Paper Contents
Abstract
Personality prediction is a crucial aspect of understanding human behaviour, decision-making, and social interactions. TheOCEAN model, comprising Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism, is a widely acceptedframework for personality assessment. The concept of using ocean models to predict personality traits based on machinelearning (ML) is an emerging field in the intersection of psychology, computer science, and physics. The Ocean Model theorysuggests that personality traits can be viewed as a set of interconnected waves or patterns that ebb and flow over time, muchlike the oceans tides. By analysing these patterns and fluctuations using ML algorithms, it may be possible to predict anindividuals personality traits with a high degree of accuracy. This study proposes a machine learning approach to predictpersonality traits based on the OCEAN model. We collected a dataset of participantsresponses to a personality questionnaireand applied various machine learning algorithms, including K- Means Clustering, Gaussian Mixture Model to predict theirpersonality scores. Our results show that the proposed approach achieves high accuracy in predicting personality traits, withshowing the highest prediction accuracy. The study demonstrates the potential of machine learning in personality predictionand provides insights into the relationships between personality traits and behavioural patterns. The findings have implicationsfor applications in human resources, marketing, and mental health. This abstract presents an overview of the Ocean Modeltheory, its potential applications in personality assessment, and the challenges and limitations associated with this approach.Keywords: Personality prediction ,Machine Learning, K- Means Clustering, Gaussian Mixture Model, Ocean Model.
Copyright
Copyright © 2025 Kanchan Raju Sangle. This is an open access article distributed under the Creative Commons Attribution License.
