Multi-class Resume Classification Framework for Skill Extraction

Karmakar, Anwesha (2023) Multi-class Resume Classification Framework for Skill Extraction. Masters thesis, Dublin, National College of Ireland.

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Abstract

Skill extraction identifies and extracts technical and soft skills from resumes such as programming and problem solving. Current research uses machine learning and deep learning technologies for extracting skills from resumes. However, the challenge is in identifying high-level skills such as web development from low-level skills such as HTML. This research proposes a Multiclass Resume Classification framework to assist recruiters in hiring candidates with the right technical skills. The proposed framework combines an optimal transfer learning-based word embedding model with deep learning resume classification model. A deep learning text classification model is trained using resume corpus dataset consisting of 29,783 resumes to classify ten classes of occupations. Contextual word embedding and deep learning technique named Bidirectional Long Short-Term Memory (BiLSTM) is applied. Results of the model are presented based on accuracy, loss, precision, sensitivity, and specificity. This research shows promise for the proposed model in classifying resumes into different categories.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Stynes, Paul UNSPECIFIED Clifford, William UNSPECIFIED McLaughlin, Eugene UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management > Human Resource Management > Recruitment
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Tamara Malone
Date Deposited:	25 Nov 2024 13:55
Last Modified:	25 Nov 2024 13:55
URI:	https://norma.ncirl.ie/id/eprint/7195

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