Machine Learning Powered Compatible People Proposer Based on Personality Traits

EasyChair Preprint 2511

Abstract

The aim is to suggest groups of various people that are compatible working with each other and have similar thinking by analyzing their personality traits obtained or inferred by their speeches, social media updates, views, etc. The textual data (containing non-ASCII characters too) is firstly filtered and then fed to a machine learning model which will spit out 27 different numeric values corresponding to different personality traits. The obtained dataset is then dimensionally reduced for better usage ahead. Then a visual 3D graph is plotted where compatible people groups are displayed as clusters.

Finally, we can make groups as the clusters in graph which could surely lead to better throughput in the tasks performed by groups

Keyphrases: NLU, PCA, personality insights, personality traits

@booklet{EasyChair:2511,
  author    = {Gaurav Goswami and Divyanshu Gaur and Eshani Agarwal and Enosh Kumar and Mukesh Rawat},
  title     = {Machine Learning Powered Compatible People Proposer Based on Personality Traits},
  howpublished = {EasyChair Preprint 2511},
  year      = {EasyChair, 2020}}