Published on: October 2026
CAMPUSHIRE: AN AI-POWERED TRAINING AND PLACEMENT MANAGEMENT SYSTEM WITH EXPLAINABLE SKILL MATCHING
Amit Hirole Om Talokar Sejal Chandekar Sakshi Hage Komal Tiwari
Guru Nanak Institute of Engineering and Technology
Nagpur, Maharashtra, India
Article Status
Available Documents
Abstract
Index Terms—Campus recruitment, content-based recommendation, explainable matching, job recommendation, placement management system, role-based access control, skill-gap analysis, web application.
How to Cite this Paper
Hirole, A., Talokar, O., Chandekar, S., Hage, S. & Tiwari, K. (2026). CampusHire: An AI-Powered Training and Placement Management System with Explainable Skill Matching. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(10), 1-9. https://doi.org/10.55041/ijcope.v2i10.037
Hirole, Amit, et al.. "CampusHire: An AI-Powered Training and Placement Management System with Explainable Skill Matching." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 10, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i10.037.
Hirole, Amit,Om Talokar,Sejal Chandekar,Sakshi Hage, and Komal Tiwari. "CampusHire: An AI-Powered Training and Placement Management System with Explainable Skill Matching." International Journal of Creative and Open Research in Engineering and Management 02, no. 10 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i10.037.
References
- Siting, H. Wenxing, Z. Ning, and Y. Fan, “Job recommender systems: A survey,” in Proc. 7th Int. Conf. Comput. Sci. Educ. (ICCSE), Melbourne, VIC, Australia, 2012, pp. 920–924, doi: 10.1109/ICCSE.2012.6295216.
- de Ruijt and S. Bhulai, “Job recommender systems: A review,” 2021, arXiv:2111.13576.
- Zhu, H. Zhu, H. Xiong, C. Ma, F. Xie, P. Ding, and P. Li, “Person-job fit: Adapting the right talent for the right job with joint representation learning,” ACM Trans. Manage. Inf. Syst., vol. 9, no. 3, 1–17, 2018.
- Qin, H. Zhu, T. Xu, C. Zhu, L. Jiang, E. Chen, and H. Xiong, “Enhancing person-job fit for talent recruitment: An ability-aware neural network approach,” in Proc. 41st Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, Ann Arbor, MI, USA, 2018, pp. 25–34, doi: 10.1145/3209978.3210025.
- K. Thangavel, P. D. Bkaratki, and A. Sankar, “Student placement analyzer: A recommendation system using machine learning,” in Proc. 4th Int. Conf. Adv. Comput. Commun. Syst. (ICACCS), Coimbatore, India, 2017, doi: 10.1109/ICACCS.2017.8014632.
- Aravind, B. S. Reddy, S. Avinash, and G. Jeyakumar, “A comparative study on machine learning algorithms for predicting the placement information of under graduate students,” in Proc. 3rd Int. Conf. I-SMAC (IoT in Social, Mobile, Analytics and Cloud), Palladam, India, 2019.
- Malinowski, T. Keim, O. Wendt, and T. Weitzel, “Matching people and jobs: A bilateral recommendation approach,” in Proc. 39th Annu. Hawaii Int. Conf. Syst. Sci. (HICSS’06), Kauai, HI, USA, 2006, vol. 6, 137c.
- Paparrizos, B. B. Cambazoglu, and A. Gionis, “Machine learned job recommendation,” in Proc. 5th ACM Conf. Recommender Syst. (RecSys), Chicago, IL, USA, 2011, pp. 325–328.
- Abel, A. Benczúr, D. Kohlsdorf, M. Larson, and R. Pálovics, “RecSys Challenge 2016: Job recommendations,” in Proc. 10th ACM Conf. Recommender Syst. (RecSys), Boston, MA, USA, 2016, pp. 425–426.
- Lops, M. de Gemmis, and G. Semeraro, “Content-based recommender systems: State of the art and trends,” in Recommender Systems Handbook, F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, Eds. Boston, MA, USA: Springer, 2011, pp. 73–105.
Ethical Compliance & Review Process
- •All submissions are screened under plagiarism detection.
- •Review follows editorial policy.
- •Authors retain copyright.
- •Peer Review Type: Double-Blind Peer Review
- •Published on: Oct 07 2026
This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.

