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1724707 Vol 10 · Issue 5 Download Paper

Career Recommendation System

Neela Chandana Mamidi Hema Hasini Pandari Pragnya Shri Marella Amulya Dr. Dharmendra K Roy

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

Abstract

The Career Recommendation System is a proposed web-based application designed to help students identify suitable career paths based on their skills, educational qualifications, interests and experience. In today’s competitive job market, students often face difficulties in choosing the right career, understanding industry requirements, identifying skill gaps and preparing professional resumes. Traditional career guidance methods may not always provide personalized recommendations based on an individual’s profile and career goals. The proposed Career Recommendation System provides a centralized platform where users can create and manage their profiles, receive personalized career recommendations, analyze the skills required for specific careers and build professional resumes. The system also incorporates AI-based assistance to generate relevant career suggestions and internship or job recommendations, helping students explore opportunities that align with their qualifications and interests. Additionally, the resume builder enables users to create and preview resumes and download them in PDF format. The project aims to make career planning more accessible, personalized and efficient by combining profile management, career guidance, skill gap analysis and AI-assisted recommendations in a single platform. It provides a foundation for future enhancements such as real-time job portal integration, advanced machine learning-based recommendation algorithms, aptitude assessment, career trend analysis and personalized learning path suggestions.

Keywords

Career Recommendation System; Career Guidance; Artificial Intelligence; Personalized Recommendations; Skill Gap Analysis; Resume Builder; Job Recommendations; Internship Recommendations; Student Profile Management; Career Planning

References

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[2] Sribharathi B, Balamurugan SV, Megavarmaraj S, Deepak S, Kajendhiran S (2025). Scopira: An AI-driven career guidance system using resume parsing, skill gap analysis, and intelligent job matching. In: Proceedings of the International Conference on Smart Structures and Systems (ICSSS), pp. 1–8. https://doi.org/10.1109/ICSSS66939.2025.11346170

[3] Tejwani R, Mehta A, Sabale S, Pannase O, Dedgaonkar SG, Lal B (2025). Real-time job recommendation using transformer embeddings and vector similarity matching. In: Proceedings of the IEEE International Conference on ICT in Business Industry & Government (ICTBIG), pp. 1–8. https://doi.org/10.1109/ICTBIG68706.2025.11323827

[4] Deshmukh S, Bajaj A (2024). CareerBoost: A hybrid RAG-NLP job recommendation framework. In: Proceedings of the International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), pp. 853–858. https://doi.org/10.1109/I-SMAC61858.2024.10714727

[5] Mirajkar R, Shinde GR, Shelke PM, Yadav S, Shinde B, Shinde G (2024). Skill recommendation system and resume analysis using AI. In: Proceedings of the IEEE Pune Section International Conference (PuneCon), pp. 1–3. https://doi.org/10.1109/PuneCon63413.2024.10895306

[6] Qamhieh M, Sammaneh H, Demaidi MN (2020). PCRS: Personalized career-path recommender system for engineering students. IEEE Access, 8, 214039–214049. https://doi.org/10.1109/ACCESS.2020.3040338

[7] Abdul Rashid AH, Mohamad M, Masrom S, Selamat A (2022). Student career recommendation system using content-based filtering method. In: Proceedings of the International Conference on Artificial Intelligence and Data Sciences (AiDAS), pp. 60–65. https://doi.org/10.1109/AiDAS56890.2022.9918766

[8] Panchasara S, Gupta RK, Sharma A (2023). AI based job recommendation system using BERT. In: Proceedings of the 7th International Conference on Computing, Communication, Control and Automation (ICCUBEA), pp. 1–6. https://doi.org/10.1109/ICCUBEA58933.2023.10392119

[9] Rajput A, Dubey A, Thakur R, Singh D, Singh UP (2024). Career Craft AI: A personalized resume analysis and job recommendations system. In: Proceedings of the 1st International Conference on Innovative Sustainable Technologies for Energy, Mechatronics, and Smart Systems (ISTEMS), pp. 1–6. https://doi.org/10.1109/ISTEMS60181.2024.10560126

How to cite this paper

Neela Chandana, Mamidi Hema Hasini, Pandari Pragnya Shri, Marella Amulya, Dr. Dharmendra K Roy "Career Recommendation System" Iconic Research And Engineering Journals Volume 10 Issue 5 2026 Page 785-797
Neela Chandana, Mamidi Hema Hasini, Pandari Pragnya Shri, Marella Amulya, Dr. Dharmendra K Roy "Career Recommendation System" Iconic Research And Engineering Journals, vol. 10, no. 5, Nov. 2026
Neela Chandana, Mamidi Hema Hasini, Pandari Pragnya Shri, Marella Amulya, Dr. Dharmendra K Roy (2026). Career Recommendation System. Iconic Research And Engineering Journals, 10(5).
Neela Chandana, Mamidi Hema Hasini, Pandari Pragnya Shri, Marella Amulya, Dr. Dharmendra K Roy "Career Recommendation System" Iconic Research And Engineering Journals, vol. 10, no. 5, Nov. 2026.
@article{1724707,
      author = {Neela Chandana, Mamidi Hema Hasini, Pandari Pragnya Shri, Marella Amulya, Dr. Dharmendra K Roy},
      title = {Career Recommendation System},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {5},
      pages = {785-797},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1724707.pdf},
      abstract = {The Career Recommendation System is a proposed web-based application designed to help students identify suitable career paths based on their skills, educational qualifications, interests and experience. In today’s competitive job market, students often face difficulties in choosing the right career, understanding industry requirements, identifying skill gaps and preparing professional resumes. Traditional career guidance methods may not always provide personalized recommendations based on an individual’s profile and career goals.

The proposed Career Recommendation System provides a centralized platform where users can create and manage their profiles, receive personalized career recommendations, analyze the skills required for specific careers and build professional resumes. The system also incorporates AI-based assistance to generate relevant career suggestions and internship or job recommendations, helping students explore opportunities that align with their qualifications and interests. Additionally, the resume builder enables users to create and preview resumes and download them in PDF format.

The project aims to make career planning more accessible, personalized and efficient by combining profile management, career guidance, skill gap analysis and AI-assisted recommendations in a single platform. It provides a foundation for future enhancements such as real-time job portal integration, advanced machine learning-based recommendation algorithms, aptitude assessment, career trend analysis and personalized learning path suggestions.},
      keywords = {Career Recommendation System; Career Guidance; Artificial Intelligence; Personalized Recommendations; Skill Gap Analysis; Resume Builder; Job Recommendations; Internship Recommendations; Student Profile Management; Career Planning},
      month = {November},
  }