Career Reactant: Transforming Job Search with AI-Enhanced Recommendation Algorithms

Vunnam, Srikanth (2025) Career Reactant: Transforming Job Search with AI-Enhanced Recommendation Algorithms. Masters thesis, Dublin, National College of Ireland.

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Abstract

This paper introduces a detailed description of Career Reactant, an AI-controlled hybrid job recommendation platform that promotes greater individuality, transparency, and ethical conformance in online job matching. Conventional systems can perform based on an anti-keyword tree and do not make use of user context, hence giving irrelevant or biased suggestions. To overcome these drawbacks, the paper will combine content-based filtering, collaborative filtering, and deep learning with PyTorch, and NLP will be applied and used to suggest skills. Experiments were conducted over publicly-available datasets and model performance was captured by technical measures like the F1-score and the AUC-ROC and also through user-centred measures like the click-through rate. Ethics was also incorporated into the product in terms of data privacy, data bias, fairness-aware design and adherence to GDPR. The learning system was implemented on an interactive Gradio interface where real-time feedback and immediate adjustment of the model was possible. The results substantiate the conclusion that Career Reactant enhances the relevance and transparency of recommendation, providing a scalable (and user-specific) method of addressing the new terrain of digital employment.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Anadh, Devanshu UNSPECIFIED
Subjects:	Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management > Human Resource Management > Careers P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing
Divisions:	School of Computing > Master of Science in Artificial Intelligence
Depositing User:	Ciara O'Brien
Date Deposited:	20 Aug 2026 09:56
Last Modified:	20 Aug 2026 09:56
URI:	https://norma.ncirl.ie/id/eprint/9564

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