Authors : Dr. Mallika Natarajan; Dr. Veeramani Veerapathran

Volume/Issue : Volume 10 - 2025, Issue 1 - January

Google Scholar : https://tinyurl.com/y3kvcpum

Scribd : https://tinyurl.com/53s3dtwx

DOI : https://doi.org/10.5281/zenodo.14716996

Abstract : Personality prediction, a critical task in various fields such as human resources, education, and marketing, often relies on subjective assessments or limited data. To address these limitations, this paper proposes a novel intelligent system (NFSAWIS) for personality prediction using Neutrosophic Fuzzy Set theory and the Simple Additive Weighting (SAW) method. Neutrosophic Fuzzy sets, capable of handling uncertainty, indeterminacy, and inconsistency, are employed to represent the inherent ambiguity in personality assessment. The SAW method, a simple yet effective multi-criteria decision-making tool, is adapted to aggregate the scores derived from different CV features. By extracting meaningful features from CVs, such as educational background, hands on experience, skill sets, and achievements, our framework will provide valuable insights of an individual's capability. These features are then processed using Neutrosophic Fuzzy logic to account for the inherent subjectivity and ambiguity in CV interpretation. Through rigorous experiments and evaluations, we demonstrate the effectiveness of our proposed framework in accurately predicting personality traits from CVs. Our findings demonstrate the significant potential of integrating Neutrosophic Fuzzy logic with Curriculum Vitae (CV) analysis for more objective and reliable personality assessments. Furthermore, by leveraging Generative AI, such as GPT-3, the final reports can be efficiently and effectively disseminated to all relevant stakeholders.

Keywords : Personality prediction, Neutrosophic Fuzzy logic, SAW (Simple Additive Weighting), Curriculum Vitae analysis, Intelligent system, NLP (Natural Language Processing)

References :

1. Rachid, Ababou, Jean-Marie, Marcoux., Michel, Quintard. (2023). Fuzzy Set Characterization of Uncertainty (Fuzzy Variables). Springer Briefs in applied sciences and technology, doi: 10.1007/978-981-99-6241-9_4
2. Yash, Mor, Rupali, Sawant. (2023). Personality Prediction Using Psychometric and CV Analysis.   doi: 10.1109/gcitc60406.2023.10426233
3. Rutuja, Narwade., Srujami, Palkar., Isha, Zade., Nidhi, Sanghavi. (2022). Personality Prediction with CV Analysis. International Journal for Science Technology and Engineering, doi: 10.22214/ijraset.2022.41359.
4. Alakh, Arora.N, K. Arora. (2020). Personality Prediction System Through CV Analysis. Advances in intelligent systems and computing, doi: 10.1007/978-981-15-1518-7_28
5. Gagandeep, Kaur, Shruti, Maheshwari. (2019). Personality Prediction through Curriculam Vitae Analysis involving Password Encryption and Prediction Analysis.   
6. Muskan, Goyal., Shreyam, Shah., Aakash, Sangani., Bhoomika, Valani., Neha, Ram. (2022). Job Role and Personality Prediction Using CV and Text Analysis. International Journal for Science Technology And Engineering, doi: 10.22214/ijraset.2022.47201
7. Florentin, Smarandache. (2018). Neutropsychic Personality: A Mathematical Approach to Psychology. Social Science Research Network. 
8. Hong-yu, Zhang, Jian-qiang, Wang. (2017). A Projection-Based Todim Method Under Multi-Valued Neutrosophic Environments and Its Application in Personnel Selection.
9. Rajalakshmi, Krishnamurthi., Mukta, Goyal. (2018). Automatic Detection of Career Recommendation Using Fuzzy Approach. Journal of Information Technology Research, doi: 10.4018/JITR.2018100107
10. Peide, Liu., Lili, Zhang. (2017). An Extended Multiple Criteria Decision Making Method Based on Neutrosophic Hesitant Fuzzy Information.  
11. Ilanthenral, Kandasamy., Florentin, Smarandache. (2016). Triple Refined Indeterminate Neutrosophic Sets for personality classification.   doi: 10.1109/SSCI.2016.7850153
12. Ravi et. el, Ahmed, Dheyaa, Radhi., Lateef, Harshavardhan. (2022). Neutrosophic Sets in Big Data Analytics: A Novel Approach for Feature Selection and Classification. International journal of neutrosophic science, doi: 10.54216/ijns.250138
13. Dragisa et al., Hatice, Ercan-Teksen. (2021). Multi-criteria Decision Making Problem with Triangular Fuzzy Neutrosophic Sets.   doi: 10.1007/978-3-030-85577-2_43.
14. Stanujkic, Smarandache, Florentin., Zavadskas, Edmunds, Kazimieras., Meidute-Kavaliauskiene, Ieva. (2021). Multiple-criteria Decision-making Based on the Use of Single-valued Neutrosophic Sets and Similarity Measures. Economic Computation and Economic Cybernetics Studies and Research, doi: 10.24818/18423264/55.2.21.01