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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/19829
Title: Intelligent Analysis for Personality Detection on Various Indicators by Clinical Reliable Psychological TTH and Stress Surveys
Authors: Rastogi R.
Chaturvedi D.K.
Satya S.
Arora, Navneet
Trivedi P.
Singh A.K.
Sharma A.K.
Singh A.
Das A.K.
Nayak J.
Naik B.
Pati S.K.
Pelusi D.
Published in: Advances in Intelligent Systems and Computing
Proceedings of 1st International Conference on Computational Intelligence in Pattern Recognition, CIPR 2019
Abstract: Psychologists seek to measure personality to analyze the human behavior through a number of methods. As the personality of an individual affects all aspects of a person’s performances, even how he reacts to situations in his social life, academics, job, or personal life. The purpose of this research article is to enlighten the use of personality detection test in an individual’s personal, academics, career or social life, and also provide possible methods to perform personality detection test. One of the possible solutions to detect the personality study is based on the individual’s sense of humor. Throughout the twentieth century, psychologists show an outgoing interest in the study of an individual’s sense of humor. Since individual differences in humor and their relation to psychological well-being can be used to detect the particular personality traits. We have used machine learning used for personality detection that involves the development and initial validation of questionnaire, which assesses four dimensions relating to individual differences in uses of humor. 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), and Self-defeating (humor use to enhance relationships at the expense of self).
Citation: Advances in Intelligent Systems and Computing, 2020, 127- 143
URI: https://doi.org/10.1007/978-981-13-9042-5_12
http://repository.iitr.ac.in/handle/123456789/19829
Issue Date: 2020
Publisher: Springer
Keywords: Affiliative
Aggressive
Anaconda
Decision tree
Linear regression
Machine learning
Multiple linear regression
Personality
Python
Random forest
Regression
Self-defeating
Self-enhancing
Sense of humor
Decision trees
Learning systems
Linear regression
Machine learning
Pattern recognition
Surveys
Affiliative
Aggressive
Anaconda
Multiple linear regressions
Personality
Python
Random forests
Regression
Self-defeating
Self-enhancing
Sense of
ISBN: 9.78981E+12
ISSN: 21945357
Author Scopus IDs: 57192103103
12809516500
55897679400
15130971300
57210121940
57210113968
57210115129
57210113886
Author Affiliations: Rastogi, R., Department of Computer Science & Engineering, ABESEC, Ghaziabad, 201009, India
Chaturvedi, D.K., Department of Electrical Engineering, DEI-Agra, Agra, India
Satya, S., Department of Rural Development, IIT-Delhi, Delhi, India
Arora, N., Dep
Funding Details: The authors are obliged for the guidance of ABES Engineering College staffs and faculties. Python mentor, Asst. Prof., Mr. Shubham Sidana, Asso. Prof., Mr. Abhishek Goyal, and evaluation team of experimental presentation to understand the concept well and.
Corresponding Author: Rastogi, R.; Department of Computer Science & Engineering, India; email: rohit.rastogi@abes.ac.in
Appears in Collections:Conference Publications [ME]

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