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Computational Approach for Personality Detection on Attributes: An IoT-MMBD-Enabled Environment

Computational Approach for Personality Detection on Attributes: An IoT-MMBD-Enabled Environment
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Author(s): Rohit Rastogi (Dayalbagh Educational Institute, India & ABES Engineering College, India), Devendra Kumar Chaturvedi (Dayalbagh Educational Institute, India)and Mayank Gupta (Tata Consultancy Services, Noida, India)
Copyright: 2020
Pages: 31
Source title: Handbook of Research on Advancements of Artificial Intelligence in Healthcare Engineering
Source Author(s)/Editor(s): Dilip Singh Sisodia (National Institute of Technology, Raipur, India), Ram Bilas Pachori (Indian Institute of Technology, Indore, India)and Lalit Garg (University of Malta, Malta)
DOI: 10.4018/978-1-7998-2120-5.ch016

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Abstract

Psychologists seek to measure personality to analyze the human behavior through a number of methods, which are self-enhancing (humor use to enhance self), affiliative (humor use to enhance the relationship with other), aggressive (humor use to enhance the self at the expense of others), self-defeating (the humor use to enhance relationships at the expense of self). The purpose of this chapter is to enlighten the use of personality detection test in academics, job placement, group-interaction, and self-reflection. This chapter provides the use of multimedia and IoT to detect the personality and to analyze the different human behaviors. It also includes the concept of big data for the storage and processing the data that will be generated while analyzing the personality through IoT. Linear regression and multiple linear regression are proved to be the best, so they can be used to implement the prediction of personality of individuals. Decision tree regression model has achieved minimum accuracy in comparison to others.

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