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1716851 Vol 9 · Issue 10 Download Paper

PlaceReady: An Intelligent AI System for Placement Skill Development

D. V. Rajkumar Akash V. Anishkumar R. Gokul S.

Subject area: Science,Engineering and Technology  ·  Area of research: Artificial Intelligence

DOI: 10.64388/IREV9I10-1716851

Abstract

PlaceReady is an intelligent AI-based platform designed to enhance campus placement preparation for students. The system integrates aptitude training, group discussion simulation, and mock interview practice into a single unified environment. Based on the selected job role, the system dynamically generates relevant questions and interview scenarios that reflect real recruitment processes. Natural Language Processing (NLP) techniques are used to analyze user responses and provide automated feedback to improve communication, problem-solving ability, and technical knowledge. The proposed system offers personalized training, reduces dependency on manual evaluation, and improves the overall readiness of students for campus placements.

Keywords

Artificial Intelligence, Placement Training, NLP, Mock Interview System, Skill Development

References

[1] Artificial Intelligence: A Modern Approach – Stuart Russell and Peter Norvig, Pearson Education, 2021.

[2] Introduction to Algorithms – Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, MIT Press, 2009.

[3] Computer Organization and Design – David A. Patterson and John L. Hennessy, Morgan Kaufmann, 2019.

[4] Pattern Recognition and Machine Learning – Christopher M. Bishop, Springer, 2006.

[5] Machine Learning – Tom M. Mitchell, McGraw-Hill, 1997.

[6] ’Deep Learning – Ian Goodfellow, Yoshua Bengio, Aaron Courville, MIT Press, 2016.

[7] Data Mining: Concepts and Techniques – Jiawei Han, Micheline Kamber, Jian Pei, Morgan Kaufmann, 2012.

[8] Digital Design – Morris Mano, Pearson Education, 2014.

[9] Computer Networks – Andrew S. Tanenbaum, Pearson Education, 2009.

[10] Operating System Concepts – Abraham Silberschatz, Peter B. Galvin, Greg Gagne, Wiley, 2019.

[11] Institute of Electrical and Electronics Engineers Digital Library, 2007.

[12] Association for Computing Machinery Digital Library, 2003.

[13] International Organization for Standardization Standards documentation, 2021.

[14] World Wide Web Consortium Web technology standards, 2010.

[15] National Institute of Standards and Technology Technical reports, 2015.

How to cite this paper

D. V. Rajkumar, Akash V., Anishkumar R., Gokul S. "PlaceReady: An Intelligent AI System for Placement Skill Development" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 2815-2820 https://doi.org/10.64388/IREV9I10-1716851
D. V. Rajkumar, Akash V., Anishkumar R., Gokul S. "PlaceReady: An Intelligent AI System for Placement Skill Development" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026, doi: https://doi.org/10.64388/IREV9I10-1716851
D. V. Rajkumar, Akash V., Anishkumar R., Gokul S. (2026). PlaceReady: An Intelligent AI System for Placement Skill Development. Iconic Research And Engineering Journals, 9(10). doi: https://doi.org/10.64388/IREV9I10-1716851
D. V. Rajkumar, Akash V., Anishkumar R., Gokul S. "PlaceReady: An Intelligent AI System for Placement Skill Development" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026. Crossref, https://doi.org/10.64388/IREV9I10-1716851
@article{1716851,
      author = {D. V. Rajkumar, Akash V., Anishkumar R., Gokul S.},
      title = {PlaceReady: An Intelligent AI System for Placement Skill Development},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {10},
      pages = {2815-2820},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1716851.pdf},
      abstract = {PlaceReady is an intelligent AI-based platform designed to enhance campus placement preparation for students. The system integrates aptitude training, group discussion simulation, and mock interview practice into a single unified environment. Based on the selected job role, the system dynamically generates relevant questions and interview scenarios that reflect real recruitment processes. Natural Language Processing (NLP) techniques are used to analyze user responses and provide automated feedback to improve communication, problem-solving ability, and technical knowledge. The proposed system offers personalized training, reduces dependency on manual evaluation, and improves the overall readiness of students for campus placements.},
      keywords = {Artificial Intelligence, Placement Training, NLP, Mock Interview System, Skill Development},
      month = {April},
      doi = {https://doi.org/10.64388/IREV9I10-1716851}
  }