Next Step: A Hybrid AI Framework for Demand-Driven Career Recommendation Using Skill Gap Quantification and Semantic Similarity

Velan G,; Dr Asha N; Leena Swarna Devi

doi:10.59256/ijrtmr.20260603034

Original Article

Next Step: A Hybrid AI Framework for Demand-Driven Career Recommendation Using Skill Gap Quantification and Semantic Similarity

Paper ID 384
Volume 6, Issue 3
Pages 297-306
Published Online: May-June 2026
15 Views

Open Access Peer Reviewed Crossref DOI

Authors

Velan G,¹
Dr Asha N²
Leena Swarna Devi³

¹ Student, Department of Computer Science, Nrupathunga University formly Government Science College, Bengaluru, Karnataka, India. ²,³Associate Professor, Department of Computer Science, Nrupathunga University formly Government Science College, Bengaluru, Karnataka, India.

View PDF Download PDF Cite this article

Article Information

DOI: https://www.doi.org/10.59256/ijrtmr.20260603034
Published In: Volume 6, Issue 3 (2026)
Published Online: May-June 2026
Pages: 297-306
Article Type: Original Article
Check for updates

Citations

Velan G, Dr Asha N, Leena Swarna Devi, “Next Step: A Hybrid AI Framework for Demand-Driven Career Recommendation Using Skill Gap Quantification and Semantic Similarity”, International Journal of Recent Trends in Multidisciplinary Research, May-June 2026, Vol 6(03), 297-306

Next Step: A Hybrid AI Framework for Demand-Driven Career Recommendation Using Skill Gap Quantification and Semantic Similarity

Article Information

Citations

Related Articles