Nikhil Kumar1, Mrinal Kumar1, Devo Prasad Paitandy1, Vaishnavi Kumari1 and Amar Nath Singh2*
1Department of MCA, Amity University, Jharkhand, India
2Department of Computer Science and Engineering, Amity University, Jharkhand, India
*Corresponding Author: Amar Nath Singh, Department of Computer Science and Engineering, Amity University, Jharkhand, India.
Received: March 11, 2020; Published: April 27, 2020
Artificial Intelligence is the most popular area of research which is now a days plays a vital role in almost all field of science. Today we are living in the era of technology. We are mostly getting all sort of applications for our basic needs which is powered by AI. Very recently, we came across the application Amazon ad on “Amazon Echo”, a device which responds to the voice and answers all possible questions which are stored in the device. This is an example of Artificial Intelligence where the machine is smart enough to identify the request and produce the response . Here the machine is going to analyze the emotion of the person and based on that, it finds the search result and accordingly it produces the response. It is the application where the search result depends on many factors like emotion, anger etc. In this case the finding of emotions is a very difficult task. To find the optimal range of the human emotions We have studied the responses of 1000 faculty members, having wide teaching experience, different designations such as Asst Professor, Professor and lecturers. During the analysis we also found that the emotion factors are also get vary gender wise. Ie, the emotion factor of a man is always less than women in certain case. In this paper we are going to propose a learning model based on the approach of emotion factor.
Keywords: Human Emotion; Emotion Intelligence; AI; Machine Learning; Recognition
Citation: Amar Nath Singh., et al. “Development of E-Learning Model by Analyzing the Emotion Intelligence Factor of Human Using the AI and Machine Learning”Acta Scientific Computer Sciences 2.5 (2020): 04-07.
Copyright: © 2020 Amar Nath Singh., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.