali Text about?

In the field of natural language processing and human-computer interaction, human attitudes and sentiments have attracted the researchers. However, in the field of humancomputer interaction, human abnormality detection has not been investigated extensively and most works depend on imagebased information. In natural language processing, effective meaning can potentially convey by all words. Each word may bring out difficult encounters because of their semantic connection with ideas or categories. In this paper, an efficient and effective human abnormality detection model is introduced, that only uses Bengali text. This proposed model can recognize whether the person is in a normal or abnormal state by analyzing their typed Bengali text. To the best of our knowledge, this is the first attempt in developing a text based human abnormality detection system. We have created our Bengali dataset (contains 2000 sentences) that is generated by voluntary conversations. We have performed the comparative analysis by using Naïve Bayes and Support Vector Machine as classifiers. Two different feature extraction techniques count vector, and TF-IDF is used to experiment on our constructed dataset. W

Author

Mridha, M. F. ;Mridha, M. F. ;Rahman, Md Saifur ;Rahman, Md. Saifur ;Ohi, Abu Quwsar ;Ohi, Abu Quwsar

Publisher

IEEE

Published

2020

Language

EN